From 4b3d32b4e2e18e1320550e398ea5e918d16d5b04 Mon Sep 17 00:00:00 2001
From: Chanin Nantasenamat <51851491+dataprofessor@users.noreply.github.com>
Date: Wed, 6 Jan 2021 11:06:13 +0700
Subject: [PATCH 01/11] Add files via upload

---
 python/klib.ipynb | 2809 +++++++++++++++++++++++++++++++++++++++++++++
 1 file changed, 2809 insertions(+)
 create mode 100644 python/klib.ipynb

diff --git a/python/klib.ipynb b/python/klib.ipynb
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+{
+  "nbformat": 4,
+  "nbformat_minor": 0,
+  "metadata": {
+    "colab": {
+      "name": "klib.ipynb",
+      "provenance": [],
+      "collapsed_sections": []
+    },
+    "kernelspec": {
+      "name": "python3",
+      "display_name": "Python 3"
+    }
+  },
+  "cells": [
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "HjrfJDqnXWWH"
+      },
+      "source": [
+        "# **How to Speed Up Data Cleaning with the klib Python library**\n",
+        "\n",
+        "Chanin Nantasenamat\n",
+        "\n",
+        "[Data Professor YouTube channel](http://youtube.com/dataprofessor), http://youtube.com/dataprofessor\n",
+        "\n",
+        "---\n",
+        "**Further reading:**\n",
+        "* [Andreas Kanz @ Medium](https://medium.com/@akanz)\n",
+        "* [klib Examples on GitHub](https://github.com/akanz1/klib/tree/main/examples)\n",
+        "* [klib on Towards Data Science](https://towardsdatascience.com/speed-up-your-data-cleaning-and-preprocessing-with-klib-97191d320f80)\n",
+        "* [klib Documentation](https://klib.readthedocs.io/en/latest/)"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "cWgopKUOzDTR"
+      },
+      "source": [
+        "# **Install klib**"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "2QV7BW7xXVXV",
+        "outputId": "a6f3b0b3-32ef-4e75-a1f7-f876477c46a9"
+      },
+      "source": [
+        "! pip install klib"
+      ],
+      "execution_count": null,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "text": [
+            "Collecting klib\n",
+            "  Downloading https://files.pythonhosted.org/packages/89/bc/5c289a2f573ca02f5c5429592d26e3e67ade4998f7e432fc5d5a8be2d174/klib-0.0.89-py3-none-any.whl\n",
+            "Requirement already satisfied: pandas>=1.0.0 in /usr/local/lib/python3.6/dist-packages (from klib) (1.1.5)\n",
+            "Requirement already satisfied: seaborn>=0.1.0 in /usr/local/lib/python3.6/dist-packages (from klib) (0.11.0)\n",
+            "Requirement already satisfied: numpy>=1.13.3 in /usr/local/lib/python3.6/dist-packages (from klib) (1.19.4)\n",
+            "Requirement already satisfied: matplotlib>=2.1.2 in /usr/local/lib/python3.6/dist-packages (from klib) (3.2.2)\n",
+            "Requirement already satisfied: scikit-learn>=0.22 in /usr/local/lib/python3.6/dist-packages (from klib) (0.22.2.post1)\n",
+            "Requirement already satisfied: python-dateutil>=2.7.3 in /usr/local/lib/python3.6/dist-packages (from pandas>=1.0.0->klib) (2.8.1)\n",
+            "Requirement already satisfied: pytz>=2017.2 in /usr/local/lib/python3.6/dist-packages (from pandas>=1.0.0->klib) (2018.9)\n",
+            "Requirement already satisfied: scipy>=1.0 in /usr/local/lib/python3.6/dist-packages (from seaborn>=0.1.0->klib) (1.4.1)\n",
+            "Requirement already satisfied: kiwisolver>=1.0.1 in /usr/local/lib/python3.6/dist-packages (from matplotlib>=2.1.2->klib) (1.3.1)\n",
+            "Requirement already satisfied: cycler>=0.10 in /usr/local/lib/python3.6/dist-packages (from matplotlib>=2.1.2->klib) (0.10.0)\n",
+            "Requirement already satisfied: pyparsing!=2.0.4,!=2.1.2,!=2.1.6,>=2.0.1 in /usr/local/lib/python3.6/dist-packages (from matplotlib>=2.1.2->klib) (2.4.7)\n",
+            "Requirement already satisfied: joblib>=0.11 in /usr/local/lib/python3.6/dist-packages (from scikit-learn>=0.22->klib) (1.0.0)\n",
+            "Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.6/dist-packages (from python-dateutil>=2.7.3->pandas>=1.0.0->klib) (1.15.0)\n",
+            "Installing collected packages: klib\n",
+            "Successfully installed klib-0.0.89\n"
+          ],
+          "name": "stdout"
+        }
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "IdFTspYMazKx"
+      },
+      "source": [
+        "# **Missing Values Plot**\n",
+        "\n",
+        "Here we can examine the data quality. In other words, how clean is the dataset?\n",
+        "\n",
+        "***missingval_plot()*** - provides a high-level overview of the missing values in a dataset. It pinpoints which columns and rows to examine in more detail.\n",
+        "\n",
+        "**Top** portion of the plot shows the aggregate for each column. Summary statistics is displayed on the right most side.\n",
+        "\n",
+        "**Bottom** portion of the plot shows the missing values (black colors) in the DataFrame."
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 715
+        },
+        "id": "9SMR3_bGYH5d",
+        "outputId": "851e1af4-d6a3-414d-f6ae-571e943eda91"
+      },
+      "source": [
+        "# NFL Dataset\n",
+        "import klib\n",
+        "import pandas as pd\n",
+        "\n",
+        "df = pd.read_csv('https://github.com/akanz1/klib/raw/main/examples/NFL_DATASET.csv')\n",
+        "klib.missingval_plot(df)"
+      ],
+      "execution_count": null,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "GridSpec(6, 6)"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 2
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "image/png": 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\n",
+            "text/plain": [
+              "<Figure size 1440x1440 with 4 Axes>"
+            ]
+          },
+          "metadata": {
+            "tags": [],
+            "needs_background": "light"
+          }
+        }
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "GTwPToNepHy3"
+      },
+      "source": [
+        "# **Data Cleaning**\n",
+        "\n",
+        "The ***data_cleaning()*** function essentially drops empty and single valued columns as well as empty and duplicate rows."
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "u1waScSfpKcT",
+        "outputId": "85d30425-ab23-44e0-ed4d-9810479b3e2d"
+      },
+      "source": [
+        "df_cleaned = klib.data_cleaning(df)"
+      ],
+      "execution_count": null,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "text": [
+            "Shape of cleaned data: (183460, 63) - Remaining NAs: 1757318\n",
+            "\n",
+            "Changes:\n",
+            "Dropped rows: 0\n",
+            "     of which 0 duplicates. (Rows: [])\n",
+            "Dropped columns: 4\n",
+            "     of which 1 single valued. (Columns: ['PlayAttempted'])\n",
+            "Dropped missing values: 520667\n",
+            "Reduced memory by at least: 59.37 MB (-63.3%)\n"
+          ],
+          "name": "stdout"
+        }
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "enUcOWWidMbP"
+      },
+      "source": [
+        "# **Correlation Plot**\n",
+        "\n",
+        "Here, we can examine the intercorrelation amongst the features."
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "szW70rtefazL"
+      },
+      "source": [
+        "### Display all correlations data."
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 611
+        },
+        "id": "P3E108xue2ZR",
+        "outputId": "74ef4e07-3547-4789-ccf7-1d10f083f1ea"
+      },
+      "source": [
+        "klib.corr_plot(df_cleaned, annot=False)"
+      ],
+      "execution_count": null,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "<matplotlib.axes._subplots.AxesSubplot at 0x7f414af6a7f0>"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 5
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "image/png": 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\n",
+            "text/plain": [
+              "<Figure size 864x720 with 2 Axes>"
+            ]
+          },
+          "metadata": {
+            "tags": [],
+            "needs_background": "light"
+          }
+        }
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "eeRm_1KnfgLJ"
+      },
+      "source": [
+        "### Display only positive correlation."
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 659
+        },
+        "id": "tQfukbI5aSQo",
+        "outputId": "2dcf4ff5-1151-49aa-f242-8747db88fbd2"
+      },
+      "source": [
+        "klib.corr_plot(df_cleaned, split='pos', annot=False)"
+      ],
+      "execution_count": null,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "text": [
+            "Displaying positive correlations. Use \"threshold\" to further limit the results.\n"
+          ],
+          "name": "stdout"
+        },
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "<matplotlib.axes._subplots.AxesSubplot at 0x7f414a6172b0>"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 6
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "image/png": 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\n",
+            "text/plain": [
+              "<Figure size 864x720 with 2 Axes>"
+            ]
+          },
+          "metadata": {
+            "tags": [],
+            "needs_background": "light"
+          }
+        }
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "x8--KKRqfokd"
+      },
+      "source": [
+        "### Display only negative correlation."
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 653
+        },
+        "id": "-FJsZveUdrEB",
+        "outputId": "c5257101-9f89-459a-a7a9-09839b397fcd"
+      },
+      "source": [
+        "klib.corr_plot(df_cleaned, split='neg', annot=False)"
+      ],
+      "execution_count": null,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "text": [
+            "Displaying negative correlations. Use \"threshold\" to further limit the results.\n"
+          ],
+          "name": "stdout"
+        },
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "<matplotlib.axes._subplots.AxesSubplot at 0x7f414a41ee10>"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 7
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "image/png": 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\n",
+            "text/plain": [
+              "<Figure size 864x720 with 2 Axes>"
+            ]
+          },
+          "metadata": {
+            "tags": [],
+            "needs_background": "light"
+          }
+        }
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "L-yQ9uG3fsOj"
+      },
+      "source": [
+        "Display correlation with a target variable of interest"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 534
+        },
+        "id": "9--UAToOeGzp",
+        "outputId": "5b087884-199e-43f9-c496-56b46c9e855c"
+      },
+      "source": [
+        "klib.corr_plot(df_cleaned, target='Touchdown')"
+      ],
+      "execution_count": null,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "<matplotlib.axes._subplots.AxesSubplot at 0x7f414a288198>"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 8
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "image/png": 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\n",
+            "text/plain": [
+              "<Figure size 864x720 with 2 Axes>"
+            ]
+          },
+          "metadata": {
+            "tags": [],
+            "needs_background": "light"
+          }
+        }
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "vW77Oi6Yod4U"
+      },
+      "source": [
+        "### Correlation data matrix"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 1000
+        },
+        "id": "EQ0_dfrherzw",
+        "outputId": "20a5d58b-a3ee-463d-f08b-1e5eb8642712"
+      },
+      "source": [
+        "klib.corr_mat(df_cleaned)"
+      ],
+      "execution_count": null,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/html": [
+              "<style  type=\"text/css\" >\n",
+              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+              "            color:  None;\n",
+              "        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+              "            color:  #FF3344;\n",
+              "        }</style><table id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >Unnamed: 0</th>        <th class=\"col_heading level0 col1\" >qtr</th>        <th class=\"col_heading level0 col2\" >down</th>        <th class=\"col_heading level0 col3\" >TimeUnder</th>        <th class=\"col_heading level0 col4\" >PlayTimeDiff</th>        <th class=\"col_heading level0 col5\" >yrdln</th>        <th class=\"col_heading level0 col6\" >ydstogo</th>        <th class=\"col_heading level0 col7\" >ydsnet</th>        <th class=\"col_heading level0 col8\" >GoalToGo</th>        <th class=\"col_heading level0 col9\" >FirstDown</th>        <th class=\"col_heading level0 col10\" >Yards.Gained</th>        <th class=\"col_heading level0 col11\" >sp</th>        <th class=\"col_heading level0 col12\" >Touchdown</th>        <th class=\"col_heading level0 col13\" >Safety</th>        <th class=\"col_heading level0 col14\" >Onsidekick</th>        <th class=\"col_heading level0 col15\" >PassAttempt</th>        <th class=\"col_heading level0 col16\" >AirYards</th>        <th class=\"col_heading level0 col17\" >YardsAfterCatch</th>        <th class=\"col_heading level0 col18\" >QBHit</th>        <th class=\"col_heading level0 col19\" >InterceptionThrown</th>        <th class=\"col_heading level0 col20\" >RushAttempt</th>        <th class=\"col_heading level0 col21\" >Reception</th>        <th class=\"col_heading level0 col22\" >Fumble</th>        <th class=\"col_heading level0 col23\" >Sack</th>        <th class=\"col_heading level0 col24\" >Challenge.Replay</th>        <th class=\"col_heading level0 col25\" >Opp_Field_Goal_Prob</th>        <th class=\"col_heading level0 col26\" >Opp_Safety_Prob</th>        <th class=\"col_heading level0 col27\" >Opp_Touchdown_Prob</th>        <th class=\"col_heading level0 col28\" >Field_Goal_Prob</th>        <th class=\"col_heading level0 col29\" >Safety_Prob</th>        <th class=\"col_heading level0 col30\" >Touchdown_Prob</th>        <th class=\"col_heading level0 col31\" >ExPoint_Prob</th>        <th class=\"col_heading level0 col32\" >TwoPoint_Prob</th>        <th class=\"col_heading level0 col33\" >ExpPts</th>        <th class=\"col_heading level0 col34\" >EPA</th>        <th class=\"col_heading level0 col35\" >airEPA</th>        <th class=\"col_heading level0 col36\" >yacEPA</th>        <th class=\"col_heading level0 col37\" >Home_WP_pre</th>        <th class=\"col_heading level0 col38\" >Away_WP_pre</th>        <th class=\"col_heading level0 col39\" >Home_WP_post</th>        <th class=\"col_heading level0 col40\" >Away_WP_post</th>        <th class=\"col_heading level0 col41\" >Win_Prob</th>        <th class=\"col_heading level0 col42\" >WPA</th>        <th class=\"col_heading level0 col43\" >airWPA</th>        <th class=\"col_heading level0 col44\" >yacWPA</th>    </tr></thead><tbody>\n",
+              "                <tr>\n",
+              "                        <th id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002level0_row0\" class=\"row_heading level0 row0\" >Unnamed: 0</th>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row0_col0\" class=\"data row0 col0\" >1.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row0_col1\" class=\"data row0 col1\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row0_col2\" class=\"data row0 col2\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row0_col3\" class=\"data row0 col3\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row0_col4\" class=\"data row0 col4\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row0_col5\" class=\"data row0 col5\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row0_col6\" class=\"data row0 col6\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row0_col7\" class=\"data row0 col7\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row0_col8\" class=\"data row0 col8\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row0_col9\" class=\"data row0 col9\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row0_col10\" class=\"data row0 col10\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row0_col11\" class=\"data row0 col11\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row0_col12\" class=\"data row0 col12\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row0_col13\" class=\"data row0 col13\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row0_col14\" class=\"data row0 col14\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row0_col15\" class=\"data row0 col15\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row0_col16\" class=\"data row0 col16\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row0_col17\" class=\"data row0 col17\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row0_col18\" class=\"data row0 col18\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row0_col19\" class=\"data row0 col19\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row0_col20\" class=\"data row0 col20\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row0_col21\" class=\"data row0 col21\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row0_col22\" class=\"data row0 col22\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row0_col23\" class=\"data row0 col23\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row0_col24\" class=\"data row0 col24\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row0_col25\" class=\"data row0 col25\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row0_col26\" class=\"data row0 col26\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row0_col27\" class=\"data row0 col27\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row0_col28\" class=\"data row0 col28\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row0_col29\" class=\"data row0 col29\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row0_col30\" class=\"data row0 col30\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row0_col31\" class=\"data row0 col31\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row0_col32\" class=\"data row0 col32\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row0_col33\" class=\"data row0 col33\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row0_col34\" class=\"data row0 col34\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row0_col35\" class=\"data row0 col35\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row0_col36\" class=\"data row0 col36\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row0_col37\" class=\"data row0 col37\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row0_col38\" class=\"data row0 col38\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row0_col39\" class=\"data row0 col39\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row0_col40\" class=\"data row0 col40\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row0_col41\" class=\"data row0 col41\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row0_col42\" class=\"data row0 col42\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row0_col43\" class=\"data row0 col43\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row0_col44\" class=\"data row0 col44\" >0.00</td>\n",
+              "            </tr>\n",
+              "            <tr>\n",
+              "                        <th id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002level0_row1\" class=\"row_heading level0 row1\" >qtr</th>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row1_col0\" class=\"data row1 col0\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row1_col1\" class=\"data row1 col1\" >1.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row1_col2\" class=\"data row1 col2\" >0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row1_col3\" class=\"data row1 col3\" >-0.03</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row1_col4\" class=\"data row1 col4\" >-0.06</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row1_col5\" class=\"data row1 col5\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row1_col6\" class=\"data row1 col6\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row1_col7\" class=\"data row1 col7\" >0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row1_col8\" class=\"data row1 col8\" >0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row1_col9\" class=\"data row1 col9\" >-0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row1_col10\" class=\"data row1 col10\" >-0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row1_col11\" class=\"data row1 col11\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row1_col12\" class=\"data row1 col12\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row1_col13\" class=\"data row1 col13\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row1_col14\" class=\"data row1 col14\" >0.04</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row1_col15\" class=\"data row1 col15\" >0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row1_col16\" class=\"data row1 col16\" >0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row1_col17\" class=\"data row1 col17\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row1_col18\" class=\"data row1 col18\" >0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row1_col19\" class=\"data row1 col19\" >0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row1_col20\" class=\"data row1 col20\" >-0.04</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row1_col21\" class=\"data row1 col21\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row1_col22\" class=\"data row1 col22\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row1_col23\" class=\"data row1 col23\" >0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row1_col24\" class=\"data row1 col24\" >0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row1_col25\" class=\"data row1 col25\" >-0.16</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row1_col26\" class=\"data row1 col26\" >-0.10</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row1_col27\" class=\"data row1 col27\" >-0.17</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row1_col28\" class=\"data row1 col28\" >-0.07</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row1_col29\" class=\"data row1 col29\" >-0.18</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row1_col30\" class=\"data row1 col30\" >-0.11</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row1_col31\" class=\"data row1 col31\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row1_col32\" class=\"data row1 col32\" >0.04</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row1_col33\" class=\"data row1 col33\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row1_col34\" class=\"data row1 col34\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row1_col35\" class=\"data row1 col35\" >0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row1_col36\" class=\"data row1 col36\" >-0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row1_col37\" class=\"data row1 col37\" >0.04</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row1_col38\" class=\"data row1 col38\" >-0.03</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row1_col39\" class=\"data row1 col39\" >0.04</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row1_col40\" class=\"data row1 col40\" >-0.03</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row1_col41\" class=\"data row1 col41\" >-0.03</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row1_col42\" class=\"data row1 col42\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row1_col43\" class=\"data row1 col43\" >0.04</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row1_col44\" class=\"data row1 col44\" >-0.04</td>\n",
+              "            </tr>\n",
+              "            <tr>\n",
+              "                        <th id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002level0_row2\" class=\"row_heading level0 row2\" >down</th>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row2_col0\" class=\"data row2 col0\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row2_col1\" class=\"data row2 col1\" >0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row2_col2\" class=\"data row2 col2\" >1.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row2_col3\" class=\"data row2 col3\" >-0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row2_col4\" class=\"data row2 col4\" >0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row2_col5\" class=\"data row2 col5\" >0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row2_col6\" class=\"data row2 col6\" >-0.24</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row2_col7\" class=\"data row2 col7\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row2_col8\" class=\"data row2 col8\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row2_col9\" class=\"data row2 col9\" >0.28</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row2_col10\" class=\"data row2 col10\" >-0.05</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row2_col11\" class=\"data row2 col11\" >0.17</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row2_col12\" class=\"data row2 col12\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row2_col13\" class=\"data row2 col13\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row2_col14\" class=\"data row2 col14\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row2_col15\" class=\"data row2 col15\" >-0.06</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row2_col16\" class=\"data row2 col16\" >-0.03</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row2_col17\" class=\"data row2 col17\" >-0.04</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row2_col18\" class=\"data row2 col18\" >0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row2_col19\" class=\"data row2 col19\" >0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row2_col20\" class=\"data row2 col20\" >-0.30</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row2_col21\" class=\"data row2 col21\" >-0.06</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row2_col22\" class=\"data row2 col22\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row2_col23\" class=\"data row2 col23\" >0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row2_col24\" class=\"data row2 col24\" >0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row2_col25\" class=\"data row2 col25\" >0.25</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row2_col26\" class=\"data row2 col26\" >0.07</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row2_col27\" class=\"data row2 col27\" >0.22</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row2_col28\" class=\"data row2 col28\" >0.17</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row2_col29\" class=\"data row2 col29\" >0.22</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row2_col30\" class=\"data row2 col30\" >-0.45</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row2_col31\" class=\"data row2 col31\" >-</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row2_col32\" class=\"data row2 col32\" >-</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row2_col33\" class=\"data row2 col33\" >-0.33</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row2_col34\" class=\"data row2 col34\" >0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row2_col35\" class=\"data row2 col35\" >0.15</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row2_col36\" class=\"data row2 col36\" >-0.11</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row2_col37\" class=\"data row2 col37\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row2_col38\" class=\"data row2 col38\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row2_col39\" class=\"data row2 col39\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row2_col40\" class=\"data row2 col40\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row2_col41\" class=\"data row2 col41\" >-0.03</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row2_col42\" class=\"data row2 col42\" >0.07</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row2_col43\" class=\"data row2 col43\" >0.10</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row2_col44\" class=\"data row2 col44\" >-0.08</td>\n",
+              "            </tr>\n",
+              "            <tr>\n",
+              "                        <th id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002level0_row3\" class=\"row_heading level0 row3\" >TimeUnder</th>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row3_col0\" class=\"data row3 col0\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row3_col1\" class=\"data row3 col1\" >-0.03</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row3_col2\" class=\"data row3 col2\" >-0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row3_col3\" class=\"data row3 col3\" >1.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row3_col4\" class=\"data row3 col4\" >0.10</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row3_col5\" class=\"data row3 col5\" >0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row3_col6\" class=\"data row3 col6\" >0.09</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row3_col7\" class=\"data row3 col7\" >-0.07</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row3_col8\" class=\"data row3 col8\" >-0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row3_col9\" class=\"data row3 col9\" >0.09</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row3_col10\" class=\"data row3 col10\" >0.07</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row3_col11\" class=\"data row3 col11\" >-0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row3_col12\" class=\"data row3 col12\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row3_col13\" class=\"data row3 col13\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row3_col14\" class=\"data row3 col14\" >-0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row3_col15\" class=\"data row3 col15\" >0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row3_col16\" class=\"data row3 col16\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row3_col17\" class=\"data row3 col17\" >0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row3_col18\" class=\"data row3 col18\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row3_col19\" class=\"data row3 col19\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row3_col20\" class=\"data row3 col20\" >0.11</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row3_col21\" class=\"data row3 col21\" >0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row3_col22\" class=\"data row3 col22\" >0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row3_col23\" class=\"data row3 col23\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row3_col24\" class=\"data row3 col24\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row3_col25\" class=\"data row3 col25\" >0.38</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row3_col26\" class=\"data row3 col26\" >0.21</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row3_col27\" class=\"data row3 col27\" >0.41</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row3_col28\" class=\"data row3 col28\" >0.17</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row3_col29\" class=\"data row3 col29\" >0.50</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row3_col30\" class=\"data row3 col30\" >0.34</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row3_col31\" class=\"data row3 col31\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row3_col32\" class=\"data row3 col32\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row3_col33\" class=\"data row3 col33\" >0.04</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row3_col34\" class=\"data row3 col34\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row3_col35\" class=\"data row3 col35\" >-0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row3_col36\" class=\"data row3 col36\" >0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row3_col37\" class=\"data row3 col37\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row3_col38\" class=\"data row3 col38\" >0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row3_col39\" class=\"data row3 col39\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row3_col40\" class=\"data row3 col40\" >0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row3_col41\" class=\"data row3 col41\" >0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row3_col42\" class=\"data row3 col42\" >0.03</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row3_col43\" class=\"data row3 col43\" >-0.03</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row3_col44\" class=\"data row3 col44\" >0.03</td>\n",
+              "            </tr>\n",
+              "            <tr>\n",
+              "                        <th id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002level0_row4\" class=\"row_heading level0 row4\" >PlayTimeDiff</th>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row4_col0\" class=\"data row4 col0\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row4_col1\" class=\"data row4 col1\" >-0.06</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row4_col2\" class=\"data row4 col2\" >0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row4_col3\" class=\"data row4 col3\" >0.10</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row4_col4\" class=\"data row4 col4\" >1.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row4_col5\" class=\"data row4 col5\" >0.08</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row4_col6\" class=\"data row4 col6\" >0.06</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row4_col7\" class=\"data row4 col7\" >0.15</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row4_col8\" class=\"data row4 col8\" >0.04</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row4_col9\" class=\"data row4 col9\" >0.03</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row4_col10\" class=\"data row4 col10\" >-0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row4_col11\" class=\"data row4 col11\" >-0.07</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row4_col12\" class=\"data row4 col12\" >0.04</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row4_col13\" class=\"data row4 col13\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row4_col14\" class=\"data row4 col14\" >-0.04</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row4_col15\" class=\"data row4 col15\" >0.10</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row4_col16\" class=\"data row4 col16\" >0.05</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row4_col17\" class=\"data row4 col17\" >0.04</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row4_col18\" class=\"data row4 col18\" >0.03</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row4_col19\" class=\"data row4 col19\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row4_col20\" class=\"data row4 col20\" >0.11</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row4_col21\" class=\"data row4 col21\" >0.07</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row4_col22\" class=\"data row4 col22\" >0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row4_col23\" class=\"data row4 col23\" >0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row4_col24\" class=\"data row4 col24\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row4_col25\" class=\"data row4 col25\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row4_col26\" class=\"data row4 col26\" >-0.11</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row4_col27\" class=\"data row4 col27\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row4_col28\" class=\"data row4 col28\" >0.13</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row4_col29\" class=\"data row4 col29\" >0.18</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row4_col30\" class=\"data row4 col30\" >0.28</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row4_col31\" class=\"data row4 col31\" >-0.12</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row4_col32\" class=\"data row4 col32\" >-0.03</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row4_col33\" class=\"data row4 col33\" >0.21</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row4_col34\" class=\"data row4 col34\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row4_col35\" class=\"data row4 col35\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row4_col36\" class=\"data row4 col36\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row4_col37\" class=\"data row4 col37\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row4_col38\" class=\"data row4 col38\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row4_col39\" class=\"data row4 col39\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row4_col40\" class=\"data row4 col40\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row4_col41\" class=\"data row4 col41\" >0.10</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row4_col42\" class=\"data row4 col42\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row4_col43\" class=\"data row4 col43\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row4_col44\" class=\"data row4 col44\" >0.01</td>\n",
+              "            </tr>\n",
+              "            <tr>\n",
+              "                        <th id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002level0_row5\" class=\"row_heading level0 row5\" >yrdln</th>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row5_col0\" class=\"data row5 col0\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row5_col1\" class=\"data row5 col1\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row5_col2\" class=\"data row5 col2\" >0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row5_col3\" class=\"data row5 col3\" >0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row5_col4\" class=\"data row5 col4\" >0.08</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row5_col5\" class=\"data row5 col5\" >1.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row5_col6\" class=\"data row5 col6\" >0.08</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row5_col7\" class=\"data row5 col7\" >-0.19</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row5_col8\" class=\"data row5 col8\" >-0.41</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row5_col9\" class=\"data row5 col9\" >0.15</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row5_col10\" class=\"data row5 col10\" >0.09</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row5_col11\" class=\"data row5 col11\" >-0.34</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row5_col12\" class=\"data row5 col12\" >-0.19</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row5_col13\" class=\"data row5 col13\" >-0.03</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row5_col14\" class=\"data row5 col14\" >0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row5_col15\" class=\"data row5 col15\" >0.05</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row5_col16\" class=\"data row5 col16\" >0.08</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row5_col17\" class=\"data row5 col17\" >0.05</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row5_col18\" class=\"data row5 col18\" >0.03</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row5_col19\" class=\"data row5 col19\" >0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row5_col20\" class=\"data row5 col20\" >-0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row5_col21\" class=\"data row5 col21\" >0.05</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row5_col22\" class=\"data row5 col22\" >0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row5_col23\" class=\"data row5 col23\" >0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row5_col24\" class=\"data row5 col24\" >-0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row5_col25\" class=\"data row5 col25\" >0.05</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row5_col26\" class=\"data row5 col26\" >-0.30</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row5_col27\" class=\"data row5 col27\" >0.05</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row5_col28\" class=\"data row5 col28\" >0.05</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row5_col29\" class=\"data row5 col29\" >0.25</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row5_col30\" class=\"data row5 col30\" >0.07</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row5_col31\" class=\"data row5 col31\" >-0.28</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row5_col32\" class=\"data row5 col32\" >-0.08</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row5_col33\" class=\"data row5 col33\" >0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row5_col34\" class=\"data row5 col34\" >-0.04</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row5_col35\" class=\"data row5 col35\" >-0.11</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row5_col36\" class=\"data row5 col36\" >0.04</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row5_col37\" class=\"data row5 col37\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row5_col38\" class=\"data row5 col38\" >0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row5_col39\" class=\"data row5 col39\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row5_col40\" class=\"data row5 col40\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row5_col41\" class=\"data row5 col41\" >-0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row5_col42\" class=\"data row5 col42\" >-0.03</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row5_col43\" class=\"data row5 col43\" >-0.10</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row5_col44\" class=\"data row5 col44\" >0.04</td>\n",
+              "            </tr>\n",
+              "            <tr>\n",
+              "                        <th id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002level0_row6\" class=\"row_heading level0 row6\" >ydstogo</th>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row6_col0\" class=\"data row6 col0\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row6_col1\" class=\"data row6 col1\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row6_col2\" class=\"data row6 col2\" >-0.24</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row6_col3\" class=\"data row6 col3\" >0.09</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row6_col4\" class=\"data row6 col4\" >0.06</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row6_col5\" class=\"data row6 col5\" >0.08</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row6_col6\" class=\"data row6 col6\" >1.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row6_col7\" class=\"data row6 col7\" >-0.11</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row6_col8\" class=\"data row6 col8\" >-0.09</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row6_col9\" class=\"data row6 col9\" >-0.03</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row6_col10\" class=\"data row6 col10\" >0.05</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row6_col11\" class=\"data row6 col11\" >-0.17</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row6_col12\" class=\"data row6 col12\" >-0.04</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row6_col13\" class=\"data row6 col13\" >0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row6_col14\" class=\"data row6 col14\" >-0.05</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row6_col15\" class=\"data row6 col15\" >0.27</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row6_col16\" class=\"data row6 col16\" >0.16</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row6_col17\" class=\"data row6 col17\" >0.12</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row6_col18\" class=\"data row6 col18\" >0.08</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row6_col19\" class=\"data row6 col19\" >0.04</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row6_col20\" class=\"data row6 col20\" >0.12</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row6_col21\" class=\"data row6 col21\" >0.20</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row6_col22\" class=\"data row6 col22\" >0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row6_col23\" class=\"data row6 col23\" >0.06</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row6_col24\" class=\"data row6 col24\" >0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row6_col25\" class=\"data row6 col25\" >0.26</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row6_col26\" class=\"data row6 col26\" >0.19</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row6_col27\" class=\"data row6 col27\" >0.25</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row6_col28\" class=\"data row6 col28\" >0.24</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row6_col29\" class=\"data row6 col29\" >0.31</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row6_col30\" class=\"data row6 col30\" >0.16</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row6_col31\" class=\"data row6 col31\" >-0.24</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row6_col32\" class=\"data row6 col32\" >-0.06</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row6_col33\" class=\"data row6 col33\" >0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row6_col34\" class=\"data row6 col34\" >-0.04</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row6_col35\" class=\"data row6 col35\" >-0.11</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row6_col36\" class=\"data row6 col36\" >0.06</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row6_col37\" class=\"data row6 col37\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row6_col38\" class=\"data row6 col38\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row6_col39\" class=\"data row6 col39\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row6_col40\" class=\"data row6 col40\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row6_col41\" class=\"data row6 col41\" >-0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row6_col42\" class=\"data row6 col42\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row6_col43\" class=\"data row6 col43\" >-0.07</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row6_col44\" class=\"data row6 col44\" >0.05</td>\n",
+              "            </tr>\n",
+              "            <tr>\n",
+              "                        <th id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002level0_row7\" class=\"row_heading level0 row7\" >ydsnet</th>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row7_col0\" class=\"data row7 col0\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row7_col1\" class=\"data row7 col1\" >0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row7_col2\" class=\"data row7 col2\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row7_col3\" class=\"data row7 col3\" >-0.07</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row7_col4\" class=\"data row7 col4\" >0.15</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row7_col5\" class=\"data row7 col5\" >-0.19</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row7_col6\" class=\"data row7 col6\" >-0.11</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row7_col7\" class=\"data row7 col7\" >1.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row7_col8\" class=\"data row7 col8\" >0.30</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row7_col9\" class=\"data row7 col9\" >0.03</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row7_col10\" class=\"data row7 col10\" >0.12</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row7_col11\" class=\"data row7 col11\" >0.36</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row7_col12\" class=\"data row7 col12\" >0.24</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row7_col13\" class=\"data row7 col13\" >-0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row7_col14\" class=\"data row7 col14\" >-0.03</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row7_col15\" class=\"data row7 col15\" >0.11</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row7_col16\" class=\"data row7 col16\" >0.08</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row7_col17\" class=\"data row7 col17\" >0.15</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row7_col18\" class=\"data row7 col18\" >-0.04</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row7_col19\" class=\"data row7 col19\" >-0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row7_col20\" class=\"data row7 col20\" >0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row7_col21\" class=\"data row7 col21\" >0.15</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row7_col22\" class=\"data row7 col22\" >-0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row7_col23\" class=\"data row7 col23\" >-0.08</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row7_col24\" class=\"data row7 col24\" >0.04</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row7_col25\" class=\"data row7 col25\" >-0.53</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row7_col26\" class=\"data row7 col26\" >-0.47</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row7_col27\" class=\"data row7 col27\" >-0.52</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row7_col28\" class=\"data row7 col28\" >0.33</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row7_col29\" class=\"data row7 col29\" >-0.21</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row7_col30\" class=\"data row7 col30\" >0.23</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row7_col31\" class=\"data row7 col31\" >0.25</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row7_col32\" class=\"data row7 col32\" >0.06</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row7_col33\" class=\"data row7 col33\" >0.56</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row7_col34\" class=\"data row7 col34\" >0.22</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row7_col35\" class=\"data row7 col35\" >0.14</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row7_col36\" class=\"data row7 col36\" >0.15</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row7_col37\" class=\"data row7 col37\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row7_col38\" class=\"data row7 col38\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row7_col39\" class=\"data row7 col39\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row7_col40\" class=\"data row7 col40\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row7_col41\" class=\"data row7 col41\" >0.08</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row7_col42\" class=\"data row7 col42\" >0.16</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row7_col43\" class=\"data row7 col43\" >0.11</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row7_col44\" class=\"data row7 col44\" >0.11</td>\n",
+              "            </tr>\n",
+              "            <tr>\n",
+              "                        <th id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002level0_row8\" class=\"row_heading level0 row8\" >GoalToGo</th>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row8_col0\" class=\"data row8 col0\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row8_col1\" class=\"data row8 col1\" >0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row8_col2\" class=\"data row8 col2\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row8_col3\" class=\"data row8 col3\" >-0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row8_col4\" class=\"data row8 col4\" >0.04</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row8_col5\" class=\"data row8 col5\" >-0.41</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row8_col6\" class=\"data row8 col6\" >-0.09</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row8_col7\" class=\"data row8 col7\" >0.30</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row8_col8\" class=\"data row8 col8\" >1.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row8_col9\" class=\"data row8 col9\" >-0.11</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row8_col10\" class=\"data row8 col10\" >-0.09</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row8_col11\" class=\"data row8 col11\" >0.24</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row8_col12\" class=\"data row8 col12\" >0.32</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row8_col13\" class=\"data row8 col13\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row8_col14\" class=\"data row8 col14\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row8_col15\" class=\"data row8 col15\" >0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row8_col16\" class=\"data row8 col16\" >-0.06</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row8_col17\" class=\"data row8 col17\" >-0.05</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row8_col18\" class=\"data row8 col18\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row8_col19\" class=\"data row8 col19\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row8_col20\" class=\"data row8 col20\" >0.06</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row8_col21\" class=\"data row8 col21\" >-0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row8_col22\" class=\"data row8 col22\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row8_col23\" class=\"data row8 col23\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row8_col24\" class=\"data row8 col24\" >0.04</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row8_col25\" class=\"data row8 col25\" >-0.26</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row8_col26\" class=\"data row8 col26\" >-0.16</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row8_col27\" class=\"data row8 col27\" >-0.26</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row8_col28\" class=\"data row8 col28\" >0.16</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row8_col29\" class=\"data row8 col29\" >-0.09</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row8_col30\" class=\"data row8 col30\" >0.36</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row8_col31\" class=\"data row8 col31\" >-0.04</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row8_col32\" class=\"data row8 col32\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row8_col33\" class=\"data row8 col33\" >0.43</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row8_col34\" class=\"data row8 col34\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row8_col35\" class=\"data row8 col35\" >0.08</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row8_col36\" class=\"data row8 col36\" >-0.07</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row8_col37\" class=\"data row8 col37\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row8_col38\" class=\"data row8 col38\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row8_col39\" class=\"data row8 col39\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row8_col40\" class=\"data row8 col40\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row8_col41\" class=\"data row8 col41\" >0.08</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row8_col42\" class=\"data row8 col42\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row8_col43\" class=\"data row8 col43\" >0.07</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row8_col44\" class=\"data row8 col44\" >-0.06</td>\n",
+              "            </tr>\n",
+              "            <tr>\n",
+              "                        <th id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002level0_row9\" class=\"row_heading level0 row9\" >FirstDown</th>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row9_col0\" class=\"data row9 col0\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row9_col1\" class=\"data row9 col1\" >-0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row9_col2\" class=\"data row9 col2\" >0.28</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row9_col3\" class=\"data row9 col3\" >0.09</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row9_col4\" class=\"data row9 col4\" >0.03</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row9_col5\" class=\"data row9 col5\" >0.15</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row9_col6\" class=\"data row9 col6\" >-0.03</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row9_col7\" class=\"data row9 col7\" >0.03</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row9_col8\" class=\"data row9 col8\" >-0.11</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row9_col9\" class=\"data row9 col9\" >1.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row9_col10\" class=\"data row9 col10\" >0.37</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row9_col11\" class=\"data row9 col11\" >-0.19</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row9_col12\" class=\"data row9 col12\" >-0.11</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row9_col13\" class=\"data row9 col13\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row9_col14\" class=\"data row9 col14\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row9_col15\" class=\"data row9 col15\" >0.09</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row9_col16\" class=\"data row9 col16\" >0.08</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row9_col17\" class=\"data row9 col17\" >0.20</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row9_col18\" class=\"data row9 col18\" >-0.07</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row9_col19\" class=\"data row9 col19\" >0.14</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row9_col20\" class=\"data row9 col20\" >-0.14</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row9_col21\" class=\"data row9 col21\" >0.22</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row9_col22\" class=\"data row9 col22\" >0.06</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row9_col23\" class=\"data row9 col23\" >-0.07</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row9_col24\" class=\"data row9 col24\" >0.03</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row9_col25\" class=\"data row9 col25\" >0.27</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row9_col26\" class=\"data row9 col26\" >0.10</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row9_col27\" class=\"data row9 col27\" >0.25</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row9_col28\" class=\"data row9 col28\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row9_col29\" class=\"data row9 col29\" >0.27</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row9_col30\" class=\"data row9 col30\" >0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row9_col31\" class=\"data row9 col31\" >-0.11</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row9_col32\" class=\"data row9 col32\" >-0.03</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row9_col33\" class=\"data row9 col33\" >-0.14</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row9_col34\" class=\"data row9 col34\" >0.27</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row9_col35\" class=\"data row9 col35\" >0.12</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row9_col36\" class=\"data row9 col36\" >0.20</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row9_col37\" class=\"data row9 col37\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row9_col38\" class=\"data row9 col38\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row9_col39\" class=\"data row9 col39\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row9_col40\" class=\"data row9 col40\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row9_col41\" class=\"data row9 col41\" >-0.08</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row9_col42\" class=\"data row9 col42\" >0.28</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row9_col43\" class=\"data row9 col43\" >0.09</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row9_col44\" class=\"data row9 col44\" >0.18</td>\n",
+              "            </tr>\n",
+              "            <tr>\n",
+              "                        <th id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002level0_row10\" class=\"row_heading level0 row10\" >Yards.Gained</th>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row10_col0\" class=\"data row10 col0\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row10_col1\" class=\"data row10 col1\" >-0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row10_col2\" class=\"data row10 col2\" >-0.05</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row10_col3\" class=\"data row10 col3\" >0.07</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row10_col4\" class=\"data row10 col4\" >-0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row10_col5\" class=\"data row10 col5\" >0.09</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row10_col6\" class=\"data row10 col6\" >0.05</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row10_col7\" class=\"data row10 col7\" >0.12</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row10_col8\" class=\"data row10 col8\" >-0.09</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row10_col9\" class=\"data row10 col9\" >0.37</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row10_col10\" class=\"data row10 col10\" >1.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row10_col11\" class=\"data row10 col11\" >0.04</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row10_col12\" class=\"data row10 col12\" >0.21</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row10_col13\" class=\"data row10 col13\" >-0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row10_col14\" class=\"data row10 col14\" >-0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row10_col15\" class=\"data row10 col15\" >0.19</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row10_col16\" class=\"data row10 col16\" >0.25</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row10_col17\" class=\"data row10 col17\" >0.49</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row10_col18\" class=\"data row10 col18\" >-0.13</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row10_col19\" class=\"data row10 col19\" >-0.05</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row10_col20\" class=\"data row10 col20\" >-0.05</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row10_col21\" class=\"data row10 col21\" >0.41</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row10_col22\" class=\"data row10 col22\" >-0.04</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row10_col23\" class=\"data row10 col23\" >-0.21</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row10_col24\" class=\"data row10 col24\" >0.04</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row10_col25\" class=\"data row10 col25\" >0.17</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row10_col26\" class=\"data row10 col26\" >0.12</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row10_col27\" class=\"data row10 col27\" >0.17</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row10_col28\" class=\"data row10 col28\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row10_col29\" class=\"data row10 col29\" >0.14</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row10_col30\" class=\"data row10 col30\" >0.08</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row10_col31\" class=\"data row10 col31\" >-0.09</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row10_col32\" class=\"data row10 col32\" >-0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row10_col33\" class=\"data row10 col33\" >-0.05</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row10_col34\" class=\"data row10 col34\" >0.53</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row10_col35\" class=\"data row10 col35\" >0.16</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row10_col36\" class=\"data row10 col36\" >0.48</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row10_col37\" class=\"data row10 col37\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row10_col38\" class=\"data row10 col38\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row10_col39\" class=\"data row10 col39\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row10_col40\" class=\"data row10 col40\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row10_col41\" class=\"data row10 col41\" >-0.05</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row10_col42\" class=\"data row10 col42\" >0.43</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row10_col43\" class=\"data row10 col43\" >0.11</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row10_col44\" class=\"data row10 col44\" >0.39</td>\n",
+              "            </tr>\n",
+              "            <tr>\n",
+              "                        <th id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002level0_row11\" class=\"row_heading level0 row11\" >sp</th>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row11_col0\" class=\"data row11 col0\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row11_col1\" class=\"data row11 col1\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row11_col2\" class=\"data row11 col2\" >0.17</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row11_col3\" class=\"data row11 col3\" >-0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row11_col4\" class=\"data row11 col4\" >-0.07</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row11_col5\" class=\"data row11 col5\" >-0.34</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row11_col6\" class=\"data row11 col6\" >-0.17</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row11_col7\" class=\"data row11 col7\" >0.36</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row11_col8\" class=\"data row11 col8\" >0.24</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row11_col9\" class=\"data row11 col9\" >-0.19</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row11_col10\" class=\"data row11 col10\" >0.04</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row11_col11\" class=\"data row11 col11\" >1.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row11_col12\" class=\"data row11 col12\" >0.61</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row11_col13\" class=\"data row11 col13\" >0.07</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row11_col14\" class=\"data row11 col14\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row11_col15\" class=\"data row11 col15\" >-0.09</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row11_col16\" class=\"data row11 col16\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row11_col17\" class=\"data row11 col17\" >0.03</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row11_col18\" class=\"data row11 col18\" >-0.04</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row11_col19\" class=\"data row11 col19\" >0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row11_col20\" class=\"data row11 col20\" >-0.10</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row11_col21\" class=\"data row11 col21\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row11_col22\" class=\"data row11 col22\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row11_col23\" class=\"data row11 col23\" >-0.04</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row11_col24\" class=\"data row11 col24\" >0.04</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row11_col25\" class=\"data row11 col25\" >-0.27</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row11_col26\" class=\"data row11 col26\" >-0.17</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row11_col27\" class=\"data row11 col27\" >-0.27</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row11_col28\" class=\"data row11 col28\" >0.19</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row11_col29\" class=\"data row11 col29\" >-0.28</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row11_col30\" class=\"data row11 col30\" >-0.15</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row11_col31\" class=\"data row11 col31\" >0.55</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row11_col32\" class=\"data row11 col32\" >0.06</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row11_col33\" class=\"data row11 col33\" >0.15</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row11_col34\" class=\"data row11 col34\" >0.20</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row11_col35\" class=\"data row11 col35\" >0.17</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row11_col36\" class=\"data row11 col36\" >0.13</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row11_col37\" class=\"data row11 col37\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row11_col38\" class=\"data row11 col38\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row11_col39\" class=\"data row11 col39\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row11_col40\" class=\"data row11 col40\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row11_col41\" class=\"data row11 col41\" >0.09</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row11_col42\" class=\"data row11 col42\" >0.17</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row11_col43\" class=\"data row11 col43\" >0.13</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row11_col44\" class=\"data row11 col44\" >0.11</td>\n",
+              "            </tr>\n",
+              "            <tr>\n",
+              "                        <th id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002level0_row12\" class=\"row_heading level0 row12\" >Touchdown</th>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row12_col0\" class=\"data row12 col0\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row12_col1\" class=\"data row12 col1\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row12_col2\" class=\"data row12 col2\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row12_col3\" class=\"data row12 col3\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row12_col4\" class=\"data row12 col4\" >0.04</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row12_col5\" class=\"data row12 col5\" >-0.19</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row12_col6\" class=\"data row12 col6\" >-0.04</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row12_col7\" class=\"data row12 col7\" >0.24</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row12_col8\" class=\"data row12 col8\" >0.32</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row12_col9\" class=\"data row12 col9\" >-0.11</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row12_col10\" class=\"data row12 col10\" >0.21</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row12_col11\" class=\"data row12 col11\" >0.61</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row12_col12\" class=\"data row12 col12\" >1.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row12_col13\" class=\"data row12 col13\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row12_col14\" class=\"data row12 col14\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row12_col15\" class=\"data row12 col15\" >0.08</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row12_col16\" class=\"data row12 col16\" >0.09</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row12_col17\" class=\"data row12 col17\" >0.12</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row12_col18\" class=\"data row12 col18\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row12_col19\" class=\"data row12 col19\" >0.04</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row12_col20\" class=\"data row12 col20\" >0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row12_col21\" class=\"data row12 col21\" >0.14</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row12_col22\" class=\"data row12 col22\" >0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row12_col23\" class=\"data row12 col23\" >-0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row12_col24\" class=\"data row12 col24\" >0.12</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row12_col25\" class=\"data row12 col25\" >-0.13</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row12_col26\" class=\"data row12 col26\" >-0.09</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row12_col27\" class=\"data row12 col27\" >-0.13</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row12_col28\" class=\"data row12 col28\" >0.08</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row12_col29\" class=\"data row12 col29\" >0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row12_col30\" class=\"data row12 col30\" >0.22</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row12_col31\" class=\"data row12 col31\" >-0.03</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row12_col32\" class=\"data row12 col32\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row12_col33\" class=\"data row12 col33\" >0.24</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row12_col34\" class=\"data row12 col34\" >0.25</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row12_col35\" class=\"data row12 col35\" >0.17</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row12_col36\" class=\"data row12 col36\" >0.12</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row12_col37\" class=\"data row12 col37\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row12_col38\" class=\"data row12 col38\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row12_col39\" class=\"data row12 col39\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row12_col40\" class=\"data row12 col40\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row12_col41\" class=\"data row12 col41\" >0.04</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row12_col42\" class=\"data row12 col42\" >0.22</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row12_col43\" class=\"data row12 col43\" >0.13</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row12_col44\" class=\"data row12 col44\" >0.11</td>\n",
+              "            </tr>\n",
+              "            <tr>\n",
+              "                        <th id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002level0_row13\" class=\"row_heading level0 row13\" >Safety</th>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row13_col0\" class=\"data row13 col0\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row13_col1\" class=\"data row13 col1\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row13_col2\" class=\"data row13 col2\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row13_col3\" class=\"data row13 col3\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row13_col4\" class=\"data row13 col4\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row13_col5\" class=\"data row13 col5\" >-0.03</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row13_col6\" class=\"data row13 col6\" >0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row13_col7\" class=\"data row13 col7\" >-0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row13_col8\" class=\"data row13 col8\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row13_col9\" class=\"data row13 col9\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row13_col10\" class=\"data row13 col10\" >-0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row13_col11\" class=\"data row13 col11\" >0.07</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row13_col12\" class=\"data row13 col12\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row13_col13\" class=\"data row13 col13\" >1.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row13_col14\" class=\"data row13 col14\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row13_col15\" class=\"data row13 col15\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row13_col16\" class=\"data row13 col16\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row13_col17\" class=\"data row13 col17\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row13_col18\" class=\"data row13 col18\" >0.03</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row13_col19\" class=\"data row13 col19\" >0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row13_col20\" class=\"data row13 col20\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row13_col21\" class=\"data row13 col21\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row13_col22\" class=\"data row13 col22\" >0.04</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row13_col23\" class=\"data row13 col23\" >0.05</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row13_col24\" class=\"data row13 col24\" >0.03</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row13_col25\" class=\"data row13 col25\" >0.03</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row13_col26\" class=\"data row13 col26\" >0.07</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row13_col27\" class=\"data row13 col27\" >0.03</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row13_col28\" class=\"data row13 col28\" >-0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row13_col29\" class=\"data row13 col29\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row13_col30\" class=\"data row13 col30\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row13_col31\" class=\"data row13 col31\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row13_col32\" class=\"data row13 col32\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row13_col33\" class=\"data row13 col33\" >-0.03</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row13_col34\" class=\"data row13 col34\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row13_col35\" class=\"data row13 col35\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row13_col36\" class=\"data row13 col36\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row13_col37\" class=\"data row13 col37\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row13_col38\" class=\"data row13 col38\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row13_col39\" class=\"data row13 col39\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row13_col40\" class=\"data row13 col40\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row13_col41\" class=\"data row13 col41\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row13_col42\" class=\"data row13 col42\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row13_col43\" class=\"data row13 col43\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row13_col44\" class=\"data row13 col44\" >-0.01</td>\n",
+              "            </tr>\n",
+              "            <tr>\n",
+              "                        <th id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002level0_row14\" class=\"row_heading level0 row14\" >Onsidekick</th>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row14_col0\" class=\"data row14 col0\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row14_col1\" class=\"data row14 col1\" >0.04</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row14_col2\" class=\"data row14 col2\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row14_col3\" class=\"data row14 col3\" >-0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row14_col4\" class=\"data row14 col4\" >-0.04</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row14_col5\" class=\"data row14 col5\" >0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row14_col6\" class=\"data row14 col6\" >-0.05</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row14_col7\" class=\"data row14 col7\" >-0.03</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row14_col8\" class=\"data row14 col8\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row14_col9\" class=\"data row14 col9\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row14_col10\" class=\"data row14 col10\" >-0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row14_col11\" class=\"data row14 col11\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row14_col12\" class=\"data row14 col12\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row14_col13\" class=\"data row14 col13\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row14_col14\" class=\"data row14 col14\" >1.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row14_col15\" class=\"data row14 col15\" >-0.03</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row14_col16\" class=\"data row14 col16\" >-0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row14_col17\" class=\"data row14 col17\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row14_col18\" class=\"data row14 col18\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row14_col19\" class=\"data row14 col19\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row14_col20\" class=\"data row14 col20\" >-0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row14_col21\" class=\"data row14 col21\" >-0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row14_col22\" class=\"data row14 col22\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row14_col23\" class=\"data row14 col23\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row14_col24\" class=\"data row14 col24\" >0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row14_col25\" class=\"data row14 col25\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row14_col26\" class=\"data row14 col26\" >0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row14_col27\" class=\"data row14 col27\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row14_col28\" class=\"data row14 col28\" >-0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row14_col29\" class=\"data row14 col29\" >-0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row14_col30\" class=\"data row14 col30\" >-0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row14_col31\" class=\"data row14 col31\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row14_col32\" class=\"data row14 col32\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row14_col33\" class=\"data row14 col33\" >-0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row14_col34\" class=\"data row14 col34\" >0.03</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row14_col35\" class=\"data row14 col35\" >0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row14_col36\" class=\"data row14 col36\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row14_col37\" class=\"data row14 col37\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row14_col38\" class=\"data row14 col38\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row14_col39\" class=\"data row14 col39\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row14_col40\" class=\"data row14 col40\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row14_col41\" class=\"data row14 col41\" >0.05</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row14_col42\" class=\"data row14 col42\" >-0.04</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row14_col43\" class=\"data row14 col43\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row14_col44\" class=\"data row14 col44\" >-0.00</td>\n",
+              "            </tr>\n",
+              "            <tr>\n",
+              "                        <th id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002level0_row15\" class=\"row_heading level0 row15\" >PassAttempt</th>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row15_col0\" class=\"data row15 col0\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row15_col1\" class=\"data row15 col1\" >0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row15_col2\" class=\"data row15 col2\" >-0.06</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row15_col3\" class=\"data row15 col3\" >0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row15_col4\" class=\"data row15 col4\" >0.10</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row15_col5\" class=\"data row15 col5\" >0.05</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row15_col6\" class=\"data row15 col6\" >0.27</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row15_col7\" class=\"data row15 col7\" >0.11</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row15_col8\" class=\"data row15 col8\" >0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row15_col9\" class=\"data row15 col9\" >0.09</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row15_col10\" class=\"data row15 col10\" >0.19</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row15_col11\" class=\"data row15 col11\" >-0.09</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row15_col12\" class=\"data row15 col12\" >0.08</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row15_col13\" class=\"data row15 col13\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row15_col14\" class=\"data row15 col14\" >-0.03</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row15_col15\" class=\"data row15 col15\" >1.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row15_col16\" class=\"data row15 col16\" >0.52</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row15_col17\" class=\"data row15 col17\" >0.36</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row15_col18\" class=\"data row15 col18\" >0.07</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row15_col19\" class=\"data row15 col19\" >0.13</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row15_col20\" class=\"data row15 col20\" >-0.54</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row15_col21\" class=\"data row15 col21\" >0.69</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row15_col22\" class=\"data row15 col22\" >-0.04</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row15_col23\" class=\"data row15 col23\" >-0.14</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row15_col24\" class=\"data row15 col24\" >0.06</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row15_col25\" class=\"data row15 col25\" >0.04</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row15_col26\" class=\"data row15 col26\" >0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row15_col27\" class=\"data row15 col27\" >0.04</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row15_col28\" class=\"data row15 col28\" >0.13</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row15_col29\" class=\"data row15 col29\" >0.14</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row15_col30\" class=\"data row15 col30\" >0.18</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row15_col31\" class=\"data row15 col31\" >-0.13</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row15_col32\" class=\"data row15 col32\" >0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row15_col33\" class=\"data row15 col33\" >0.12</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row15_col34\" class=\"data row15 col34\" >0.08</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row15_col35\" class=\"data row15 col35\" >-</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row15_col36\" class=\"data row15 col36\" >-</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row15_col37\" class=\"data row15 col37\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row15_col38\" class=\"data row15 col38\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row15_col39\" class=\"data row15 col39\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row15_col40\" class=\"data row15 col40\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row15_col41\" class=\"data row15 col41\" >-0.13</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row15_col42\" class=\"data row15 col42\" >0.06</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row15_col43\" class=\"data row15 col43\" >-</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row15_col44\" class=\"data row15 col44\" >-</td>\n",
+              "            </tr>\n",
+              "            <tr>\n",
+              "                        <th id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002level0_row16\" class=\"row_heading level0 row16\" >AirYards</th>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row16_col0\" class=\"data row16 col0\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row16_col1\" class=\"data row16 col1\" >0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row16_col2\" class=\"data row16 col2\" >-0.03</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row16_col3\" class=\"data row16 col3\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row16_col4\" class=\"data row16 col4\" >0.05</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row16_col5\" class=\"data row16 col5\" >0.08</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row16_col6\" class=\"data row16 col6\" >0.16</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row16_col7\" class=\"data row16 col7\" >0.08</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row16_col8\" class=\"data row16 col8\" >-0.06</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row16_col9\" class=\"data row16 col9\" >0.08</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row16_col10\" class=\"data row16 col10\" >0.25</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row16_col11\" class=\"data row16 col11\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row16_col12\" class=\"data row16 col12\" >0.09</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row16_col13\" class=\"data row16 col13\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row16_col14\" class=\"data row16 col14\" >-0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row16_col15\" class=\"data row16 col15\" >0.52</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row16_col16\" class=\"data row16 col16\" >1.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row16_col17\" class=\"data row16 col17\" >0.06</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row16_col18\" class=\"data row16 col18\" >0.07</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row16_col19\" class=\"data row16 col19\" >0.17</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row16_col20\" class=\"data row16 col20\" >-0.28</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row16_col21\" class=\"data row16 col21\" >0.22</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row16_col22\" class=\"data row16 col22\" >-0.03</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row16_col23\" class=\"data row16 col23\" >-0.07</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row16_col24\" class=\"data row16 col24\" >0.06</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row16_col25\" class=\"data row16 col25\" >0.04</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row16_col26\" class=\"data row16 col26\" >0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row16_col27\" class=\"data row16 col27\" >0.04</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row16_col28\" class=\"data row16 col28\" >0.06</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row16_col29\" class=\"data row16 col29\" >0.08</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row16_col30\" class=\"data row16 col30\" >0.06</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row16_col31\" class=\"data row16 col31\" >-0.07</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row16_col32\" class=\"data row16 col32\" >-0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row16_col33\" class=\"data row16 col33\" >0.03</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row16_col34\" class=\"data row16 col34\" >0.10</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row16_col35\" class=\"data row16 col35\" >0.77</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row16_col36\" class=\"data row16 col36\" >-0.47</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row16_col37\" class=\"data row16 col37\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row16_col38\" class=\"data row16 col38\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row16_col39\" class=\"data row16 col39\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row16_col40\" class=\"data row16 col40\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row16_col41\" class=\"data row16 col41\" >-0.09</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row16_col42\" class=\"data row16 col42\" >0.08</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row16_col43\" class=\"data row16 col43\" >0.53</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row16_col44\" class=\"data row16 col44\" >-0.37</td>\n",
+              "            </tr>\n",
+              "            <tr>\n",
+              "                        <th id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002level0_row17\" class=\"row_heading level0 row17\" >YardsAfterCatch</th>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row17_col0\" class=\"data row17 col0\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row17_col1\" class=\"data row17 col1\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row17_col2\" class=\"data row17 col2\" >-0.04</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row17_col3\" class=\"data row17 col3\" >0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row17_col4\" class=\"data row17 col4\" >0.04</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row17_col5\" class=\"data row17 col5\" >0.05</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row17_col6\" class=\"data row17 col6\" >0.12</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row17_col7\" class=\"data row17 col7\" >0.15</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row17_col8\" class=\"data row17 col8\" >-0.05</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row17_col9\" class=\"data row17 col9\" >0.20</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row17_col10\" class=\"data row17 col10\" >0.49</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row17_col11\" class=\"data row17 col11\" >0.03</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row17_col12\" class=\"data row17 col12\" >0.12</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row17_col13\" class=\"data row17 col13\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row17_col14\" class=\"data row17 col14\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row17_col15\" class=\"data row17 col15\" >0.36</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row17_col16\" class=\"data row17 col16\" >0.06</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row17_col17\" class=\"data row17 col17\" >1.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row17_col18\" class=\"data row17 col18\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row17_col19\" class=\"data row17 col19\" >-0.03</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row17_col20\" class=\"data row17 col20\" >-0.19</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row17_col21\" class=\"data row17 col21\" >0.52</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row17_col22\" class=\"data row17 col22\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row17_col23\" class=\"data row17 col23\" >-0.05</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row17_col24\" class=\"data row17 col24\" >0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row17_col25\" class=\"data row17 col25\" >0.06</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row17_col26\" class=\"data row17 col26\" >0.03</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row17_col27\" class=\"data row17 col27\" >0.06</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row17_col28\" class=\"data row17 col28\" >0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row17_col29\" class=\"data row17 col29\" >0.07</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row17_col30\" class=\"data row17 col30\" >0.05</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row17_col31\" class=\"data row17 col31\" >-0.05</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row17_col32\" class=\"data row17 col32\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row17_col33\" class=\"data row17 col33\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row17_col34\" class=\"data row17 col34\" >0.35</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row17_col35\" class=\"data row17 col35\" >-0.22</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row17_col36\" class=\"data row17 col36\" >0.54</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row17_col37\" class=\"data row17 col37\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row17_col38\" class=\"data row17 col38\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row17_col39\" class=\"data row17 col39\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row17_col40\" class=\"data row17 col40\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row17_col41\" class=\"data row17 col41\" >-0.03</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row17_col42\" class=\"data row17 col42\" >0.28</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row17_col43\" class=\"data row17 col43\" >-0.16</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row17_col44\" class=\"data row17 col44\" >0.43</td>\n",
+              "            </tr>\n",
+              "            <tr>\n",
+              "                        <th id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002level0_row18\" class=\"row_heading level0 row18\" >QBHit</th>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row18_col0\" class=\"data row18 col0\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row18_col1\" class=\"data row18 col1\" >0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row18_col2\" class=\"data row18 col2\" >0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row18_col3\" class=\"data row18 col3\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row18_col4\" class=\"data row18 col4\" >0.03</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row18_col5\" class=\"data row18 col5\" >0.03</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row18_col6\" class=\"data row18 col6\" >0.08</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row18_col7\" class=\"data row18 col7\" >-0.04</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row18_col8\" class=\"data row18 col8\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row18_col9\" class=\"data row18 col9\" >-0.07</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row18_col10\" class=\"data row18 col10\" >-0.13</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row18_col11\" class=\"data row18 col11\" >-0.04</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row18_col12\" class=\"data row18 col12\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row18_col13\" class=\"data row18 col13\" >0.03</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row18_col14\" class=\"data row18 col14\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row18_col15\" class=\"data row18 col15\" >0.07</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row18_col16\" class=\"data row18 col16\" >0.07</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row18_col17\" class=\"data row18 col17\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row18_col18\" class=\"data row18 col18\" >1.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row18_col19\" class=\"data row18 col19\" >0.03</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row18_col20\" class=\"data row18 col20\" >-0.15</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row18_col21\" class=\"data row18 col21\" >-0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row18_col22\" class=\"data row18 col22\" >0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row18_col23\" class=\"data row18 col23\" >0.59</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row18_col24\" class=\"data row18 col24\" >0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row18_col25\" class=\"data row18 col25\" >0.03</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row18_col26\" class=\"data row18 col26\" >0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row18_col27\" class=\"data row18 col27\" >0.03</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row18_col28\" class=\"data row18 col28\" >0.04</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row18_col29\" class=\"data row18 col29\" >0.05</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row18_col30\" class=\"data row18 col30\" >0.03</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row18_col31\" class=\"data row18 col31\" >-0.04</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row18_col32\" class=\"data row18 col32\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row18_col33\" class=\"data row18 col33\" >0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row18_col34\" class=\"data row18 col34\" >-0.16</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row18_col35\" class=\"data row18 col35\" >0.03</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row18_col36\" class=\"data row18 col36\" >-0.09</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row18_col37\" class=\"data row18 col37\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row18_col38\" class=\"data row18 col38\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row18_col39\" class=\"data row18 col39\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row18_col40\" class=\"data row18 col40\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row18_col41\" class=\"data row18 col41\" >-0.06</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row18_col42\" class=\"data row18 col42\" >-0.13</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row18_col43\" class=\"data row18 col43\" >0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row18_col44\" class=\"data row18 col44\" >-0.07</td>\n",
+              "            </tr>\n",
+              "            <tr>\n",
+              "                        <th id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002level0_row19\" class=\"row_heading level0 row19\" >InterceptionThrown</th>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row19_col0\" class=\"data row19 col0\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row19_col1\" class=\"data row19 col1\" >0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row19_col2\" class=\"data row19 col2\" >0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row19_col3\" class=\"data row19 col3\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row19_col4\" class=\"data row19 col4\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row19_col5\" class=\"data row19 col5\" >0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row19_col6\" class=\"data row19 col6\" >0.04</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row19_col7\" class=\"data row19 col7\" >-0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row19_col8\" class=\"data row19 col8\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row19_col9\" class=\"data row19 col9\" >0.14</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row19_col10\" class=\"data row19 col10\" >-0.05</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row19_col11\" class=\"data row19 col11\" >0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row19_col12\" class=\"data row19 col12\" >0.04</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row19_col13\" class=\"data row19 col13\" >0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row19_col14\" class=\"data row19 col14\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row19_col15\" class=\"data row19 col15\" >0.13</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row19_col16\" class=\"data row19 col16\" >0.17</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row19_col17\" class=\"data row19 col17\" >-0.03</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row19_col18\" class=\"data row19 col18\" >0.03</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row19_col19\" class=\"data row19 col19\" >1.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row19_col20\" class=\"data row19 col20\" >-0.07</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row19_col21\" class=\"data row19 col21\" >-0.06</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row19_col22\" class=\"data row19 col22\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row19_col23\" class=\"data row19 col23\" >-0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row19_col24\" class=\"data row19 col24\" >0.07</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row19_col25\" class=\"data row19 col25\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row19_col26\" class=\"data row19 col26\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row19_col27\" class=\"data row19 col27\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row19_col28\" class=\"data row19 col28\" >0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row19_col29\" class=\"data row19 col29\" >0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row19_col30\" class=\"data row19 col30\" >0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row19_col31\" class=\"data row19 col31\" >-0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row19_col32\" class=\"data row19 col32\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row19_col33\" class=\"data row19 col33\" >0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row19_col34\" class=\"data row19 col34\" >-0.33</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row19_col35\" class=\"data row19 col35\" >0.10</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row19_col36\" class=\"data row19 col36\" >-0.45</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row19_col37\" class=\"data row19 col37\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row19_col38\" class=\"data row19 col38\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row19_col39\" class=\"data row19 col39\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row19_col40\" class=\"data row19 col40\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row19_col41\" class=\"data row19 col41\" >-0.04</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row19_col42\" class=\"data row19 col42\" >-0.22</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row19_col43\" class=\"data row19 col43\" >0.07</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row19_col44\" class=\"data row19 col44\" >-0.30</td>\n",
+              "            </tr>\n",
+              "            <tr>\n",
+              "                        <th id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002level0_row20\" class=\"row_heading level0 row20\" >RushAttempt</th>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row20_col0\" class=\"data row20 col0\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row20_col1\" class=\"data row20 col1\" >-0.04</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row20_col2\" class=\"data row20 col2\" >-0.30</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row20_col3\" class=\"data row20 col3\" >0.11</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row20_col4\" class=\"data row20 col4\" >0.11</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row20_col5\" class=\"data row20 col5\" >-0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row20_col6\" class=\"data row20 col6\" >0.12</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row20_col7\" class=\"data row20 col7\" >0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row20_col8\" class=\"data row20 col8\" >0.06</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row20_col9\" class=\"data row20 col9\" >-0.14</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row20_col10\" class=\"data row20 col10\" >-0.05</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row20_col11\" class=\"data row20 col11\" >-0.10</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row20_col12\" class=\"data row20 col12\" >0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row20_col13\" class=\"data row20 col13\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row20_col14\" class=\"data row20 col14\" >-0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row20_col15\" class=\"data row20 col15\" >-0.54</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row20_col16\" class=\"data row20 col16\" >-0.28</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row20_col17\" class=\"data row20 col17\" >-0.19</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row20_col18\" class=\"data row20 col18\" >-0.15</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row20_col19\" class=\"data row20 col19\" >-0.07</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row20_col20\" class=\"data row20 col20\" >1.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row20_col21\" class=\"data row20 col21\" >-0.37</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row20_col22\" class=\"data row20 col22\" >0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row20_col23\" class=\"data row20 col23\" >-0.11</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row20_col24\" class=\"data row20 col24\" >-0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row20_col25\" class=\"data row20 col25\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row20_col26\" class=\"data row20 col26\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row20_col27\" class=\"data row20 col27\" >0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row20_col28\" class=\"data row20 col28\" >0.09</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row20_col29\" class=\"data row20 col29\" >0.13</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row20_col30\" class=\"data row20 col30\" >0.35</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row20_col31\" class=\"data row20 col31\" >-0.10</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row20_col32\" class=\"data row20 col32\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row20_col33\" class=\"data row20 col33\" >0.25</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row20_col34\" class=\"data row20 col34\" >-0.04</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row20_col35\" class=\"data row20 col35\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row20_col36\" class=\"data row20 col36\" >0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row20_col37\" class=\"data row20 col37\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row20_col38\" class=\"data row20 col38\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row20_col39\" class=\"data row20 col39\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row20_col40\" class=\"data row20 col40\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row20_col41\" class=\"data row20 col41\" >0.16</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row20_col42\" class=\"data row20 col42\" >-0.04</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row20_col43\" class=\"data row20 col43\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row20_col44\" class=\"data row20 col44\" >0.00</td>\n",
+              "            </tr>\n",
+              "            <tr>\n",
+              "                        <th id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002level0_row21\" class=\"row_heading level0 row21\" >Reception</th>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row21_col0\" class=\"data row21 col0\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row21_col1\" class=\"data row21 col1\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row21_col2\" class=\"data row21 col2\" >-0.06</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row21_col3\" class=\"data row21 col3\" >0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row21_col4\" class=\"data row21 col4\" >0.07</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row21_col5\" class=\"data row21 col5\" >0.05</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row21_col6\" class=\"data row21 col6\" >0.20</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row21_col7\" class=\"data row21 col7\" >0.15</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row21_col8\" class=\"data row21 col8\" >-0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row21_col9\" class=\"data row21 col9\" >0.22</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row21_col10\" class=\"data row21 col10\" >0.41</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row21_col11\" class=\"data row21 col11\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row21_col12\" class=\"data row21 col12\" >0.14</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row21_col13\" class=\"data row21 col13\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row21_col14\" class=\"data row21 col14\" >-0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row21_col15\" class=\"data row21 col15\" >0.69</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row21_col16\" class=\"data row21 col16\" >0.22</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row21_col17\" class=\"data row21 col17\" >0.52</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row21_col18\" class=\"data row21 col18\" >-0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row21_col19\" class=\"data row21 col19\" >-0.06</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row21_col20\" class=\"data row21 col20\" >-0.37</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row21_col21\" class=\"data row21 col21\" >1.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row21_col22\" class=\"data row21 col22\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row21_col23\" class=\"data row21 col23\" >-0.10</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row21_col24\" class=\"data row21 col24\" >0.03</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row21_col25\" class=\"data row21 col25\" >0.05</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row21_col26\" class=\"data row21 col26\" >0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row21_col27\" class=\"data row21 col27\" >0.05</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row21_col28\" class=\"data row21 col28\" >0.07</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row21_col29\" class=\"data row21 col29\" >0.10</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row21_col30\" class=\"data row21 col30\" >0.12</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row21_col31\" class=\"data row21 col31\" >-0.09</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row21_col32\" class=\"data row21 col32\" >0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row21_col33\" class=\"data row21 col33\" >0.06</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row21_col34\" class=\"data row21 col34\" >0.36</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row21_col35\" class=\"data row21 col35\" >-0.25</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row21_col36\" class=\"data row21 col36\" >0.67</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row21_col37\" class=\"data row21 col37\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row21_col38\" class=\"data row21 col38\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row21_col39\" class=\"data row21 col39\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row21_col40\" class=\"data row21 col40\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row21_col41\" class=\"data row21 col41\" >-0.08</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row21_col42\" class=\"data row21 col42\" >0.28</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row21_col43\" class=\"data row21 col43\" >-0.18</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row21_col44\" class=\"data row21 col44\" >0.54</td>\n",
+              "            </tr>\n",
+              "            <tr>\n",
+              "                        <th id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002level0_row22\" class=\"row_heading level0 row22\" >Fumble</th>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row22_col0\" class=\"data row22 col0\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row22_col1\" class=\"data row22 col1\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row22_col2\" class=\"data row22 col2\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row22_col3\" class=\"data row22 col3\" >0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row22_col4\" class=\"data row22 col4\" >0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row22_col5\" class=\"data row22 col5\" >0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row22_col6\" class=\"data row22 col6\" >0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row22_col7\" class=\"data row22 col7\" >-0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row22_col8\" class=\"data row22 col8\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row22_col9\" class=\"data row22 col9\" >0.06</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row22_col10\" class=\"data row22 col10\" >-0.04</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row22_col11\" class=\"data row22 col11\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row22_col12\" class=\"data row22 col12\" >0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row22_col13\" class=\"data row22 col13\" >0.04</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row22_col14\" class=\"data row22 col14\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row22_col15\" class=\"data row22 col15\" >-0.04</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row22_col16\" class=\"data row22 col16\" >-0.03</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row22_col17\" class=\"data row22 col17\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row22_col18\" class=\"data row22 col18\" >0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row22_col19\" class=\"data row22 col19\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row22_col20\" class=\"data row22 col20\" >0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row22_col21\" class=\"data row22 col21\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row22_col22\" class=\"data row22 col22\" >1.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row22_col23\" class=\"data row22 col23\" >0.19</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row22_col24\" class=\"data row22 col24\" >0.14</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row22_col25\" class=\"data row22 col25\" >0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row22_col26\" class=\"data row22 col26\" >0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row22_col27\" class=\"data row22 col27\" >0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row22_col28\" class=\"data row22 col28\" >0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row22_col29\" class=\"data row22 col29\" >0.03</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row22_col30\" class=\"data row22 col30\" >0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row22_col31\" class=\"data row22 col31\" >-0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row22_col32\" class=\"data row22 col32\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row22_col33\" class=\"data row22 col33\" >0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row22_col34\" class=\"data row22 col34\" >-0.21</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row22_col35\" class=\"data row22 col35\" >-0.05</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row22_col36\" class=\"data row22 col36\" >-0.06</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row22_col37\" class=\"data row22 col37\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row22_col38\" class=\"data row22 col38\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row22_col39\" class=\"data row22 col39\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row22_col40\" class=\"data row22 col40\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row22_col41\" class=\"data row22 col41\" >-0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row22_col42\" class=\"data row22 col42\" >-0.14</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row22_col43\" class=\"data row22 col43\" >-0.04</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row22_col44\" class=\"data row22 col44\" >-0.04</td>\n",
+              "            </tr>\n",
+              "            <tr>\n",
+              "                        <th id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002level0_row23\" class=\"row_heading level0 row23\" >Sack</th>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row23_col0\" class=\"data row23 col0\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row23_col1\" class=\"data row23 col1\" >0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row23_col2\" class=\"data row23 col2\" >0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row23_col3\" class=\"data row23 col3\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row23_col4\" class=\"data row23 col4\" >0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row23_col5\" class=\"data row23 col5\" >0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row23_col6\" class=\"data row23 col6\" >0.06</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row23_col7\" class=\"data row23 col7\" >-0.08</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row23_col8\" class=\"data row23 col8\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row23_col9\" class=\"data row23 col9\" >-0.07</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row23_col10\" class=\"data row23 col10\" >-0.21</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row23_col11\" class=\"data row23 col11\" >-0.04</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row23_col12\" class=\"data row23 col12\" >-0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row23_col13\" class=\"data row23 col13\" >0.05</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row23_col14\" class=\"data row23 col14\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row23_col15\" class=\"data row23 col15\" >-0.14</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row23_col16\" class=\"data row23 col16\" >-0.07</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row23_col17\" class=\"data row23 col17\" >-0.05</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row23_col18\" class=\"data row23 col18\" >0.59</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row23_col19\" class=\"data row23 col19\" >-0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row23_col20\" class=\"data row23 col20\" >-0.11</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row23_col21\" class=\"data row23 col21\" >-0.10</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row23_col22\" class=\"data row23 col22\" >0.19</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row23_col23\" class=\"data row23 col23\" >1.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row23_col24\" class=\"data row23 col24\" >0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row23_col25\" class=\"data row23 col25\" >0.03</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row23_col26\" class=\"data row23 col26\" >0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row23_col27\" class=\"data row23 col27\" >0.03</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row23_col28\" class=\"data row23 col28\" >0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row23_col29\" class=\"data row23 col29\" >0.04</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row23_col30\" class=\"data row23 col30\" >0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row23_col31\" class=\"data row23 col31\" >-0.03</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row23_col32\" class=\"data row23 col32\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row23_col33\" class=\"data row23 col33\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row23_col34\" class=\"data row23 col34\" >-0.21</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row23_col35\" class=\"data row23 col35\" >-0.03</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row23_col36\" class=\"data row23 col36\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row23_col37\" class=\"data row23 col37\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row23_col38\" class=\"data row23 col38\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row23_col39\" class=\"data row23 col39\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row23_col40\" class=\"data row23 col40\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row23_col41\" class=\"data row23 col41\" >-0.04</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row23_col42\" class=\"data row23 col42\" >-0.16</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row23_col43\" class=\"data row23 col43\" >-0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row23_col44\" class=\"data row23 col44\" >0.00</td>\n",
+              "            </tr>\n",
+              "            <tr>\n",
+              "                        <th id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002level0_row24\" class=\"row_heading level0 row24\" >Challenge.Replay</th>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row24_col0\" class=\"data row24 col0\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row24_col1\" class=\"data row24 col1\" >0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row24_col2\" class=\"data row24 col2\" >0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row24_col3\" class=\"data row24 col3\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row24_col4\" class=\"data row24 col4\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row24_col5\" class=\"data row24 col5\" >-0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row24_col6\" class=\"data row24 col6\" >0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row24_col7\" class=\"data row24 col7\" >0.04</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row24_col8\" class=\"data row24 col8\" >0.04</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row24_col9\" class=\"data row24 col9\" >0.03</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row24_col10\" class=\"data row24 col10\" >0.04</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row24_col11\" class=\"data row24 col11\" >0.04</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row24_col12\" class=\"data row24 col12\" >0.12</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row24_col13\" class=\"data row24 col13\" >0.03</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row24_col14\" class=\"data row24 col14\" >0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row24_col15\" class=\"data row24 col15\" >0.06</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row24_col16\" class=\"data row24 col16\" >0.06</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row24_col17\" class=\"data row24 col17\" >0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row24_col18\" class=\"data row24 col18\" >0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row24_col19\" class=\"data row24 col19\" >0.07</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row24_col20\" class=\"data row24 col20\" >-0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row24_col21\" class=\"data row24 col21\" >0.03</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row24_col22\" class=\"data row24 col22\" >0.14</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row24_col23\" class=\"data row24 col23\" >0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row24_col24\" class=\"data row24 col24\" >1.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row24_col25\" class=\"data row24 col25\" >-0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row24_col26\" class=\"data row24 col26\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row24_col27\" class=\"data row24 col27\" >-0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row24_col28\" class=\"data row24 col28\" >0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row24_col29\" class=\"data row24 col29\" >0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row24_col30\" class=\"data row24 col30\" >0.03</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row24_col31\" class=\"data row24 col31\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row24_col32\" class=\"data row24 col32\" >0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row24_col33\" class=\"data row24 col33\" >0.03</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row24_col34\" class=\"data row24 col34\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row24_col35\" class=\"data row24 col35\" >0.03</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row24_col36\" class=\"data row24 col36\" >-0.03</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row24_col37\" class=\"data row24 col37\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row24_col38\" class=\"data row24 col38\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row24_col39\" class=\"data row24 col39\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row24_col40\" class=\"data row24 col40\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row24_col41\" class=\"data row24 col41\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row24_col42\" class=\"data row24 col42\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row24_col43\" class=\"data row24 col43\" >0.04</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row24_col44\" class=\"data row24 col44\" >-0.02</td>\n",
+              "            </tr>\n",
+              "            <tr>\n",
+              "                        <th id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002level0_row25\" class=\"row_heading level0 row25\" >Opp_Field_Goal_Prob</th>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row25_col0\" class=\"data row25 col0\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row25_col1\" class=\"data row25 col1\" >-0.16</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row25_col2\" class=\"data row25 col2\" >0.25</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row25_col3\" class=\"data row25 col3\" >0.38</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row25_col4\" class=\"data row25 col4\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row25_col5\" class=\"data row25 col5\" >0.05</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row25_col6\" class=\"data row25 col6\" >0.26</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row25_col7\" class=\"data row25 col7\" >-0.53</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row25_col8\" class=\"data row25 col8\" >-0.26</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row25_col9\" class=\"data row25 col9\" >0.27</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row25_col10\" class=\"data row25 col10\" >0.17</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row25_col11\" class=\"data row25 col11\" >-0.27</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row25_col12\" class=\"data row25 col12\" >-0.13</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row25_col13\" class=\"data row25 col13\" >0.03</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row25_col14\" class=\"data row25 col14\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row25_col15\" class=\"data row25 col15\" >0.04</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row25_col16\" class=\"data row25 col16\" >0.04</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row25_col17\" class=\"data row25 col17\" >0.06</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row25_col18\" class=\"data row25 col18\" >0.03</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row25_col19\" class=\"data row25 col19\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row25_col20\" class=\"data row25 col20\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row25_col21\" class=\"data row25 col21\" >0.05</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row25_col22\" class=\"data row25 col22\" >0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row25_col23\" class=\"data row25 col23\" >0.03</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row25_col24\" class=\"data row25 col24\" >-0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row25_col25\" class=\"data row25 col25\" >1.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row25_col26\" class=\"data row25 col26\" >0.80</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row25_col27\" class=\"data row25 col27\" >1.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row25_col28\" class=\"data row25 col28\" >-0.18</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row25_col29\" class=\"data row25 col29\" >0.70</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row25_col30\" class=\"data row25 col30\" >0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row25_col31\" class=\"data row25 col31\" >-0.21</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row25_col32\" class=\"data row25 col32\" >-0.05</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row25_col33\" class=\"data row25 col33\" >-0.63</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row25_col34\" class=\"data row25 col34\" >0.03</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row25_col35\" class=\"data row25 col35\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row25_col36\" class=\"data row25 col36\" >0.03</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row25_col37\" class=\"data row25 col37\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row25_col38\" class=\"data row25 col38\" >0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row25_col39\" class=\"data row25 col39\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row25_col40\" class=\"data row25 col40\" >0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row25_col41\" class=\"data row25 col41\" >-0.17</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row25_col42\" class=\"data row25 col42\" >0.07</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row25_col43\" class=\"data row25 col43\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row25_col44\" class=\"data row25 col44\" >0.04</td>\n",
+              "            </tr>\n",
+              "            <tr>\n",
+              "                        <th id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002level0_row26\" class=\"row_heading level0 row26\" >Opp_Safety_Prob</th>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row26_col0\" class=\"data row26 col0\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row26_col1\" class=\"data row26 col1\" >-0.10</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row26_col2\" class=\"data row26 col2\" >0.07</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row26_col3\" class=\"data row26 col3\" >0.21</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row26_col4\" class=\"data row26 col4\" >-0.11</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row26_col5\" class=\"data row26 col5\" >-0.30</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row26_col6\" class=\"data row26 col6\" >0.19</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row26_col7\" class=\"data row26 col7\" >-0.47</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row26_col8\" class=\"data row26 col8\" >-0.16</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row26_col9\" class=\"data row26 col9\" >0.10</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row26_col10\" class=\"data row26 col10\" >0.12</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row26_col11\" class=\"data row26 col11\" >-0.17</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row26_col12\" class=\"data row26 col12\" >-0.09</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row26_col13\" class=\"data row26 col13\" >0.07</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row26_col14\" class=\"data row26 col14\" >0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row26_col15\" class=\"data row26 col15\" >0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row26_col16\" class=\"data row26 col16\" >0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row26_col17\" class=\"data row26 col17\" >0.03</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row26_col18\" class=\"data row26 col18\" >0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row26_col19\" class=\"data row26 col19\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row26_col20\" class=\"data row26 col20\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row26_col21\" class=\"data row26 col21\" >0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row26_col22\" class=\"data row26 col22\" >0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row26_col23\" class=\"data row26 col23\" >0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row26_col24\" class=\"data row26 col24\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row26_col25\" class=\"data row26 col25\" >0.80</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row26_col26\" class=\"data row26 col26\" >1.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row26_col27\" class=\"data row26 col27\" >0.79</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row26_col28\" class=\"data row26 col28\" >-0.30</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row26_col29\" class=\"data row26 col29\" >0.33</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row26_col30\" class=\"data row26 col30\" >-0.17</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row26_col31\" class=\"data row26 col31\" >-0.12</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row26_col32\" class=\"data row26 col32\" >-0.03</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row26_col33\" class=\"data row26 col33\" >-0.65</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row26_col34\" class=\"data row26 col34\" >0.03</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row26_col35\" class=\"data row26 col35\" >0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row26_col36\" class=\"data row26 col36\" >0.03</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row26_col37\" class=\"data row26 col37\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row26_col38\" class=\"data row26 col38\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row26_col39\" class=\"data row26 col39\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row26_col40\" class=\"data row26 col40\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row26_col41\" class=\"data row26 col41\" >-0.15</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row26_col42\" class=\"data row26 col42\" >0.05</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row26_col43\" class=\"data row26 col43\" >0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row26_col44\" class=\"data row26 col44\" >0.02</td>\n",
+              "            </tr>\n",
+              "            <tr>\n",
+              "                        <th id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002level0_row27\" class=\"row_heading level0 row27\" >Opp_Touchdown_Prob</th>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row27_col0\" class=\"data row27 col0\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row27_col1\" class=\"data row27 col1\" >-0.17</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row27_col2\" class=\"data row27 col2\" >0.22</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row27_col3\" class=\"data row27 col3\" >0.41</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row27_col4\" class=\"data row27 col4\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row27_col5\" class=\"data row27 col5\" >0.05</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row27_col6\" class=\"data row27 col6\" >0.25</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row27_col7\" class=\"data row27 col7\" >-0.52</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row27_col8\" class=\"data row27 col8\" >-0.26</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row27_col9\" class=\"data row27 col9\" >0.25</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row27_col10\" class=\"data row27 col10\" >0.17</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row27_col11\" class=\"data row27 col11\" >-0.27</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row27_col12\" class=\"data row27 col12\" >-0.13</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row27_col13\" class=\"data row27 col13\" >0.03</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row27_col14\" class=\"data row27 col14\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row27_col15\" class=\"data row27 col15\" >0.04</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row27_col16\" class=\"data row27 col16\" >0.04</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row27_col17\" class=\"data row27 col17\" >0.06</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row27_col18\" class=\"data row27 col18\" >0.03</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row27_col19\" class=\"data row27 col19\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row27_col20\" class=\"data row27 col20\" >0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row27_col21\" class=\"data row27 col21\" >0.05</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row27_col22\" class=\"data row27 col22\" >0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row27_col23\" class=\"data row27 col23\" >0.03</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row27_col24\" class=\"data row27 col24\" >-0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row27_col25\" class=\"data row27 col25\" >1.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row27_col26\" class=\"data row27 col26\" >0.79</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row27_col27\" class=\"data row27 col27\" >1.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row27_col28\" class=\"data row27 col28\" >-0.16</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row27_col29\" class=\"data row27 col29\" >0.73</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row27_col30\" class=\"data row27 col30\" >0.04</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row27_col31\" class=\"data row27 col31\" >-0.20</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row27_col32\" class=\"data row27 col32\" >-0.05</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row27_col33\" class=\"data row27 col33\" >-0.60</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row27_col34\" class=\"data row27 col34\" >0.03</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row27_col35\" class=\"data row27 col35\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row27_col36\" class=\"data row27 col36\" >0.03</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row27_col37\" class=\"data row27 col37\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row27_col38\" class=\"data row27 col38\" >0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row27_col39\" class=\"data row27 col39\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row27_col40\" class=\"data row27 col40\" >0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row27_col41\" class=\"data row27 col41\" >-0.16</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row27_col42\" class=\"data row27 col42\" >0.07</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row27_col43\" class=\"data row27 col43\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row27_col44\" class=\"data row27 col44\" >0.04</td>\n",
+              "            </tr>\n",
+              "            <tr>\n",
+              "                        <th id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002level0_row28\" class=\"row_heading level0 row28\" >Field_Goal_Prob</th>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row28_col0\" class=\"data row28 col0\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row28_col1\" class=\"data row28 col1\" >-0.07</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row28_col2\" class=\"data row28 col2\" >0.17</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row28_col3\" class=\"data row28 col3\" >0.17</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row28_col4\" class=\"data row28 col4\" >0.13</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row28_col5\" class=\"data row28 col5\" >0.05</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row28_col6\" class=\"data row28 col6\" >0.24</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row28_col7\" class=\"data row28 col7\" >0.33</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row28_col8\" class=\"data row28 col8\" >0.16</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row28_col9\" class=\"data row28 col9\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row28_col10\" class=\"data row28 col10\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row28_col11\" class=\"data row28 col11\" >0.19</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row28_col12\" class=\"data row28 col12\" >0.08</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row28_col13\" class=\"data row28 col13\" >-0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row28_col14\" class=\"data row28 col14\" >-0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row28_col15\" class=\"data row28 col15\" >0.13</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row28_col16\" class=\"data row28 col16\" >0.06</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row28_col17\" class=\"data row28 col17\" >0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row28_col18\" class=\"data row28 col18\" >0.04</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row28_col19\" class=\"data row28 col19\" >0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row28_col20\" class=\"data row28 col20\" >0.09</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row28_col21\" class=\"data row28 col21\" >0.07</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row28_col22\" class=\"data row28 col22\" >0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row28_col23\" class=\"data row28 col23\" >0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row28_col24\" class=\"data row28 col24\" >0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row28_col25\" class=\"data row28 col25\" >-0.18</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row28_col26\" class=\"data row28 col26\" >-0.30</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row28_col27\" class=\"data row28 col27\" >-0.16</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row28_col28\" class=\"data row28 col28\" >1.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row28_col29\" class=\"data row28 col29\" >0.19</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row28_col30\" class=\"data row28 col30\" >0.38</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row28_col31\" class=\"data row28 col31\" >-0.24</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row28_col32\" class=\"data row28 col32\" >-0.06</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row28_col33\" class=\"data row28 col33\" >0.60</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row28_col34\" class=\"data row28 col34\" >-0.04</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row28_col35\" class=\"data row28 col35\" >0.07</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row28_col36\" class=\"data row28 col36\" >-0.07</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row28_col37\" class=\"data row28 col37\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row28_col38\" class=\"data row28 col38\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row28_col39\" class=\"data row28 col39\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row28_col40\" class=\"data row28 col40\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row28_col41\" class=\"data row28 col41\" >0.10</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row28_col42\" class=\"data row28 col42\" >-0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row28_col43\" class=\"data row28 col43\" >0.05</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row28_col44\" class=\"data row28 col44\" >-0.05</td>\n",
+              "            </tr>\n",
+              "            <tr>\n",
+              "                        <th id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002level0_row29\" class=\"row_heading level0 row29\" >Safety_Prob</th>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row29_col0\" class=\"data row29 col0\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row29_col1\" class=\"data row29 col1\" >-0.18</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row29_col2\" class=\"data row29 col2\" >0.22</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row29_col3\" class=\"data row29 col3\" >0.50</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row29_col4\" class=\"data row29 col4\" >0.18</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row29_col5\" class=\"data row29 col5\" >0.25</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row29_col6\" class=\"data row29 col6\" >0.31</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row29_col7\" class=\"data row29 col7\" >-0.21</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row29_col8\" class=\"data row29 col8\" >-0.09</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row29_col9\" class=\"data row29 col9\" >0.27</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row29_col10\" class=\"data row29 col10\" >0.14</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row29_col11\" class=\"data row29 col11\" >-0.28</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row29_col12\" class=\"data row29 col12\" >0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row29_col13\" class=\"data row29 col13\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row29_col14\" class=\"data row29 col14\" >-0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row29_col15\" class=\"data row29 col15\" >0.14</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row29_col16\" class=\"data row29 col16\" >0.08</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row29_col17\" class=\"data row29 col17\" >0.07</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row29_col18\" class=\"data row29 col18\" >0.05</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row29_col19\" class=\"data row29 col19\" >0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row29_col20\" class=\"data row29 col20\" >0.13</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row29_col21\" class=\"data row29 col21\" >0.10</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row29_col22\" class=\"data row29 col22\" >0.03</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row29_col23\" class=\"data row29 col23\" >0.04</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row29_col24\" class=\"data row29 col24\" >0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row29_col25\" class=\"data row29 col25\" >0.70</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row29_col26\" class=\"data row29 col26\" >0.33</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row29_col27\" class=\"data row29 col27\" >0.73</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row29_col28\" class=\"data row29 col28\" >0.19</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row29_col29\" class=\"data row29 col29\" >1.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row29_col30\" class=\"data row29 col30\" >0.49</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row29_col31\" class=\"data row29 col31\" >-0.28</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row29_col32\" class=\"data row29 col32\" >-0.07</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row29_col33\" class=\"data row29 col33\" >-0.05</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row29_col34\" class=\"data row29 col34\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row29_col35\" class=\"data row29 col35\" >0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row29_col36\" class=\"data row29 col36\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row29_col37\" class=\"data row29 col37\" >-0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row29_col38\" class=\"data row29 col38\" >0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row29_col39\" class=\"data row29 col39\" >-0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row29_col40\" class=\"data row29 col40\" >0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row29_col41\" class=\"data row29 col41\" >-0.06</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row29_col42\" class=\"data row29 col42\" >0.05</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row29_col43\" class=\"data row29 col43\" >-0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row29_col44\" class=\"data row29 col44\" >0.02</td>\n",
+              "            </tr>\n",
+              "            <tr>\n",
+              "                        <th id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002level0_row30\" class=\"row_heading level0 row30\" >Touchdown_Prob</th>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row30_col0\" class=\"data row30 col0\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row30_col1\" class=\"data row30 col1\" >-0.11</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row30_col2\" class=\"data row30 col2\" >-0.45</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row30_col3\" class=\"data row30 col3\" >0.34</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row30_col4\" class=\"data row30 col4\" >0.28</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row30_col5\" class=\"data row30 col5\" >0.07</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row30_col6\" class=\"data row30 col6\" >0.16</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row30_col7\" class=\"data row30 col7\" >0.23</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row30_col8\" class=\"data row30 col8\" >0.36</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row30_col9\" class=\"data row30 col9\" >0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row30_col10\" class=\"data row30 col10\" >0.08</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row30_col11\" class=\"data row30 col11\" >-0.15</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row30_col12\" class=\"data row30 col12\" >0.22</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row30_col13\" class=\"data row30 col13\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row30_col14\" class=\"data row30 col14\" >-0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row30_col15\" class=\"data row30 col15\" >0.18</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row30_col16\" class=\"data row30 col16\" >0.06</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row30_col17\" class=\"data row30 col17\" >0.05</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row30_col18\" class=\"data row30 col18\" >0.03</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row30_col19\" class=\"data row30 col19\" >0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row30_col20\" class=\"data row30 col20\" >0.35</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row30_col21\" class=\"data row30 col21\" >0.12</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row30_col22\" class=\"data row30 col22\" >0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row30_col23\" class=\"data row30 col23\" >0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row30_col24\" class=\"data row30 col24\" >0.03</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row30_col25\" class=\"data row30 col25\" >0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row30_col26\" class=\"data row30 col26\" >-0.17</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row30_col27\" class=\"data row30 col27\" >0.04</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row30_col28\" class=\"data row30 col28\" >0.38</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row30_col29\" class=\"data row30 col29\" >0.49</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row30_col30\" class=\"data row30 col30\" >1.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row30_col31\" class=\"data row30 col31\" >-0.28</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row30_col32\" class=\"data row30 col32\" >-0.07</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row30_col33\" class=\"data row30 col33\" >0.73</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row30_col34\" class=\"data row30 col34\" >-0.04</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row30_col35\" class=\"data row30 col35\" >-0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row30_col36\" class=\"data row30 col36\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row30_col37\" class=\"data row30 col37\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row30_col38\" class=\"data row30 col38\" >0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row30_col39\" class=\"data row30 col39\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row30_col40\" class=\"data row30 col40\" >0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row30_col41\" class=\"data row30 col41\" >0.10</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row30_col42\" class=\"data row30 col42\" >-0.03</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row30_col43\" class=\"data row30 col43\" >-0.03</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row30_col44\" class=\"data row30 col44\" >0.01</td>\n",
+              "            </tr>\n",
+              "            <tr>\n",
+              "                        <th id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002level0_row31\" class=\"row_heading level0 row31\" >ExPoint_Prob</th>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row31_col0\" class=\"data row31 col0\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row31_col1\" class=\"data row31 col1\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row31_col2\" class=\"data row31 col2\" >-</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row31_col3\" class=\"data row31 col3\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row31_col4\" class=\"data row31 col4\" >-0.12</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row31_col5\" class=\"data row31 col5\" >-0.28</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row31_col6\" class=\"data row31 col6\" >-0.24</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row31_col7\" class=\"data row31 col7\" >0.25</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row31_col8\" class=\"data row31 col8\" >-0.04</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row31_col9\" class=\"data row31 col9\" >-0.11</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row31_col10\" class=\"data row31 col10\" >-0.09</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row31_col11\" class=\"data row31 col11\" >0.55</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row31_col12\" class=\"data row31 col12\" >-0.03</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row31_col13\" class=\"data row31 col13\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row31_col14\" class=\"data row31 col14\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row31_col15\" class=\"data row31 col15\" >-0.13</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row31_col16\" class=\"data row31 col16\" >-0.07</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row31_col17\" class=\"data row31 col17\" >-0.05</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row31_col18\" class=\"data row31 col18\" >-0.04</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row31_col19\" class=\"data row31 col19\" >-0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row31_col20\" class=\"data row31 col20\" >-0.10</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row31_col21\" class=\"data row31 col21\" >-0.09</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row31_col22\" class=\"data row31 col22\" >-0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row31_col23\" class=\"data row31 col23\" >-0.03</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row31_col24\" class=\"data row31 col24\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row31_col25\" class=\"data row31 col25\" >-0.21</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row31_col26\" class=\"data row31 col26\" >-0.12</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row31_col27\" class=\"data row31 col27\" >-0.20</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row31_col28\" class=\"data row31 col28\" >-0.24</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row31_col29\" class=\"data row31 col29\" >-0.28</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row31_col30\" class=\"data row31 col30\" >-0.28</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row31_col31\" class=\"data row31 col31\" >1.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row31_col32\" class=\"data row31 col32\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row31_col33\" class=\"data row31 col33\" >-0.05</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row31_col34\" class=\"data row31 col34\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row31_col35\" class=\"data row31 col35\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row31_col36\" class=\"data row31 col36\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row31_col37\" class=\"data row31 col37\" >0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row31_col38\" class=\"data row31 col38\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row31_col39\" class=\"data row31 col39\" >0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row31_col40\" class=\"data row31 col40\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row31_col41\" class=\"data row31 col41\" >0.09</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row31_col42\" class=\"data row31 col42\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row31_col43\" class=\"data row31 col43\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row31_col44\" class=\"data row31 col44\" >0.00</td>\n",
+              "            </tr>\n",
+              "            <tr>\n",
+              "                        <th id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002level0_row32\" class=\"row_heading level0 row32\" >TwoPoint_Prob</th>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row32_col0\" class=\"data row32 col0\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row32_col1\" class=\"data row32 col1\" >0.04</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row32_col2\" class=\"data row32 col2\" >-</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row32_col3\" class=\"data row32 col3\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row32_col4\" class=\"data row32 col4\" >-0.03</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row32_col5\" class=\"data row32 col5\" >-0.08</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row32_col6\" class=\"data row32 col6\" >-0.06</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row32_col7\" class=\"data row32 col7\" >0.06</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row32_col8\" class=\"data row32 col8\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row32_col9\" class=\"data row32 col9\" >-0.03</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row32_col10\" class=\"data row32 col10\" >-0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row32_col11\" class=\"data row32 col11\" >0.06</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row32_col12\" class=\"data row32 col12\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row32_col13\" class=\"data row32 col13\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row32_col14\" class=\"data row32 col14\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row32_col15\" class=\"data row32 col15\" >0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row32_col16\" class=\"data row32 col16\" >-0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row32_col17\" class=\"data row32 col17\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row32_col18\" class=\"data row32 col18\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row32_col19\" class=\"data row32 col19\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row32_col20\" class=\"data row32 col20\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row32_col21\" class=\"data row32 col21\" >0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row32_col22\" class=\"data row32 col22\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row32_col23\" class=\"data row32 col23\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row32_col24\" class=\"data row32 col24\" >0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row32_col25\" class=\"data row32 col25\" >-0.05</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row32_col26\" class=\"data row32 col26\" >-0.03</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row32_col27\" class=\"data row32 col27\" >-0.05</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row32_col28\" class=\"data row32 col28\" >-0.06</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row32_col29\" class=\"data row32 col29\" >-0.07</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row32_col30\" class=\"data row32 col30\" >-0.07</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row32_col31\" class=\"data row32 col31\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row32_col32\" class=\"data row32 col32\" >1.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row32_col33\" class=\"data row32 col33\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row32_col34\" class=\"data row32 col34\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row32_col35\" class=\"data row32 col35\" >0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row32_col36\" class=\"data row32 col36\" >0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row32_col37\" class=\"data row32 col37\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row32_col38\" class=\"data row32 col38\" >0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row32_col39\" class=\"data row32 col39\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row32_col40\" class=\"data row32 col40\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row32_col41\" class=\"data row32 col41\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row32_col42\" class=\"data row32 col42\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row32_col43\" class=\"data row32 col43\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row32_col44\" class=\"data row32 col44\" >0.01</td>\n",
+              "            </tr>\n",
+              "            <tr>\n",
+              "                        <th id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002level0_row33\" class=\"row_heading level0 row33\" >ExpPts</th>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row33_col0\" class=\"data row33 col0\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row33_col1\" class=\"data row33 col1\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row33_col2\" class=\"data row33 col2\" >-0.33</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row33_col3\" class=\"data row33 col3\" >0.04</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row33_col4\" class=\"data row33 col4\" >0.21</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row33_col5\" class=\"data row33 col5\" >0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row33_col6\" class=\"data row33 col6\" >0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row33_col7\" class=\"data row33 col7\" >0.56</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row33_col8\" class=\"data row33 col8\" >0.43</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row33_col9\" class=\"data row33 col9\" >-0.14</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row33_col10\" class=\"data row33 col10\" >-0.05</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row33_col11\" class=\"data row33 col11\" >0.15</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row33_col12\" class=\"data row33 col12\" >0.24</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row33_col13\" class=\"data row33 col13\" >-0.03</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row33_col14\" class=\"data row33 col14\" >-0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row33_col15\" class=\"data row33 col15\" >0.12</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row33_col16\" class=\"data row33 col16\" >0.03</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row33_col17\" class=\"data row33 col17\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row33_col18\" class=\"data row33 col18\" >0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row33_col19\" class=\"data row33 col19\" >0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row33_col20\" class=\"data row33 col20\" >0.25</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row33_col21\" class=\"data row33 col21\" >0.06</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row33_col22\" class=\"data row33 col22\" >0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row33_col23\" class=\"data row33 col23\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row33_col24\" class=\"data row33 col24\" >0.03</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row33_col25\" class=\"data row33 col25\" >-0.63</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row33_col26\" class=\"data row33 col26\" >-0.65</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row33_col27\" class=\"data row33 col27\" >-0.60</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row33_col28\" class=\"data row33 col28\" >0.60</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row33_col29\" class=\"data row33 col29\" >-0.05</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row33_col30\" class=\"data row33 col30\" >0.73</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row33_col31\" class=\"data row33 col31\" >-0.05</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row33_col32\" class=\"data row33 col32\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row33_col33\" class=\"data row33 col33\" >1.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row33_col34\" class=\"data row33 col34\" >-0.05</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row33_col35\" class=\"data row33 col35\" >0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row33_col36\" class=\"data row33 col36\" >-0.03</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row33_col37\" class=\"data row33 col37\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row33_col38\" class=\"data row33 col38\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row33_col39\" class=\"data row33 col39\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row33_col40\" class=\"data row33 col40\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row33_col41\" class=\"data row33 col41\" >0.18</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row33_col42\" class=\"data row33 col42\" >-0.07</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row33_col43\" class=\"data row33 col43\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row33_col44\" class=\"data row33 col44\" >-0.03</td>\n",
+              "            </tr>\n",
+              "            <tr>\n",
+              "                        <th id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002level0_row34\" class=\"row_heading level0 row34\" >EPA</th>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row34_col0\" class=\"data row34 col0\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row34_col1\" class=\"data row34 col1\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row34_col2\" class=\"data row34 col2\" >0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row34_col3\" class=\"data row34 col3\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row34_col4\" class=\"data row34 col4\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row34_col5\" class=\"data row34 col5\" >-0.04</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row34_col6\" class=\"data row34 col6\" >-0.04</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row34_col7\" class=\"data row34 col7\" >0.22</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row34_col8\" class=\"data row34 col8\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row34_col9\" class=\"data row34 col9\" >0.27</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row34_col10\" class=\"data row34 col10\" >0.53</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row34_col11\" class=\"data row34 col11\" >0.20</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row34_col12\" class=\"data row34 col12\" >0.25</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row34_col13\" class=\"data row34 col13\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row34_col14\" class=\"data row34 col14\" >0.03</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row34_col15\" class=\"data row34 col15\" >0.08</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row34_col16\" class=\"data row34 col16\" >0.10</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row34_col17\" class=\"data row34 col17\" >0.35</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row34_col18\" class=\"data row34 col18\" >-0.16</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row34_col19\" class=\"data row34 col19\" >-0.33</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row34_col20\" class=\"data row34 col20\" >-0.04</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row34_col21\" class=\"data row34 col21\" >0.36</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row34_col22\" class=\"data row34 col22\" >-0.21</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row34_col23\" class=\"data row34 col23\" >-0.21</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row34_col24\" class=\"data row34 col24\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row34_col25\" class=\"data row34 col25\" >0.03</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row34_col26\" class=\"data row34 col26\" >0.03</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row34_col27\" class=\"data row34 col27\" >0.03</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row34_col28\" class=\"data row34 col28\" >-0.04</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row34_col29\" class=\"data row34 col29\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row34_col30\" class=\"data row34 col30\" >-0.04</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row34_col31\" class=\"data row34 col31\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row34_col32\" class=\"data row34 col32\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row34_col33\" class=\"data row34 col33\" >-0.05</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row34_col34\" class=\"data row34 col34\" >1.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row34_col35\" class=\"data row34 col35\" >0.14</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row34_col36\" class=\"data row34 col36\" >0.72</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row34_col37\" class=\"data row34 col37\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row34_col38\" class=\"data row34 col38\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row34_col39\" class=\"data row34 col39\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row34_col40\" class=\"data row34 col40\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row34_col41\" class=\"data row34 col41\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row34_col42\" class=\"data row34 col42\" >0.75</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row34_col43\" class=\"data row34 col43\" >0.11</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row34_col44\" class=\"data row34 col44\" >0.54</td>\n",
+              "            </tr>\n",
+              "            <tr>\n",
+              "                        <th id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002level0_row35\" class=\"row_heading level0 row35\" >airEPA</th>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row35_col0\" class=\"data row35 col0\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row35_col1\" class=\"data row35 col1\" >0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row35_col2\" class=\"data row35 col2\" >0.15</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row35_col3\" class=\"data row35 col3\" >-0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row35_col4\" class=\"data row35 col4\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row35_col5\" class=\"data row35 col5\" >-0.11</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row35_col6\" class=\"data row35 col6\" >-0.11</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row35_col7\" class=\"data row35 col7\" >0.14</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row35_col8\" class=\"data row35 col8\" >0.08</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row35_col9\" class=\"data row35 col9\" >0.12</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row35_col10\" class=\"data row35 col10\" >0.16</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row35_col11\" class=\"data row35 col11\" >0.17</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row35_col12\" class=\"data row35 col12\" >0.17</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row35_col13\" class=\"data row35 col13\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row35_col14\" class=\"data row35 col14\" >0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row35_col15\" class=\"data row35 col15\" >-</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row35_col16\" class=\"data row35 col16\" >0.77</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row35_col17\" class=\"data row35 col17\" >-0.22</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row35_col18\" class=\"data row35 col18\" >0.03</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row35_col19\" class=\"data row35 col19\" >0.10</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row35_col20\" class=\"data row35 col20\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row35_col21\" class=\"data row35 col21\" >-0.25</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row35_col22\" class=\"data row35 col22\" >-0.05</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row35_col23\" class=\"data row35 col23\" >-0.03</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row35_col24\" class=\"data row35 col24\" >0.03</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row35_col25\" class=\"data row35 col25\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row35_col26\" class=\"data row35 col26\" >0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row35_col27\" class=\"data row35 col27\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row35_col28\" class=\"data row35 col28\" >0.07</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row35_col29\" class=\"data row35 col29\" >0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row35_col30\" class=\"data row35 col30\" >-0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row35_col31\" class=\"data row35 col31\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row35_col32\" class=\"data row35 col32\" >0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row35_col33\" class=\"data row35 col33\" >0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row35_col34\" class=\"data row35 col34\" >0.14</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row35_col35\" class=\"data row35 col35\" >1.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row35_col36\" class=\"data row35 col36\" >-0.59</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row35_col37\" class=\"data row35 col37\" >0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row35_col38\" class=\"data row35 col38\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row35_col39\" class=\"data row35 col39\" >0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row35_col40\" class=\"data row35 col40\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row35_col41\" class=\"data row35 col41\" >-0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row35_col42\" class=\"data row35 col42\" >0.13</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row35_col43\" class=\"data row35 col43\" >0.70</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row35_col44\" class=\"data row35 col44\" >-0.47</td>\n",
+              "            </tr>\n",
+              "            <tr>\n",
+              "                        <th id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002level0_row36\" class=\"row_heading level0 row36\" >yacEPA</th>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row36_col0\" class=\"data row36 col0\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row36_col1\" class=\"data row36 col1\" >-0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row36_col2\" class=\"data row36 col2\" >-0.11</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row36_col3\" class=\"data row36 col3\" >0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row36_col4\" class=\"data row36 col4\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row36_col5\" class=\"data row36 col5\" >0.04</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row36_col6\" class=\"data row36 col6\" >0.06</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row36_col7\" class=\"data row36 col7\" >0.15</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row36_col8\" class=\"data row36 col8\" >-0.07</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row36_col9\" class=\"data row36 col9\" >0.20</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row36_col10\" class=\"data row36 col10\" >0.48</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row36_col11\" class=\"data row36 col11\" >0.13</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row36_col12\" class=\"data row36 col12\" >0.12</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row36_col13\" class=\"data row36 col13\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row36_col14\" class=\"data row36 col14\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row36_col15\" class=\"data row36 col15\" >-</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row36_col16\" class=\"data row36 col16\" >-0.47</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row36_col17\" class=\"data row36 col17\" >0.54</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row36_col18\" class=\"data row36 col18\" >-0.09</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row36_col19\" class=\"data row36 col19\" >-0.45</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row36_col20\" class=\"data row36 col20\" >0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row36_col21\" class=\"data row36 col21\" >0.67</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row36_col22\" class=\"data row36 col22\" >-0.06</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row36_col23\" class=\"data row36 col23\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row36_col24\" class=\"data row36 col24\" >-0.03</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row36_col25\" class=\"data row36 col25\" >0.03</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row36_col26\" class=\"data row36 col26\" >0.03</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row36_col27\" class=\"data row36 col27\" >0.03</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row36_col28\" class=\"data row36 col28\" >-0.07</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row36_col29\" class=\"data row36 col29\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row36_col30\" class=\"data row36 col30\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row36_col31\" class=\"data row36 col31\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row36_col32\" class=\"data row36 col32\" >0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row36_col33\" class=\"data row36 col33\" >-0.03</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row36_col34\" class=\"data row36 col34\" >0.72</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row36_col35\" class=\"data row36 col35\" >-0.59</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row36_col36\" class=\"data row36 col36\" >1.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row36_col37\" class=\"data row36 col37\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row36_col38\" class=\"data row36 col38\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row36_col39\" class=\"data row36 col39\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row36_col40\" class=\"data row36 col40\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row36_col41\" class=\"data row36 col41\" >0.03</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row36_col42\" class=\"data row36 col42\" >0.57</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row36_col43\" class=\"data row36 col43\" >-0.41</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row36_col44\" class=\"data row36 col44\" >0.77</td>\n",
+              "            </tr>\n",
+              "            <tr>\n",
+              "                        <th id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002level0_row37\" class=\"row_heading level0 row37\" >Home_WP_pre</th>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row37_col0\" class=\"data row37 col0\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row37_col1\" class=\"data row37 col1\" >0.04</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row37_col2\" class=\"data row37 col2\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row37_col3\" class=\"data row37 col3\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row37_col4\" class=\"data row37 col4\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row37_col5\" class=\"data row37 col5\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row37_col6\" class=\"data row37 col6\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row37_col7\" class=\"data row37 col7\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row37_col8\" class=\"data row37 col8\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row37_col9\" class=\"data row37 col9\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row37_col10\" class=\"data row37 col10\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row37_col11\" class=\"data row37 col11\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row37_col12\" class=\"data row37 col12\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row37_col13\" class=\"data row37 col13\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row37_col14\" class=\"data row37 col14\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row37_col15\" class=\"data row37 col15\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row37_col16\" class=\"data row37 col16\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row37_col17\" class=\"data row37 col17\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row37_col18\" class=\"data row37 col18\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row37_col19\" class=\"data row37 col19\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row37_col20\" class=\"data row37 col20\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row37_col21\" class=\"data row37 col21\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row37_col22\" class=\"data row37 col22\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row37_col23\" class=\"data row37 col23\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row37_col24\" class=\"data row37 col24\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row37_col25\" class=\"data row37 col25\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row37_col26\" class=\"data row37 col26\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row37_col27\" class=\"data row37 col27\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row37_col28\" class=\"data row37 col28\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row37_col29\" class=\"data row37 col29\" >-0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row37_col30\" class=\"data row37 col30\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row37_col31\" class=\"data row37 col31\" >0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row37_col32\" class=\"data row37 col32\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row37_col33\" class=\"data row37 col33\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row37_col34\" class=\"data row37 col34\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row37_col35\" class=\"data row37 col35\" >0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row37_col36\" class=\"data row37 col36\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row37_col37\" class=\"data row37 col37\" >1.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row37_col38\" class=\"data row37 col38\" >-1.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row37_col39\" class=\"data row37 col39\" >0.99</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row37_col40\" class=\"data row37 col40\" >-0.98</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row37_col41\" class=\"data row37 col41\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row37_col42\" class=\"data row37 col42\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row37_col43\" class=\"data row37 col43\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row37_col44\" class=\"data row37 col44\" >0.01</td>\n",
+              "            </tr>\n",
+              "            <tr>\n",
+              "                        <th id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002level0_row38\" class=\"row_heading level0 row38\" >Away_WP_pre</th>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row38_col0\" class=\"data row38 col0\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row38_col1\" class=\"data row38 col1\" >-0.03</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row38_col2\" class=\"data row38 col2\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row38_col3\" class=\"data row38 col3\" >0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row38_col4\" class=\"data row38 col4\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row38_col5\" class=\"data row38 col5\" >0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row38_col6\" class=\"data row38 col6\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row38_col7\" class=\"data row38 col7\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row38_col8\" class=\"data row38 col8\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row38_col9\" class=\"data row38 col9\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row38_col10\" class=\"data row38 col10\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row38_col11\" class=\"data row38 col11\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row38_col12\" class=\"data row38 col12\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row38_col13\" class=\"data row38 col13\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row38_col14\" class=\"data row38 col14\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row38_col15\" class=\"data row38 col15\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row38_col16\" class=\"data row38 col16\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row38_col17\" class=\"data row38 col17\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row38_col18\" class=\"data row38 col18\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row38_col19\" class=\"data row38 col19\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row38_col20\" class=\"data row38 col20\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row38_col21\" class=\"data row38 col21\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row38_col22\" class=\"data row38 col22\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row38_col23\" class=\"data row38 col23\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row38_col24\" class=\"data row38 col24\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row38_col25\" class=\"data row38 col25\" >0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row38_col26\" class=\"data row38 col26\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row38_col27\" class=\"data row38 col27\" >0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row38_col28\" class=\"data row38 col28\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row38_col29\" class=\"data row38 col29\" >0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row38_col30\" class=\"data row38 col30\" >0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row38_col31\" class=\"data row38 col31\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row38_col32\" class=\"data row38 col32\" >0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row38_col33\" class=\"data row38 col33\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row38_col34\" class=\"data row38 col34\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row38_col35\" class=\"data row38 col35\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row38_col36\" class=\"data row38 col36\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row38_col37\" class=\"data row38 col37\" >-1.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row38_col38\" class=\"data row38 col38\" >1.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row38_col39\" class=\"data row38 col39\" >-0.98</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row38_col40\" class=\"data row38 col40\" >0.99</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row38_col41\" class=\"data row38 col41\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row38_col42\" class=\"data row38 col42\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row38_col43\" class=\"data row38 col43\" >0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row38_col44\" class=\"data row38 col44\" >-0.01</td>\n",
+              "            </tr>\n",
+              "            <tr>\n",
+              "                        <th id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002level0_row39\" class=\"row_heading level0 row39\" >Home_WP_post</th>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row39_col0\" class=\"data row39 col0\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row39_col1\" class=\"data row39 col1\" >0.04</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row39_col2\" class=\"data row39 col2\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row39_col3\" class=\"data row39 col3\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row39_col4\" class=\"data row39 col4\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row39_col5\" class=\"data row39 col5\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row39_col6\" class=\"data row39 col6\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row39_col7\" class=\"data row39 col7\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row39_col8\" class=\"data row39 col8\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row39_col9\" class=\"data row39 col9\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row39_col10\" class=\"data row39 col10\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row39_col11\" class=\"data row39 col11\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row39_col12\" class=\"data row39 col12\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row39_col13\" class=\"data row39 col13\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row39_col14\" class=\"data row39 col14\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row39_col15\" class=\"data row39 col15\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row39_col16\" class=\"data row39 col16\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row39_col17\" class=\"data row39 col17\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row39_col18\" class=\"data row39 col18\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row39_col19\" class=\"data row39 col19\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row39_col20\" class=\"data row39 col20\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row39_col21\" class=\"data row39 col21\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row39_col22\" class=\"data row39 col22\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row39_col23\" class=\"data row39 col23\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row39_col24\" class=\"data row39 col24\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row39_col25\" class=\"data row39 col25\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row39_col26\" class=\"data row39 col26\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row39_col27\" class=\"data row39 col27\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row39_col28\" class=\"data row39 col28\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row39_col29\" class=\"data row39 col29\" >-0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row39_col30\" class=\"data row39 col30\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row39_col31\" class=\"data row39 col31\" >0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row39_col32\" class=\"data row39 col32\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row39_col33\" class=\"data row39 col33\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row39_col34\" class=\"data row39 col34\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row39_col35\" class=\"data row39 col35\" >0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row39_col36\" class=\"data row39 col36\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row39_col37\" class=\"data row39 col37\" >0.99</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row39_col38\" class=\"data row39 col38\" >-0.98</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row39_col39\" class=\"data row39 col39\" >1.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row39_col40\" class=\"data row39 col40\" >-1.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row39_col41\" class=\"data row39 col41\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row39_col42\" class=\"data row39 col42\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row39_col43\" class=\"data row39 col43\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row39_col44\" class=\"data row39 col44\" >0.00</td>\n",
+              "            </tr>\n",
+              "            <tr>\n",
+              "                        <th id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002level0_row40\" class=\"row_heading level0 row40\" >Away_WP_post</th>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row40_col0\" class=\"data row40 col0\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row40_col1\" class=\"data row40 col1\" >-0.03</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row40_col2\" class=\"data row40 col2\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row40_col3\" class=\"data row40 col3\" >0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row40_col4\" class=\"data row40 col4\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row40_col5\" class=\"data row40 col5\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row40_col6\" class=\"data row40 col6\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row40_col7\" class=\"data row40 col7\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row40_col8\" class=\"data row40 col8\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row40_col9\" class=\"data row40 col9\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row40_col10\" class=\"data row40 col10\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row40_col11\" class=\"data row40 col11\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row40_col12\" class=\"data row40 col12\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row40_col13\" class=\"data row40 col13\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row40_col14\" class=\"data row40 col14\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row40_col15\" class=\"data row40 col15\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row40_col16\" class=\"data row40 col16\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row40_col17\" class=\"data row40 col17\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row40_col18\" class=\"data row40 col18\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row40_col19\" class=\"data row40 col19\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row40_col20\" class=\"data row40 col20\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row40_col21\" class=\"data row40 col21\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row40_col22\" class=\"data row40 col22\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row40_col23\" class=\"data row40 col23\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row40_col24\" class=\"data row40 col24\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row40_col25\" class=\"data row40 col25\" >0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row40_col26\" class=\"data row40 col26\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row40_col27\" class=\"data row40 col27\" >0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row40_col28\" class=\"data row40 col28\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row40_col29\" class=\"data row40 col29\" >0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row40_col30\" class=\"data row40 col30\" >0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row40_col31\" class=\"data row40 col31\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row40_col32\" class=\"data row40 col32\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row40_col33\" class=\"data row40 col33\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row40_col34\" class=\"data row40 col34\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row40_col35\" class=\"data row40 col35\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row40_col36\" class=\"data row40 col36\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row40_col37\" class=\"data row40 col37\" >-0.98</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row40_col38\" class=\"data row40 col38\" >0.99</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row40_col39\" class=\"data row40 col39\" >-1.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row40_col40\" class=\"data row40 col40\" >1.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row40_col41\" class=\"data row40 col41\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row40_col42\" class=\"data row40 col42\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row40_col43\" class=\"data row40 col43\" >0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row40_col44\" class=\"data row40 col44\" >-0.00</td>\n",
+              "            </tr>\n",
+              "            <tr>\n",
+              "                        <th id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002level0_row41\" class=\"row_heading level0 row41\" >Win_Prob</th>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row41_col0\" class=\"data row41 col0\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row41_col1\" class=\"data row41 col1\" >-0.03</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row41_col2\" class=\"data row41 col2\" >-0.03</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row41_col3\" class=\"data row41 col3\" >0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row41_col4\" class=\"data row41 col4\" >0.10</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row41_col5\" class=\"data row41 col5\" >-0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row41_col6\" class=\"data row41 col6\" >-0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row41_col7\" class=\"data row41 col7\" >0.08</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row41_col8\" class=\"data row41 col8\" >0.08</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row41_col9\" class=\"data row41 col9\" >-0.08</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row41_col10\" class=\"data row41 col10\" >-0.05</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row41_col11\" class=\"data row41 col11\" >0.09</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row41_col12\" class=\"data row41 col12\" >0.04</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row41_col13\" class=\"data row41 col13\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row41_col14\" class=\"data row41 col14\" >0.05</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row41_col15\" class=\"data row41 col15\" >-0.13</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row41_col16\" class=\"data row41 col16\" >-0.09</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row41_col17\" class=\"data row41 col17\" >-0.03</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row41_col18\" class=\"data row41 col18\" >-0.06</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row41_col19\" class=\"data row41 col19\" >-0.04</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row41_col20\" class=\"data row41 col20\" >0.16</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row41_col21\" class=\"data row41 col21\" >-0.08</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row41_col22\" class=\"data row41 col22\" >-0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row41_col23\" class=\"data row41 col23\" >-0.04</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row41_col24\" class=\"data row41 col24\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row41_col25\" class=\"data row41 col25\" >-0.17</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row41_col26\" class=\"data row41 col26\" >-0.15</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row41_col27\" class=\"data row41 col27\" >-0.16</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row41_col28\" class=\"data row41 col28\" >0.10</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row41_col29\" class=\"data row41 col29\" >-0.06</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row41_col30\" class=\"data row41 col30\" >0.10</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row41_col31\" class=\"data row41 col31\" >0.09</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row41_col32\" class=\"data row41 col32\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row41_col33\" class=\"data row41 col33\" >0.18</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row41_col34\" class=\"data row41 col34\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row41_col35\" class=\"data row41 col35\" >-0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row41_col36\" class=\"data row41 col36\" >0.03</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row41_col37\" class=\"data row41 col37\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row41_col38\" class=\"data row41 col38\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row41_col39\" class=\"data row41 col39\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row41_col40\" class=\"data row41 col40\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row41_col41\" class=\"data row41 col41\" >1.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row41_col42\" class=\"data row41 col42\" >-0.03</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row41_col43\" class=\"data row41 col43\" >-0.03</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row41_col44\" class=\"data row41 col44\" >0.02</td>\n",
+              "            </tr>\n",
+              "            <tr>\n",
+              "                        <th id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002level0_row42\" class=\"row_heading level0 row42\" >WPA</th>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row42_col0\" class=\"data row42 col0\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row42_col1\" class=\"data row42 col1\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row42_col2\" class=\"data row42 col2\" >0.07</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row42_col3\" class=\"data row42 col3\" >0.03</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row42_col4\" class=\"data row42 col4\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row42_col5\" class=\"data row42 col5\" >-0.03</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row42_col6\" class=\"data row42 col6\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row42_col7\" class=\"data row42 col7\" >0.16</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row42_col8\" class=\"data row42 col8\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row42_col9\" class=\"data row42 col9\" >0.28</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row42_col10\" class=\"data row42 col10\" >0.43</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row42_col11\" class=\"data row42 col11\" >0.17</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row42_col12\" class=\"data row42 col12\" >0.22</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row42_col13\" class=\"data row42 col13\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row42_col14\" class=\"data row42 col14\" >-0.04</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row42_col15\" class=\"data row42 col15\" >0.06</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row42_col16\" class=\"data row42 col16\" >0.08</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row42_col17\" class=\"data row42 col17\" >0.28</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row42_col18\" class=\"data row42 col18\" >-0.13</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row42_col19\" class=\"data row42 col19\" >-0.22</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row42_col20\" class=\"data row42 col20\" >-0.04</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row42_col21\" class=\"data row42 col21\" >0.28</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row42_col22\" class=\"data row42 col22\" >-0.14</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row42_col23\" class=\"data row42 col23\" >-0.16</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row42_col24\" class=\"data row42 col24\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row42_col25\" class=\"data row42 col25\" >0.07</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row42_col26\" class=\"data row42 col26\" >0.05</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row42_col27\" class=\"data row42 col27\" >0.07</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row42_col28\" class=\"data row42 col28\" >-0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row42_col29\" class=\"data row42 col29\" >0.05</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row42_col30\" class=\"data row42 col30\" >-0.03</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row42_col31\" class=\"data row42 col31\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row42_col32\" class=\"data row42 col32\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row42_col33\" class=\"data row42 col33\" >-0.07</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row42_col34\" class=\"data row42 col34\" >0.75</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row42_col35\" class=\"data row42 col35\" >0.13</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row42_col36\" class=\"data row42 col36\" >0.57</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row42_col37\" class=\"data row42 col37\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row42_col38\" class=\"data row42 col38\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row42_col39\" class=\"data row42 col39\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row42_col40\" class=\"data row42 col40\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row42_col41\" class=\"data row42 col41\" >-0.03</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row42_col42\" class=\"data row42 col42\" >1.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row42_col43\" class=\"data row42 col43\" >0.19</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row42_col44\" class=\"data row42 col44\" >0.62</td>\n",
+              "            </tr>\n",
+              "            <tr>\n",
+              "                        <th id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002level0_row43\" class=\"row_heading level0 row43\" >airWPA</th>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row43_col0\" class=\"data row43 col0\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row43_col1\" class=\"data row43 col1\" >0.04</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row43_col2\" class=\"data row43 col2\" >0.10</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row43_col3\" class=\"data row43 col3\" >-0.03</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row43_col4\" class=\"data row43 col4\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row43_col5\" class=\"data row43 col5\" >-0.10</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row43_col6\" class=\"data row43 col6\" >-0.07</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row43_col7\" class=\"data row43 col7\" >0.11</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row43_col8\" class=\"data row43 col8\" >0.07</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row43_col9\" class=\"data row43 col9\" >0.09</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row43_col10\" class=\"data row43 col10\" >0.11</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row43_col11\" class=\"data row43 col11\" >0.13</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row43_col12\" class=\"data row43 col12\" >0.13</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row43_col13\" class=\"data row43 col13\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row43_col14\" class=\"data row43 col14\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row43_col15\" class=\"data row43 col15\" >-</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row43_col16\" class=\"data row43 col16\" >0.53</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row43_col17\" class=\"data row43 col17\" >-0.16</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row43_col18\" class=\"data row43 col18\" >0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row43_col19\" class=\"data row43 col19\" >0.07</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row43_col20\" class=\"data row43 col20\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row43_col21\" class=\"data row43 col21\" >-0.18</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row43_col22\" class=\"data row43 col22\" >-0.04</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row43_col23\" class=\"data row43 col23\" >-0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row43_col24\" class=\"data row43 col24\" >0.04</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row43_col25\" class=\"data row43 col25\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row43_col26\" class=\"data row43 col26\" >0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row43_col27\" class=\"data row43 col27\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row43_col28\" class=\"data row43 col28\" >0.05</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row43_col29\" class=\"data row43 col29\" >-0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row43_col30\" class=\"data row43 col30\" >-0.03</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row43_col31\" class=\"data row43 col31\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row43_col32\" class=\"data row43 col32\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row43_col33\" class=\"data row43 col33\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row43_col34\" class=\"data row43 col34\" >0.11</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row43_col35\" class=\"data row43 col35\" >0.70</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row43_col36\" class=\"data row43 col36\" >-0.41</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row43_col37\" class=\"data row43 col37\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row43_col38\" class=\"data row43 col38\" >0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row43_col39\" class=\"data row43 col39\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row43_col40\" class=\"data row43 col40\" >0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row43_col41\" class=\"data row43 col41\" >-0.03</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row43_col42\" class=\"data row43 col42\" >0.19</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row43_col43\" class=\"data row43 col43\" >1.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row43_col44\" class=\"data row43 col44\" >-0.66</td>\n",
+              "            </tr>\n",
+              "            <tr>\n",
+              "                        <th id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002level0_row44\" class=\"row_heading level0 row44\" >yacWPA</th>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row44_col0\" class=\"data row44 col0\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row44_col1\" class=\"data row44 col1\" >-0.04</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row44_col2\" class=\"data row44 col2\" >-0.08</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row44_col3\" class=\"data row44 col3\" >0.03</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row44_col4\" class=\"data row44 col4\" >0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row44_col5\" class=\"data row44 col5\" >0.04</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row44_col6\" class=\"data row44 col6\" >0.05</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row44_col7\" class=\"data row44 col7\" >0.11</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row44_col8\" class=\"data row44 col8\" >-0.06</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row44_col9\" class=\"data row44 col9\" >0.18</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row44_col10\" class=\"data row44 col10\" >0.39</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row44_col11\" class=\"data row44 col11\" >0.11</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row44_col12\" class=\"data row44 col12\" >0.11</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row44_col13\" class=\"data row44 col13\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row44_col14\" class=\"data row44 col14\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row44_col15\" class=\"data row44 col15\" >-</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row44_col16\" class=\"data row44 col16\" >-0.37</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row44_col17\" class=\"data row44 col17\" >0.43</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row44_col18\" class=\"data row44 col18\" >-0.07</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row44_col19\" class=\"data row44 col19\" >-0.30</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row44_col20\" class=\"data row44 col20\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row44_col21\" class=\"data row44 col21\" >0.54</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row44_col22\" class=\"data row44 col22\" >-0.04</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row44_col23\" class=\"data row44 col23\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row44_col24\" class=\"data row44 col24\" >-0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row44_col25\" class=\"data row44 col25\" >0.04</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row44_col26\" class=\"data row44 col26\" >0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row44_col27\" class=\"data row44 col27\" >0.04</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row44_col28\" class=\"data row44 col28\" >-0.05</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row44_col29\" class=\"data row44 col29\" >0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row44_col30\" class=\"data row44 col30\" >0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row44_col31\" class=\"data row44 col31\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row44_col32\" class=\"data row44 col32\" >0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row44_col33\" class=\"data row44 col33\" >-0.03</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row44_col34\" class=\"data row44 col34\" >0.54</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row44_col35\" class=\"data row44 col35\" >-0.47</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row44_col36\" class=\"data row44 col36\" >0.77</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row44_col37\" class=\"data row44 col37\" >0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row44_col38\" class=\"data row44 col38\" >-0.01</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row44_col39\" class=\"data row44 col39\" >0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row44_col40\" class=\"data row44 col40\" >-0.00</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row44_col41\" class=\"data row44 col41\" >0.02</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row44_col42\" class=\"data row44 col42\" >0.62</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row44_col43\" class=\"data row44 col43\" >-0.66</td>\n",
+              "                        <td id=\"T_1ed7d864_49f0_11eb_b04e_0242ac1c0002row44_col44\" class=\"data row44 col44\" >1.00</td>\n",
+              "            </tr>\n",
+              "    </tbody></table>"
+            ],
+            "text/plain": [
+              "<pandas.io.formats.style.Styler at 0x7f414a1b7f28>"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 9
+        }
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "c3r_lP35up7x"
+      },
+      "source": [
+        "# **Distribution Plot**\n",
+        "\n",
+        "Displays the distribution plot for columns of interest."
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 255
+        },
+        "id": "7Wsj4IuRuqDs",
+        "outputId": "0bb23acf-0584-4d68-d49a-3711083b7628"
+      },
+      "source": [
+        "klib.dist_plot(df_cleaned['Win_Prob'])"
+      ],
+      "execution_count": null,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "text": [
+            "Dropped 11346 missing values from column Win_Prob.\n"
+          ],
+          "name": "stdout"
+        },
+        {
+          "output_type": "stream",
+          "text": [
+            "/usr/local/lib/python3.6/dist-packages/seaborn/distributions.py:2551: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `kdeplot` (an axes-level function for kernel density plots).\n",
+            "  warnings.warn(msg, FutureWarning)\n",
+            "/usr/local/lib/python3.6/dist-packages/seaborn/distributions.py:2055: FutureWarning: The `axis` variable is no longer used and will be removed. Instead, assign variables directly to `x` or `y`.\n",
+            "  warnings.warn(msg, FutureWarning)\n"
+          ],
+          "name": "stderr"
+        },
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "<matplotlib.axes._subplots.AxesSubplot at 0x7f4149e462b0>"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 10
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "image/png": 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\n",
+            "text/plain": [
+              "<Figure size 1008x144 with 1 Axes>"
+            ]
+          },
+          "metadata": {
+            "tags": [],
+            "needs_background": "light"
+          }
+        }
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "SxmfR9IT6YGc"
+      },
+      "source": [
+        "# **Categorical Plot**"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 229
+        },
+        "id": "OibP0TQN3LlS",
+        "outputId": "44d3f7e4-c0ec-4f16-f8a9-a3dc7925ca35"
+      },
+      "source": [
+        "klib.cat_plot(df, figsize=(50,15))"
+      ],
+      "execution_count": null,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "GridSpec(6, 21)"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 11
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "image/png": 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\n",
+            "text/plain": [
+              "<Figure size 3600x1080 with 43 Axes>"
+            ]
+          },
+          "metadata": {
+            "tags": [],
+            "needs_background": "light"
+          }
+        }
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "8h3lAStbhih-"
+      },
+      "source": [
+        "# **Save Plot as a PDF file**"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "tI0YcNB5hkNx",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 594
+        },
+        "outputId": "5644af41-0eb3-45d3-cd34-89b2bd59dc56"
+      },
+      "source": [
+        "plot = klib.corr_plot(df_cleaned, annot=False, figsize=(12,10))"
+      ],
+      "execution_count": null,
+      "outputs": [
+        {
+          "output_type": "display_data",
+          "data": {
+            "image/png": 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\n",
+            "text/plain": [
+              "<Figure size 864x720 with 2 Axes>"
+            ]
+          },
+          "metadata": {
+            "tags": [],
+            "needs_background": "light"
+          }
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "HMxWGD5NihFS"
+      },
+      "source": [
+        "plot.figure.savefig('figure.pdf')"
+      ],
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "M4ZeJoCMRQVH"
+      },
+      "source": [
+        ""
+      ],
+      "execution_count": null,
+      "outputs": []
+    }
+  ]
+}
\ No newline at end of file

From 4caaa03433e4a167fb4249343fde95119551beb6 Mon Sep 17 00:00:00 2001
From: Chanin Nantasenamat <51851491+dataprofessor@users.noreply.github.com>
Date: Sat, 9 Jan 2021 09:05:12 +0700
Subject: [PATCH 02/11] Add files via upload

Progress bar in Jupyter notebook for tracking the progress as your machine learning model is training
---
 python/model_is_training_progress_bar.ipynb | 208 ++++++++++++++++++++
 1 file changed, 208 insertions(+)
 create mode 100644 python/model_is_training_progress_bar.ipynb

diff --git a/python/model_is_training_progress_bar.ipynb b/python/model_is_training_progress_bar.ipynb
new file mode 100644
index 0000000..6c6e46f
--- /dev/null
+++ b/python/model_is_training_progress_bar.ipynb
@@ -0,0 +1,208 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "zzD4-HxqXBmt"
+   },
+   "source": [
+    "# **Progress Bar in Jupyter Notebook**\n",
+    "\n",
+    "Chanin Nantasenamat\n",
+    "\n",
+    "**Data Professor YouTube channel**, http://youtube.com/dataprofessor"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "An7XU557Y5ci"
+   },
+   "source": [
+    "# **Progress Bar with the tqdm library**"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "3yc04janmetd"
+   },
+   "outputs": [],
+   "source": [
+    "# ! pip install tqdm"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {
+    "id": "gxa8jup1DNjt"
+   },
+   "outputs": [],
+   "source": [
+    "from tqdm.notebook import tqdm\n",
+    "from time import sleep"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {
+    "id": "009bdoXCE74q"
+   },
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "93cc2d7933af4faf96fda14e55f24e23",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/100 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "number_list = list(range(100))\n",
+    "for x in tqdm(number_list):\n",
+    "    sleep(0.05)\n",
+    "#print('Completed!')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "4tFGw2QFMz6N"
+   },
+   "source": [
+    "# **Model Building**"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "zKKr9EoSVbOV"
+   },
+   "source": [
+    "### Reading in the Delaney Solubility Dataset"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {
+    "id": "FHR0FBHEMyyL"
+   },
+   "outputs": [],
+   "source": [
+    "import pandas as pd\n",
+    "\n",
+    "dataset = pd.read_csv('https://raw.githubusercontent.com/dataprofessor/data/master/delaney_solubility_with_descriptors.csv')\n",
+    "\n",
+    "X = dataset.drop(['logS'], axis=1)\n",
+    "Y = dataset.iloc[:,-1]\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "BqqRRTtUVi7v"
+   },
+   "source": [
+    "### Model Building with Progress Bar"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {
+    "id": "cpa2tS3kInAx",
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "a1b762495ff545468e8b801795c6b708",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/10 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Tree: 100, R2: 0.9796508266364179, MSE: 0.08936295274735467\n",
+      "Tree: 200, R2: 0.9805478792326812, MSE: 0.08542356575902461\n",
+      "Tree: 300, R2: 0.9801470956638436, MSE: 0.08718359809468906\n",
+      "Tree: 400, R2: 0.9803760482277171, MSE: 0.08617815788435489\n",
+      "Tree: 500, R2: 0.9804686074892891, MSE: 0.08577168589797951\n",
+      "Tree: 600, R2: 0.9804079256830844, MSE: 0.08603816873163578\n",
+      "Tree: 700, R2: 0.9802975717717071, MSE: 0.0865227855360484\n",
+      "Tree: 800, R2: 0.9803651322114956, MSE: 0.08622609533244484\n",
+      "Tree: 900, R2: 0.98037907466393, MSE: 0.08616486735547396\n",
+      "Tree: 1000, R2: 0.9804349669126423, MSE: 0.08591941775949379\n"
+     ]
+    }
+   ],
+   "source": [
+    "from sklearn.ensemble import RandomForestRegressor\n",
+    "from sklearn.metrics import mean_squared_error, r2_score\n",
+    "\n",
+    "parameter_n_estimators = [100,200,300,400,500,600,700,800,900,1000]\n",
+    "\n",
+    "for i in tqdm(parameter_n_estimators):\n",
+    "  model = RandomForestRegressor(n_estimators=i)\n",
+    "  model.fit(X,Y)\n",
+    "  Y_pred = model.predict(X)\n",
+    "  r2 = r2_score(Y, Y_pred)\n",
+    "  mse = mean_squared_error(Y, Y_pred)\n",
+    "  print('Tree: %s, R2: %s, MSE: %s' % (i, r2, mse))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "colab": {
+   "collapsed_sections": [],
+   "name": "Model-building-with-progress-bar.ipynb",
+   "provenance": []
+  },
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.7.9"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 1
+}

From 4188fb9184cd7f1dd4adfa77a970374919d6bcc9 Mon Sep 17 00:00:00 2001
From: Chanin Nantasenamat <51851491+dataprofessor@users.noreply.github.com>
Date: Thu, 14 Jan 2021 21:50:45 +0700
Subject: [PATCH 03/11] Update
 CDD_ML_Part_4_Acetylcholinesterase_Regression_Random_Forest.ipynb

---
 ...Part_4_Acetylcholinesterase_Regression_Random_Forest.ipynb | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/python/CDD_ML_Part_4_Acetylcholinesterase_Regression_Random_Forest.ipynb b/python/CDD_ML_Part_4_Acetylcholinesterase_Regression_Random_Forest.ipynb
index edd3a3d..4023c21 100644
--- a/python/CDD_ML_Part_4_Acetylcholinesterase_Regression_Random_Forest.ipynb
+++ b/python/CDD_ML_Part_4_Acetylcholinesterase_Regression_Random_Forest.ipynb
@@ -33,7 +33,7 @@
         "colab_type": "text"
       },
       "source": [
-        "# **Bioinformatics Project - Computational Drug Discovery [Part 4] Comparing Classifiers for Building Classification Models**\n",
+        "# **Bioinformatics Project - Computational Drug Discovery [Part 4] Regression Models with Random Forest**\n",
         "\n",
         "Chanin Nantasenamat\n",
         "\n",
@@ -1614,4 +1614,4 @@
       ]
     }
   ]
-}
\ No newline at end of file
+}

From d9bf90748c8aebd6dc89b99c2d37d345dcb0bb1f Mon Sep 17 00:00:00 2001
From: Chanin Nantasenamat <51851491+dataprofessor@users.noreply.github.com>
Date: Sat, 16 Jan 2021 09:12:11 +0700
Subject: [PATCH 04/11] Update crypto-price-app.py

---
 streamlit/part12/crypto-price-app.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/streamlit/part12/crypto-price-app.py b/streamlit/part12/crypto-price-app.py
index 1a10102..3b2f474 100644
--- a/streamlit/part12/crypto-price-app.py
+++ b/streamlit/part12/crypto-price-app.py
@@ -15,7 +15,7 @@
 #---------------------------------#
 # Page layout
 ## Page expands to full width
-st.beta_set_page_config(layout="wide")
+st.set_page_config(layout="wide")
 #---------------------------------#
 # Title
 

From 027e657f961692e685aff038f73122e68dc9ad1c Mon Sep 17 00:00:00 2001
From: Chanin Nantasenamat <51851491+dataprofessor@users.noreply.github.com>
Date: Fri, 22 Jan 2021 22:02:57 +0700
Subject: [PATCH 05/11] Add files via upload

---
 ...tylcholinesterase_Compare_Regressors.ipynb | 1139 +++++++++++++++++
 1 file changed, 1139 insertions(+)
 create mode 100644 python/CDD_ML_Part_5_Acetylcholinesterase_Compare_Regressors.ipynb

diff --git a/python/CDD_ML_Part_5_Acetylcholinesterase_Compare_Regressors.ipynb b/python/CDD_ML_Part_5_Acetylcholinesterase_Compare_Regressors.ipynb
new file mode 100644
index 0000000..773945b
--- /dev/null
+++ b/python/CDD_ML_Part_5_Acetylcholinesterase_Compare_Regressors.ipynb
@@ -0,0 +1,1139 @@
+{
+  "nbformat": 4,
+  "nbformat_minor": 0,
+  "metadata": {
+    "colab": {
+      "name": "CDD_ML_Part_5_Acetylcholinesterase_Compare_Regressors.ipynb",
+      "provenance": [],
+      "collapsed_sections": []
+    },
+    "kernelspec": {
+      "name": "python3",
+      "display_name": "Python 3"
+    }
+  },
+  "cells": [
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "xNq-XQWWYNXh"
+      },
+      "source": [
+        "# **Bioinformatics Project - Computational Drug Discovery [Part 5] Comparing Regressors**\n",
+        "\n",
+        "Chanin Nantasenamat\n",
+        "\n",
+        "['Data Professor' YouTube channel](http://youtube.com/dataprofessor)\n",
+        "\n",
+        "In this Jupyter notebook, we will be building a real-life data science project that you can include in your data science portfolio. Particularly, we will be building a machine learning model using the ChEMBL bioactivity data.\n",
+        "\n",
+        "In Part 5, we will be comparing several ML algorithms for build regression models of acetylcholinesterase inhibitors.\n",
+        "\n"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "OnVZXG7QY1D2"
+      },
+      "source": [
+        "## **1. Import libraries**"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "B4i2iuTlZYvQ",
+        "outputId": "1172a063-ee94-4abe-a8a8-fa0b0ba1073e"
+      },
+      "source": [
+        "! pip install lazypredict"
+      ],
+      "execution_count": 1,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "text": [
+            "Collecting lazypredict\n",
+            "  Downloading https://files.pythonhosted.org/packages/5f/db/1566dca1050ea74e9474dca0f1e7bbffcb0c3e694cf92e7e6e7ef9fca3af/lazypredict-0.2.7-py2.py3-none-any.whl\n",
+            "Requirement already satisfied: Click>=7.0 in /usr/local/lib/python3.6/dist-packages (from lazypredict) (7.1.2)\n",
+            "Installing collected packages: lazypredict\n",
+            "Successfully installed lazypredict-0.2.7\n"
+          ],
+          "name": "stdout"
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "Vf73M_f9XwZ7",
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "outputId": "4256ee85-6e74-4322-fa05-9e79a1779dfd"
+      },
+      "source": [
+        "import pandas as pd\n",
+        "import seaborn as sns\n",
+        "from sklearn.model_selection import train_test_split\n",
+        "import lazypredict\n",
+        "from lazypredict.Supervised import LazyRegressor"
+      ],
+      "execution_count": 2,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "text": [
+            "/usr/local/lib/python3.6/dist-packages/sklearn/utils/deprecation.py:144: FutureWarning: The sklearn.utils.testing module is  deprecated in version 0.22 and will be removed in version 0.24. The corresponding classes / functions should instead be imported from sklearn.utils. Anything that cannot be imported from sklearn.utils is now part of the private API.\n",
+            "  warnings.warn(message, FutureWarning)\n"
+          ],
+          "name": "stderr"
+        }
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "lUGwBVH7Y8Rq"
+      },
+      "source": [
+        "## **2. Load the data set**\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "Oiess4VaZChk",
+        "outputId": "b9956d3a-6631-420c-b7d5-fc69ca407cff"
+      },
+      "source": [
+        "! wget https://github.com/dataprofessor/data/raw/master/acetylcholinesterase_06_bioactivity_data_3class_pIC50_pubchem_fp.csv"
+      ],
+      "execution_count": 3,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "text": [
+            "--2021-01-22 14:57:46--  https://github.com/dataprofessor/data/raw/master/acetylcholinesterase_06_bioactivity_data_3class_pIC50_pubchem_fp.csv\n",
+            "Resolving github.com (github.com)... 192.30.255.112\n",
+            "Connecting to github.com (github.com)|192.30.255.112|:443... connected.\n",
+            "HTTP request sent, awaiting response... 302 Found\n",
+            "Location: https://raw.githubusercontent.com/dataprofessor/data/master/acetylcholinesterase_06_bioactivity_data_3class_pIC50_pubchem_fp.csv [following]\n",
+            "--2021-01-22 14:57:46--  https://raw.githubusercontent.com/dataprofessor/data/master/acetylcholinesterase_06_bioactivity_data_3class_pIC50_pubchem_fp.csv\n",
+            "Resolving raw.githubusercontent.com (raw.githubusercontent.com)... 151.101.0.133, 151.101.64.133, 151.101.128.133, ...\n",
+            "Connecting to raw.githubusercontent.com (raw.githubusercontent.com)|151.101.0.133|:443... connected.\n",
+            "HTTP request sent, awaiting response... 200 OK\n",
+            "Length: 8363909 (8.0M) [text/plain]\n",
+            "Saving to: ‘acetylcholinesterase_06_bioactivity_data_3class_pIC50_pubchem_fp.csv’\n",
+            "\n",
+            "acetylcholinesteras 100%[===================>]   7.98M  46.7MB/s    in 0.2s    \n",
+            "\n",
+            "2021-01-22 14:57:47 (46.7 MB/s) - ‘acetylcholinesterase_06_bioactivity_data_3class_pIC50_pubchem_fp.csv’ saved [8363909/8363909]\n",
+            "\n"
+          ],
+          "name": "stdout"
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "WVojHjyWZC9D"
+      },
+      "source": [
+        "df = pd.read_csv('acetylcholinesterase_06_bioactivity_data_3class_pIC50_pubchem_fp.csv')"
+      ],
+      "execution_count": 4,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "KbTq4zzKZpVf"
+      },
+      "source": [
+        "X = df.drop('pIC50', axis=1)\n",
+        "Y = df.pIC50"
+      ],
+      "execution_count": 5,
+      "outputs": []
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "7Qa6WSGGZ39n"
+      },
+      "source": [
+        "## **3. Data pre-processing**"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "CtC4SWpBaCVQ",
+        "outputId": "1008b65f-5b93-423a-b2bf-0695dc2014ec"
+      },
+      "source": [
+        "# Examine X dimension\n",
+        "X.shape"
+      ],
+      "execution_count": 6,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "(4695, 881)"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 6
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "mVHzT2f5Z8sF",
+        "outputId": "66fc3cdb-2f97-4694-b915-58c95a49b3d2"
+      },
+      "source": [
+        "# Remove low variance features\n",
+        "from sklearn.feature_selection import VarianceThreshold\n",
+        "selection = VarianceThreshold(threshold=(.8 * (1 - .8)))    \n",
+        "X = selection.fit_transform(X)\n",
+        "X.shape"
+      ],
+      "execution_count": 7,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "(4695, 137)"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 7
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "MYck-_XeaHNZ"
+      },
+      "source": [
+        "# Perform data splitting using 80/20 ratio\n",
+        "X_train, X_test, Y_train, Y_test = train_test_split(X, Y, test_size=0.2, random_state=42)"
+      ],
+      "execution_count": 8,
+      "outputs": []
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "zkW9nKohamEj"
+      },
+      "source": [
+        "## **4. Compare ML algorithms**"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "nnFbUjA1aUj1",
+        "outputId": "84de30a4-1459-4506-fefd-d4495c30fbee"
+      },
+      "source": [
+        "# Defines and builds the lazyclassifier\n",
+        "clf = LazyRegressor(verbose=0,ignore_warnings=True, custom_metric=None)\n",
+        "models_train,predictions_train = clf.fit(X_train, X_train, Y_train, Y_train)\n",
+        "models_test,predictions_test = clf.fit(X_train, X_test, Y_train, Y_test)"
+      ],
+      "execution_count": 9,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "text": [
+            " 90%|████████▉ | 35/39 [00:57<00:11,  2.82s/it]"
+          ],
+          "name": "stderr"
+        },
+        {
+          "output_type": "stream",
+          "text": [
+            "[14:58:45] WARNING: /workspace/src/objective/regression_obj.cu:152: reg:linear is now deprecated in favor of reg:squarederror.\n"
+          ],
+          "name": "stdout"
+        },
+        {
+          "output_type": "stream",
+          "text": [
+            "100%|██████████| 39/39 [00:59<00:00,  1.51s/it]\n",
+            " 90%|████████▉ | 35/39 [00:48<00:08,  2.18s/it]"
+          ],
+          "name": "stderr"
+        },
+        {
+          "output_type": "stream",
+          "text": [
+            "[14:59:36] WARNING: /workspace/src/objective/regression_obj.cu:152: reg:linear is now deprecated in favor of reg:squarederror.\n"
+          ],
+          "name": "stdout"
+        },
+        {
+          "output_type": "stream",
+          "text": [
+            "100%|██████████| 39/39 [00:50<00:00,  1.29s/it]\n"
+          ],
+          "name": "stderr"
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 1000
+        },
+        "id": "cHOFkp-ka5tF",
+        "outputId": "7abc08e9-e5b4-44e2-955d-dec0c20b91a1"
+      },
+      "source": [
+        "# Performance table of the training set (80% subset)\n",
+        "predictions_train"
+      ],
+      "execution_count": 10,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/html": [
+              "<div>\n",
+              "<style scoped>\n",
+              "    .dataframe tbody tr th:only-of-type {\n",
+              "        vertical-align: middle;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe tbody tr th {\n",
+              "        vertical-align: top;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe thead th {\n",
+              "        text-align: right;\n",
+              "    }\n",
+              "</style>\n",
+              "<table border=\"1\" class=\"dataframe\">\n",
+              "  <thead>\n",
+              "    <tr style=\"text-align: right;\">\n",
+              "      <th></th>\n",
+              "      <th>R-Squared</th>\n",
+              "      <th>RMSE</th>\n",
+              "      <th>Time Taken</th>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>Model</th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "    </tr>\n",
+              "  </thead>\n",
+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <th>DecisionTreeRegressor</th>\n",
+              "      <td>0.86</td>\n",
+              "      <td>0.57</td>\n",
+              "      <td>0.16</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>ExtraTreeRegressor</th>\n",
+              "      <td>0.86</td>\n",
+              "      <td>0.57</td>\n",
+              "      <td>0.16</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>ExtraTreesRegressor</th>\n",
+              "      <td>0.86</td>\n",
+              "      <td>0.57</td>\n",
+              "      <td>5.93</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>GaussianProcessRegressor</th>\n",
+              "      <td>0.86</td>\n",
+              "      <td>0.57</td>\n",
+              "      <td>5.10</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>RandomForestRegressor</th>\n",
+              "      <td>0.83</td>\n",
+              "      <td>0.64</td>\n",
+              "      <td>4.67</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>BaggingRegressor</th>\n",
+              "      <td>0.81</td>\n",
+              "      <td>0.67</td>\n",
+              "      <td>0.59</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>MLPRegressor</th>\n",
+              "      <td>0.77</td>\n",
+              "      <td>0.75</td>\n",
+              "      <td>6.83</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>HistGradientBoostingRegressor</th>\n",
+              "      <td>0.69</td>\n",
+              "      <td>0.87</td>\n",
+              "      <td>2.55</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>LGBMRegressor</th>\n",
+              "      <td>0.69</td>\n",
+              "      <td>0.87</td>\n",
+              "      <td>0.50</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>KNeighborsRegressor</th>\n",
+              "      <td>0.65</td>\n",
+              "      <td>0.92</td>\n",
+              "      <td>2.98</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>SVR</th>\n",
+              "      <td>0.58</td>\n",
+              "      <td>1.01</td>\n",
+              "      <td>6.45</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>NuSVR</th>\n",
+              "      <td>0.57</td>\n",
+              "      <td>1.02</td>\n",
+              "      <td>4.82</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>GradientBoostingRegressor</th>\n",
+              "      <td>0.46</td>\n",
+              "      <td>1.14</td>\n",
+              "      <td>1.72</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>XGBRegressor</th>\n",
+              "      <td>0.46</td>\n",
+              "      <td>1.14</td>\n",
+              "      <td>1.28</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>Ridge</th>\n",
+              "      <td>0.33</td>\n",
+              "      <td>1.27</td>\n",
+              "      <td>0.05</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>LassoCV</th>\n",
+              "      <td>0.33</td>\n",
+              "      <td>1.27</td>\n",
+              "      <td>3.96</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>ElasticNetCV</th>\n",
+              "      <td>0.33</td>\n",
+              "      <td>1.27</td>\n",
+              "      <td>3.83</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>RidgeCV</th>\n",
+              "      <td>0.33</td>\n",
+              "      <td>1.27</td>\n",
+              "      <td>0.15</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>TransformedTargetRegressor</th>\n",
+              "      <td>0.33</td>\n",
+              "      <td>1.27</td>\n",
+              "      <td>0.07</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>LinearRegression</th>\n",
+              "      <td>0.33</td>\n",
+              "      <td>1.27</td>\n",
+              "      <td>0.09</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>SGDRegressor</th>\n",
+              "      <td>0.32</td>\n",
+              "      <td>1.28</td>\n",
+              "      <td>0.16</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>BayesianRidge</th>\n",
+              "      <td>0.32</td>\n",
+              "      <td>1.28</td>\n",
+              "      <td>0.21</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>HuberRegressor</th>\n",
+              "      <td>0.31</td>\n",
+              "      <td>1.29</td>\n",
+              "      <td>0.61</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>LassoLarsCV</th>\n",
+              "      <td>0.31</td>\n",
+              "      <td>1.29</td>\n",
+              "      <td>0.45</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>LassoLarsIC</th>\n",
+              "      <td>0.31</td>\n",
+              "      <td>1.29</td>\n",
+              "      <td>0.11</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>LinearSVR</th>\n",
+              "      <td>0.30</td>\n",
+              "      <td>1.30</td>\n",
+              "      <td>0.74</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>AdaBoostRegressor</th>\n",
+              "      <td>0.23</td>\n",
+              "      <td>1.36</td>\n",
+              "      <td>1.15</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>Lars</th>\n",
+              "      <td>0.23</td>\n",
+              "      <td>1.36</td>\n",
+              "      <td>0.12</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>OrthogonalMatchingPursuitCV</th>\n",
+              "      <td>0.23</td>\n",
+              "      <td>1.37</td>\n",
+              "      <td>0.15</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>OrthogonalMatchingPursuit</th>\n",
+              "      <td>0.23</td>\n",
+              "      <td>1.37</td>\n",
+              "      <td>0.05</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>LarsCV</th>\n",
+              "      <td>0.15</td>\n",
+              "      <td>1.43</td>\n",
+              "      <td>0.47</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>Lasso</th>\n",
+              "      <td>0.00</td>\n",
+              "      <td>1.55</td>\n",
+              "      <td>0.08</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>ElasticNet</th>\n",
+              "      <td>0.00</td>\n",
+              "      <td>1.55</td>\n",
+              "      <td>0.05</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>DummyRegressor</th>\n",
+              "      <td>0.00</td>\n",
+              "      <td>1.55</td>\n",
+              "      <td>0.03</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>LassoLars</th>\n",
+              "      <td>0.00</td>\n",
+              "      <td>1.55</td>\n",
+              "      <td>0.06</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>PassiveAggressiveRegressor</th>\n",
+              "      <td>-0.13</td>\n",
+              "      <td>1.65</td>\n",
+              "      <td>0.10</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>KernelRidge</th>\n",
+              "      <td>-13.70</td>\n",
+              "      <td>5.95</td>\n",
+              "      <td>1.46</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>RANSACRegressor</th>\n",
+              "      <td>-177394519750505689776128.00</td>\n",
+              "      <td>653870642365.76</td>\n",
+              "      <td>1.11</td>\n",
+              "    </tr>\n",
+              "  </tbody>\n",
+              "</table>\n",
+              "</div>"
+            ],
+            "text/plain": [
+              "                                                 R-Squared  ...  Time Taken\n",
+              "Model                                                       ...            \n",
+              "DecisionTreeRegressor                                 0.86  ...        0.16\n",
+              "ExtraTreeRegressor                                    0.86  ...        0.16\n",
+              "ExtraTreesRegressor                                   0.86  ...        5.93\n",
+              "GaussianProcessRegressor                              0.86  ...        5.10\n",
+              "RandomForestRegressor                                 0.83  ...        4.67\n",
+              "BaggingRegressor                                      0.81  ...        0.59\n",
+              "MLPRegressor                                          0.77  ...        6.83\n",
+              "HistGradientBoostingRegressor                         0.69  ...        2.55\n",
+              "LGBMRegressor                                         0.69  ...        0.50\n",
+              "KNeighborsRegressor                                   0.65  ...        2.98\n",
+              "SVR                                                   0.58  ...        6.45\n",
+              "NuSVR                                                 0.57  ...        4.82\n",
+              "GradientBoostingRegressor                             0.46  ...        1.72\n",
+              "XGBRegressor                                          0.46  ...        1.28\n",
+              "Ridge                                                 0.33  ...        0.05\n",
+              "LassoCV                                               0.33  ...        3.96\n",
+              "ElasticNetCV                                          0.33  ...        3.83\n",
+              "RidgeCV                                               0.33  ...        0.15\n",
+              "TransformedTargetRegressor                            0.33  ...        0.07\n",
+              "LinearRegression                                      0.33  ...        0.09\n",
+              "SGDRegressor                                          0.32  ...        0.16\n",
+              "BayesianRidge                                         0.32  ...        0.21\n",
+              "HuberRegressor                                        0.31  ...        0.61\n",
+              "LassoLarsCV                                           0.31  ...        0.45\n",
+              "LassoLarsIC                                           0.31  ...        0.11\n",
+              "LinearSVR                                             0.30  ...        0.74\n",
+              "AdaBoostRegressor                                     0.23  ...        1.15\n",
+              "Lars                                                  0.23  ...        0.12\n",
+              "OrthogonalMatchingPursuitCV                           0.23  ...        0.15\n",
+              "OrthogonalMatchingPursuit                             0.23  ...        0.05\n",
+              "LarsCV                                                0.15  ...        0.47\n",
+              "Lasso                                                 0.00  ...        0.08\n",
+              "ElasticNet                                            0.00  ...        0.05\n",
+              "DummyRegressor                                        0.00  ...        0.03\n",
+              "LassoLars                                             0.00  ...        0.06\n",
+              "PassiveAggressiveRegressor                           -0.13  ...        0.10\n",
+              "KernelRidge                                         -13.70  ...        1.46\n",
+              "RANSACRegressor               -177394519750505689776128.00  ...        1.11\n",
+              "\n",
+              "[38 rows x 3 columns]"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 10
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 1000
+        },
+        "id": "KP6qT55ebcfd",
+        "outputId": "b25cc626-135a-4c86-8a4b-90f44a63dabe"
+      },
+      "source": [
+        "# Performance table of the test set (20% subset)\n",
+        "predictions_test"
+      ],
+      "execution_count": 11,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/html": [
+              "<div>\n",
+              "<style scoped>\n",
+              "    .dataframe tbody tr th:only-of-type {\n",
+              "        vertical-align: middle;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe tbody tr th {\n",
+              "        vertical-align: top;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe thead th {\n",
+              "        text-align: right;\n",
+              "    }\n",
+              "</style>\n",
+              "<table border=\"1\" class=\"dataframe\">\n",
+              "  <thead>\n",
+              "    <tr style=\"text-align: right;\">\n",
+              "      <th></th>\n",
+              "      <th>R-Squared</th>\n",
+              "      <th>RMSE</th>\n",
+              "      <th>Time Taken</th>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>Model</th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "    </tr>\n",
+              "  </thead>\n",
+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <th>HistGradientBoostingRegressor</th>\n",
+              "      <td>0.54</td>\n",
+              "      <td>1.06</td>\n",
+              "      <td>2.13</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>LGBMRegressor</th>\n",
+              "      <td>0.54</td>\n",
+              "      <td>1.06</td>\n",
+              "      <td>0.46</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>RandomForestRegressor</th>\n",
+              "      <td>0.52</td>\n",
+              "      <td>1.08</td>\n",
+              "      <td>4.56</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>BaggingRegressor</th>\n",
+              "      <td>0.48</td>\n",
+              "      <td>1.12</td>\n",
+              "      <td>0.54</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>NuSVR</th>\n",
+              "      <td>0.48</td>\n",
+              "      <td>1.12</td>\n",
+              "      <td>3.47</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>SVR</th>\n",
+              "      <td>0.48</td>\n",
+              "      <td>1.12</td>\n",
+              "      <td>4.29</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>KNeighborsRegressor</th>\n",
+              "      <td>0.46</td>\n",
+              "      <td>1.14</td>\n",
+              "      <td>0.97</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>MLPRegressor</th>\n",
+              "      <td>0.45</td>\n",
+              "      <td>1.15</td>\n",
+              "      <td>6.73</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>GradientBoostingRegressor</th>\n",
+              "      <td>0.42</td>\n",
+              "      <td>1.18</td>\n",
+              "      <td>1.70</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>XGBRegressor</th>\n",
+              "      <td>0.42</td>\n",
+              "      <td>1.18</td>\n",
+              "      <td>1.17</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>ExtraTreesRegressor</th>\n",
+              "      <td>0.34</td>\n",
+              "      <td>1.26</td>\n",
+              "      <td>5.89</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>Ridge</th>\n",
+              "      <td>0.32</td>\n",
+              "      <td>1.28</td>\n",
+              "      <td>0.04</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>RidgeCV</th>\n",
+              "      <td>0.32</td>\n",
+              "      <td>1.28</td>\n",
+              "      <td>0.13</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>ElasticNetCV</th>\n",
+              "      <td>0.32</td>\n",
+              "      <td>1.28</td>\n",
+              "      <td>3.75</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>LassoCV</th>\n",
+              "      <td>0.32</td>\n",
+              "      <td>1.28</td>\n",
+              "      <td>3.95</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>ExtraTreeRegressor</th>\n",
+              "      <td>0.31</td>\n",
+              "      <td>1.29</td>\n",
+              "      <td>0.12</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>SGDRegressor</th>\n",
+              "      <td>0.31</td>\n",
+              "      <td>1.29</td>\n",
+              "      <td>0.18</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>TransformedTargetRegressor</th>\n",
+              "      <td>0.31</td>\n",
+              "      <td>1.29</td>\n",
+              "      <td>0.07</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>LinearRegression</th>\n",
+              "      <td>0.31</td>\n",
+              "      <td>1.29</td>\n",
+              "      <td>0.08</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>BayesianRidge</th>\n",
+              "      <td>0.31</td>\n",
+              "      <td>1.29</td>\n",
+              "      <td>0.16</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>LassoLarsCV</th>\n",
+              "      <td>0.31</td>\n",
+              "      <td>1.29</td>\n",
+              "      <td>0.45</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>LassoLarsIC</th>\n",
+              "      <td>0.31</td>\n",
+              "      <td>1.29</td>\n",
+              "      <td>0.09</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>HuberRegressor</th>\n",
+              "      <td>0.31</td>\n",
+              "      <td>1.29</td>\n",
+              "      <td>0.61</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>LinearSVR</th>\n",
+              "      <td>0.29</td>\n",
+              "      <td>1.31</td>\n",
+              "      <td>0.73</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>DecisionTreeRegressor</th>\n",
+              "      <td>0.28</td>\n",
+              "      <td>1.31</td>\n",
+              "      <td>0.16</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>OrthogonalMatchingPursuit</th>\n",
+              "      <td>0.24</td>\n",
+              "      <td>1.36</td>\n",
+              "      <td>0.04</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>OrthogonalMatchingPursuitCV</th>\n",
+              "      <td>0.24</td>\n",
+              "      <td>1.36</td>\n",
+              "      <td>0.12</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>Lars</th>\n",
+              "      <td>0.21</td>\n",
+              "      <td>1.38</td>\n",
+              "      <td>0.10</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>AdaBoostRegressor</th>\n",
+              "      <td>0.21</td>\n",
+              "      <td>1.38</td>\n",
+              "      <td>0.77</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>LarsCV</th>\n",
+              "      <td>0.15</td>\n",
+              "      <td>1.43</td>\n",
+              "      <td>0.46</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>Lasso</th>\n",
+              "      <td>-0.00</td>\n",
+              "      <td>1.55</td>\n",
+              "      <td>0.05</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>ElasticNet</th>\n",
+              "      <td>-0.00</td>\n",
+              "      <td>1.55</td>\n",
+              "      <td>0.03</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>DummyRegressor</th>\n",
+              "      <td>-0.00</td>\n",
+              "      <td>1.55</td>\n",
+              "      <td>0.03</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>LassoLars</th>\n",
+              "      <td>-0.00</td>\n",
+              "      <td>1.55</td>\n",
+              "      <td>0.05</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>PassiveAggressiveRegressor</th>\n",
+              "      <td>-0.22</td>\n",
+              "      <td>1.71</td>\n",
+              "      <td>0.09</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>GaussianProcessRegressor</th>\n",
+              "      <td>-4.99</td>\n",
+              "      <td>3.80</td>\n",
+              "      <td>3.88</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>KernelRidge</th>\n",
+              "      <td>-13.82</td>\n",
+              "      <td>5.98</td>\n",
+              "      <td>1.28</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>RANSACRegressor</th>\n",
+              "      <td>-225543784142202044678144.00</td>\n",
+              "      <td>737597884681.01</td>\n",
+              "      <td>1.13</td>\n",
+              "    </tr>\n",
+              "  </tbody>\n",
+              "</table>\n",
+              "</div>"
+            ],
+            "text/plain": [
+              "                                                 R-Squared  ...  Time Taken\n",
+              "Model                                                       ...            \n",
+              "HistGradientBoostingRegressor                         0.54  ...        2.13\n",
+              "LGBMRegressor                                         0.54  ...        0.46\n",
+              "RandomForestRegressor                                 0.52  ...        4.56\n",
+              "BaggingRegressor                                      0.48  ...        0.54\n",
+              "NuSVR                                                 0.48  ...        3.47\n",
+              "SVR                                                   0.48  ...        4.29\n",
+              "KNeighborsRegressor                                   0.46  ...        0.97\n",
+              "MLPRegressor                                          0.45  ...        6.73\n",
+              "GradientBoostingRegressor                             0.42  ...        1.70\n",
+              "XGBRegressor                                          0.42  ...        1.17\n",
+              "ExtraTreesRegressor                                   0.34  ...        5.89\n",
+              "Ridge                                                 0.32  ...        0.04\n",
+              "RidgeCV                                               0.32  ...        0.13\n",
+              "ElasticNetCV                                          0.32  ...        3.75\n",
+              "LassoCV                                               0.32  ...        3.95\n",
+              "ExtraTreeRegressor                                    0.31  ...        0.12\n",
+              "SGDRegressor                                          0.31  ...        0.18\n",
+              "TransformedTargetRegressor                            0.31  ...        0.07\n",
+              "LinearRegression                                      0.31  ...        0.08\n",
+              "BayesianRidge                                         0.31  ...        0.16\n",
+              "LassoLarsCV                                           0.31  ...        0.45\n",
+              "LassoLarsIC                                           0.31  ...        0.09\n",
+              "HuberRegressor                                        0.31  ...        0.61\n",
+              "LinearSVR                                             0.29  ...        0.73\n",
+              "DecisionTreeRegressor                                 0.28  ...        0.16\n",
+              "OrthogonalMatchingPursuit                             0.24  ...        0.04\n",
+              "OrthogonalMatchingPursuitCV                           0.24  ...        0.12\n",
+              "Lars                                                  0.21  ...        0.10\n",
+              "AdaBoostRegressor                                     0.21  ...        0.77\n",
+              "LarsCV                                                0.15  ...        0.46\n",
+              "Lasso                                                -0.00  ...        0.05\n",
+              "ElasticNet                                           -0.00  ...        0.03\n",
+              "DummyRegressor                                       -0.00  ...        0.03\n",
+              "LassoLars                                            -0.00  ...        0.05\n",
+              "PassiveAggressiveRegressor                           -0.22  ...        0.09\n",
+              "GaussianProcessRegressor                             -4.99  ...        3.88\n",
+              "KernelRidge                                         -13.82  ...        1.28\n",
+              "RANSACRegressor               -225543784142202044678144.00  ...        1.13\n",
+              "\n",
+              "[38 rows x 3 columns]"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 11
+        }
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "CM-lcHz6byNz"
+      },
+      "source": [
+        "## **5. Data visualization of model performance**"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 628
+        },
+        "id": "MLsi5uSvbpC7",
+        "outputId": "2cca0f31-9f81-4d37-8ccd-e88d35268272"
+      },
+      "source": [
+        "# Bar plot of R-squared values\n",
+        "import matplotlib.pyplot as plt\n",
+        "import seaborn as sns\n",
+        "\n",
+        "#train[\"R-Squared\"] = [0 if i < 0 else i for i in train.iloc[:,0] ]\n",
+        "\n",
+        "plt.figure(figsize=(5, 10))\n",
+        "sns.set_theme(style=\"whitegrid\")\n",
+        "ax = sns.barplot(y=predictions_train.index, x=\"R-Squared\", data=predictions_train)\n",
+        "ax.set(xlim=(0, 1))"
+      ],
+      "execution_count": 12,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "[(0.0, 1.0)]"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 12
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "image/png": 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\n",
+            "text/plain": [
+              "<Figure size 360x720 with 1 Axes>"
+            ]
+          },
+          "metadata": {
+            "tags": [],
+            "needs_background": "light"
+          }
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 628
+        },
+        "id": "OLkiiTTwb-Cb",
+        "outputId": "6efb0857-c5fe-4bbc-dead-1bfd98a6f5d3"
+      },
+      "source": [
+        "# Bar plot of RMSE values\n",
+        "import matplotlib.pyplot as plt\n",
+        "import seaborn as sns\n",
+        "\n",
+        "plt.figure(figsize=(5, 10))\n",
+        "sns.set_theme(style=\"whitegrid\")\n",
+        "ax = sns.barplot(y=predictions_train.index, x=\"RMSE\", data=predictions_train)\n",
+        "ax.set(xlim=(0, 10))"
+      ],
+      "execution_count": 13,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "[(0.0, 10.0)]"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 13
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "image/png": 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\n",
+            "text/plain": [
+              "<Figure size 360x720 with 1 Axes>"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          }
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 628
+        },
+        "id": "pCdcxpzScqXX",
+        "outputId": "62dbbf7b-d569-4280-ce60-0c191bbd8e2a"
+      },
+      "source": [
+        "# Bar plot of calculation time\n",
+        "import matplotlib.pyplot as plt\n",
+        "import seaborn as sns\n",
+        "\n",
+        "plt.figure(figsize=(5, 10))\n",
+        "sns.set_theme(style=\"whitegrid\")\n",
+        "ax = sns.barplot(y=predictions_train.index, x=\"Time Taken\", data=predictions_train)\n",
+        "ax.set(xlim=(0, 10))"
+      ],
+      "execution_count": 14,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "[(0.0, 10.0)]"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 14
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "image/png": 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\n",
+            "text/plain": [
+              "<Figure size 360x720 with 1 Axes>"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          }
+        }
+      ]
+    }
+  ]
+}
\ No newline at end of file

From 4d1a872f2fb06cdff15dc5fa509e6732dbaf7a51 Mon Sep 17 00:00:00 2001
From: Chanin Nantasenamat <51851491+dataprofessor@users.noreply.github.com>
Date: Tue, 12 Nov 2024 20:18:24 -0800
Subject: [PATCH 06/11] Add files via upload

---
 python/google_colab_first_notebook.ipynb | 983 +++++++++++++++++++++++
 1 file changed, 983 insertions(+)
 create mode 100644 python/google_colab_first_notebook.ipynb

diff --git a/python/google_colab_first_notebook.ipynb b/python/google_colab_first_notebook.ipynb
new file mode 100644
index 0000000..13386f1
--- /dev/null
+++ b/python/google_colab_first_notebook.ipynb
@@ -0,0 +1,983 @@
+{
+  "nbformat": 4,
+  "nbformat_minor": 0,
+  "metadata": {
+    "colab": {
+      "provenance": []
+    },
+    "kernelspec": {
+      "name": "python3",
+      "display_name": "Python 3"
+    },
+    "language_info": {
+      "name": "python"
+    }
+  },
+  "cells": [
+    {
+      "cell_type": "markdown",
+      "source": [
+        "# My First Notebook\n"
+      ],
+      "metadata": {
+        "id": "yWsgD4dxrhSX"
+      }
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "# H1 heading"
+      ],
+      "metadata": {
+        "id": "zRVndNmir2M4"
+      }
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "## H2 heading"
+      ],
+      "metadata": {
+        "id": "ByuA1cDmrqhb"
+      }
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "### H3 heading"
+      ],
+      "metadata": {
+        "id": "HM0mR4v4sAXP"
+      }
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "# Load API key"
+      ],
+      "metadata": {
+        "id": "qC1RLhLKwswk"
+      }
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "from google.colab import userdata\n",
+        "dummy_api_key = userdata.get('DUMMY_KEY')"
+      ],
+      "metadata": {
+        "id": "8idhWq95wgKl"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "# Examples"
+      ],
+      "metadata": {
+        "id": "ECEbeZCFsIh5"
+      }
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "## pandas"
+      ],
+      "metadata": {
+        "id": "RmJPQguLsKip"
+      }
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "import pandas as pd"
+      ],
+      "metadata": {
+        "id": "dw1W26YmroA8"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "df = pd.read_csv('sample_data/california_housing_test.csv')\n",
+        "df.head()"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 206
+        },
+        "id": "wGnYqBtFsPnf",
+        "outputId": "d4142036-ab13-4905-856a-aa8f4ee3d17b"
+      },
+      "execution_count": null,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "   longitude  latitude  housing_median_age  total_rooms  total_bedrooms  \\\n",
+              "0    -122.05     37.37                27.0       3885.0           661.0   \n",
+              "1    -118.30     34.26                43.0       1510.0           310.0   \n",
+              "2    -117.81     33.78                27.0       3589.0           507.0   \n",
+              "3    -118.36     33.82                28.0         67.0            15.0   \n",
+              "4    -119.67     36.33                19.0       1241.0           244.0   \n",
+              "\n",
+              "   population  households  median_income  median_house_value  \n",
+              "0      1537.0       606.0         6.6085            344700.0  \n",
+              "1       809.0       277.0         3.5990            176500.0  \n",
+              "2      1484.0       495.0         5.7934            270500.0  \n",
+              "3        49.0        11.0         6.1359            330000.0  \n",
+              "4       850.0       237.0         2.9375             81700.0  "
+            ],
+            "text/html": [
+              "\n",
+              "  <div id=\"df-38079fa8-4818-4a2e-9fac-8ed19b81bcc7\" class=\"colab-df-container\">\n",
+              "    <div>\n",
+              "<style scoped>\n",
+              "    .dataframe tbody tr th:only-of-type {\n",
+              "        vertical-align: middle;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe tbody tr th {\n",
+              "        vertical-align: top;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe thead th {\n",
+              "        text-align: right;\n",
+              "    }\n",
+              "</style>\n",
+              "<table border=\"1\" class=\"dataframe\">\n",
+              "  <thead>\n",
+              "    <tr style=\"text-align: right;\">\n",
+              "      <th></th>\n",
+              "      <th>longitude</th>\n",
+              "      <th>latitude</th>\n",
+              "      <th>housing_median_age</th>\n",
+              "      <th>total_rooms</th>\n",
+              "      <th>total_bedrooms</th>\n",
+              "      <th>population</th>\n",
+              "      <th>households</th>\n",
+              "      <th>median_income</th>\n",
+              "      <th>median_house_value</th>\n",
+              "    </tr>\n",
+              "  </thead>\n",
+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <th>0</th>\n",
+              "      <td>-122.05</td>\n",
+              "      <td>37.37</td>\n",
+              "      <td>27.0</td>\n",
+              "      <td>3885.0</td>\n",
+              "      <td>661.0</td>\n",
+              "      <td>1537.0</td>\n",
+              "      <td>606.0</td>\n",
+              "      <td>6.6085</td>\n",
+              "      <td>344700.0</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>1</th>\n",
+              "      <td>-118.30</td>\n",
+              "      <td>34.26</td>\n",
+              "      <td>43.0</td>\n",
+              "      <td>1510.0</td>\n",
+              "      <td>310.0</td>\n",
+              "      <td>809.0</td>\n",
+              "      <td>277.0</td>\n",
+              "      <td>3.5990</td>\n",
+              "      <td>176500.0</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2</th>\n",
+              "      <td>-117.81</td>\n",
+              "      <td>33.78</td>\n",
+              "      <td>27.0</td>\n",
+              "      <td>3589.0</td>\n",
+              "      <td>507.0</td>\n",
+              "      <td>1484.0</td>\n",
+              "      <td>495.0</td>\n",
+              "      <td>5.7934</td>\n",
+              "      <td>270500.0</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>3</th>\n",
+              "      <td>-118.36</td>\n",
+              "      <td>33.82</td>\n",
+              "      <td>28.0</td>\n",
+              "      <td>67.0</td>\n",
+              "      <td>15.0</td>\n",
+              "      <td>49.0</td>\n",
+              "      <td>11.0</td>\n",
+              "      <td>6.1359</td>\n",
+              "      <td>330000.0</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>4</th>\n",
+              "      <td>-119.67</td>\n",
+              "      <td>36.33</td>\n",
+              "      <td>19.0</td>\n",
+              "      <td>1241.0</td>\n",
+              "      <td>244.0</td>\n",
+              "      <td>850.0</td>\n",
+              "      <td>237.0</td>\n",
+              "      <td>2.9375</td>\n",
+              "      <td>81700.0</td>\n",
+              "    </tr>\n",
+              "  </tbody>\n",
+              "</table>\n",
+              "</div>\n",
+              "    <div class=\"colab-df-buttons\">\n",
+              "\n",
+              "  <div class=\"colab-df-container\">\n",
+              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-38079fa8-4818-4a2e-9fac-8ed19b81bcc7')\"\n",
+              "            title=\"Convert this dataframe to an interactive table.\"\n",
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+              "  </svg>\n",
+              "    </button>\n",
+              "\n",
+              "  <style>\n",
+              "    .colab-df-container {\n",
+              "      display:flex;\n",
+              "      gap: 12px;\n",
+              "    }\n",
+              "\n",
+              "    .colab-df-convert {\n",
+              "      background-color: #E8F0FE;\n",
+              "      border: none;\n",
+              "      border-radius: 50%;\n",
+              "      cursor: pointer;\n",
+              "      display: none;\n",
+              "      fill: #1967D2;\n",
+              "      height: 32px;\n",
+              "      padding: 0 0 0 0;\n",
+              "      width: 32px;\n",
+              "    }\n",
+              "\n",
+              "    .colab-df-convert:hover {\n",
+              "      background-color: #E2EBFA;\n",
+              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
+              "      fill: #174EA6;\n",
+              "    }\n",
+              "\n",
+              "    .colab-df-buttons div {\n",
+              "      margin-bottom: 4px;\n",
+              "    }\n",
+              "\n",
+              "    [theme=dark] .colab-df-convert {\n",
+              "      background-color: #3B4455;\n",
+              "      fill: #D2E3FC;\n",
+              "    }\n",
+              "\n",
+              "    [theme=dark] .colab-df-convert:hover {\n",
+              "      background-color: #434B5C;\n",
+              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
+              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
+              "      fill: #FFFFFF;\n",
+              "    }\n",
+              "  </style>\n",
+              "\n",
+              "    <script>\n",
+              "      const buttonEl =\n",
+              "        document.querySelector('#df-38079fa8-4818-4a2e-9fac-8ed19b81bcc7 button.colab-df-convert');\n",
+              "      buttonEl.style.display =\n",
+              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
+              "\n",
+              "      async function convertToInteractive(key) {\n",
+              "        const element = document.querySelector('#df-38079fa8-4818-4a2e-9fac-8ed19b81bcc7');\n",
+              "        const dataTable =\n",
+              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
+              "                                                    [key], {});\n",
+              "        if (!dataTable) return;\n",
+              "\n",
+              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
+              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
+              "          + ' to learn more about interactive tables.';\n",
+              "        element.innerHTML = '';\n",
+              "        dataTable['output_type'] = 'display_data';\n",
+              "        await google.colab.output.renderOutput(dataTable, element);\n",
+              "        const docLink = document.createElement('div');\n",
+              "        docLink.innerHTML = docLinkHtml;\n",
+              "        element.appendChild(docLink);\n",
+              "      }\n",
+              "    </script>\n",
+              "  </div>\n",
+              "\n",
+              "\n",
+              "<div id=\"df-86dfe127-37d4-496d-9eb6-7ecaac21241f\">\n",
+              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-86dfe127-37d4-496d-9eb6-7ecaac21241f')\"\n",
+              "            title=\"Suggest charts\"\n",
+              "            style=\"display:none;\">\n",
+              "\n",
+              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
+              "     width=\"24px\">\n",
+              "    <g>\n",
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+              "    </g>\n",
+              "</svg>\n",
+              "  </button>\n",
+              "\n",
+              "<style>\n",
+              "  .colab-df-quickchart {\n",
+              "      --bg-color: #E8F0FE;\n",
+              "      --fill-color: #1967D2;\n",
+              "      --hover-bg-color: #E2EBFA;\n",
+              "      --hover-fill-color: #174EA6;\n",
+              "      --disabled-fill-color: #AAA;\n",
+              "      --disabled-bg-color: #DDD;\n",
+              "  }\n",
+              "\n",
+              "  [theme=dark] .colab-df-quickchart {\n",
+              "      --bg-color: #3B4455;\n",
+              "      --fill-color: #D2E3FC;\n",
+              "      --hover-bg-color: #434B5C;\n",
+              "      --hover-fill-color: #FFFFFF;\n",
+              "      --disabled-bg-color: #3B4455;\n",
+              "      --disabled-fill-color: #666;\n",
+              "  }\n",
+              "\n",
+              "  .colab-df-quickchart {\n",
+              "    background-color: var(--bg-color);\n",
+              "    border: none;\n",
+              "    border-radius: 50%;\n",
+              "    cursor: pointer;\n",
+              "    display: none;\n",
+              "    fill: var(--fill-color);\n",
+              "    height: 32px;\n",
+              "    padding: 0;\n",
+              "    width: 32px;\n",
+              "  }\n",
+              "\n",
+              "  .colab-df-quickchart:hover {\n",
+              "    background-color: var(--hover-bg-color);\n",
+              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
+              "    fill: var(--button-hover-fill-color);\n",
+              "  }\n",
+              "\n",
+              "  .colab-df-quickchart-complete:disabled,\n",
+              "  .colab-df-quickchart-complete:disabled:hover {\n",
+              "    background-color: var(--disabled-bg-color);\n",
+              "    fill: var(--disabled-fill-color);\n",
+              "    box-shadow: none;\n",
+              "  }\n",
+              "\n",
+              "  .colab-df-spinner {\n",
+              "    border: 2px solid var(--fill-color);\n",
+              "    border-color: transparent;\n",
+              "    border-bottom-color: var(--fill-color);\n",
+              "    animation:\n",
+              "      spin 1s steps(1) infinite;\n",
+              "  }\n",
+              "\n",
+              "  @keyframes spin {\n",
+              "    0% {\n",
+              "      border-color: transparent;\n",
+              "      border-bottom-color: var(--fill-color);\n",
+              "      border-left-color: var(--fill-color);\n",
+              "    }\n",
+              "    20% {\n",
+              "      border-color: transparent;\n",
+              "      border-left-color: var(--fill-color);\n",
+              "      border-top-color: var(--fill-color);\n",
+              "    }\n",
+              "    30% {\n",
+              "      border-color: transparent;\n",
+              "      border-left-color: var(--fill-color);\n",
+              "      border-top-color: var(--fill-color);\n",
+              "      border-right-color: var(--fill-color);\n",
+              "    }\n",
+              "    40% {\n",
+              "      border-color: transparent;\n",
+              "      border-right-color: var(--fill-color);\n",
+              "      border-top-color: var(--fill-color);\n",
+              "    }\n",
+              "    60% {\n",
+              "      border-color: transparent;\n",
+              "      border-right-color: var(--fill-color);\n",
+              "    }\n",
+              "    80% {\n",
+              "      border-color: transparent;\n",
+              "      border-right-color: var(--fill-color);\n",
+              "      border-bottom-color: var(--fill-color);\n",
+              "    }\n",
+              "    90% {\n",
+              "      border-color: transparent;\n",
+              "      border-bottom-color: var(--fill-color);\n",
+              "    }\n",
+              "  }\n",
+              "</style>\n",
+              "\n",
+              "  <script>\n",
+              "    async function quickchart(key) {\n",
+              "      const quickchartButtonEl =\n",
+              "        document.querySelector('#' + key + ' button');\n",
+              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
+              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
+              "      try {\n",
+              "        const charts = await google.colab.kernel.invokeFunction(\n",
+              "            'suggestCharts', [key], {});\n",
+              "      } catch (error) {\n",
+              "        console.error('Error during call to suggestCharts:', error);\n",
+              "      }\n",
+              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
+              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
+              "    }\n",
+              "    (() => {\n",
+              "      let quickchartButtonEl =\n",
+              "        document.querySelector('#df-86dfe127-37d4-496d-9eb6-7ecaac21241f button');\n",
+              "      quickchartButtonEl.style.display =\n",
+              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
+              "    })();\n",
+              "  </script>\n",
+              "</div>\n",
+              "\n",
+              "    </div>\n",
+              "  </div>\n"
+            ],
+            "application/vnd.google.colaboratory.intrinsic+json": {
+              "type": "dataframe",
+              "variable_name": "df",
+              "summary": "{\n  \"name\": \"df\",\n  \"rows\": 3000,\n  \"fields\": [\n    {\n      \"column\": \"longitude\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1.9949362939550161,\n        \"min\": -124.18,\n        \"max\": -114.49,\n        \"num_unique_values\": 607,\n        \"samples\": [\n          -121.15,\n          -121.46,\n          -121.02\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"latitude\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 2.1296695233438325,\n        \"min\": 32.56,\n        \"max\": 41.92,\n        \"num_unique_values\": 587,\n        \"samples\": [\n          40.17,\n          33.69,\n          39.61\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"housing_median_age\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 12.555395554955755,\n        \"min\": 1.0,\n        \"max\": 52.0,\n        \"num_unique_values\": 52,\n        \"samples\": [\n          14.0,\n          49.0,\n          7.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"total_rooms\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 2155.59333162558,\n        \"min\": 6.0,\n        \"max\": 30450.0,\n        \"num_unique_values\": 2215,\n        \"samples\": [\n          1961.0,\n          1807.0,\n          680.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"total_bedrooms\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 415.6543681363232,\n        \"min\": 2.0,\n        \"max\": 5419.0,\n        \"num_unique_values\": 1055,\n        \"samples\": [\n          532.0,\n          764.0,\n          2162.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"population\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1030.5430124122422,\n        \"min\": 5.0,\n        \"max\": 11935.0,\n        \"num_unique_values\": 1802,\n        \"samples\": [\n          947.0,\n          1140.0,\n          2019.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"households\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 365.42270980552604,\n        \"min\": 2.0,\n        \"max\": 4930.0,\n        \"num_unique_values\": 1026,\n        \"samples\": [\n          646.0,\n          629.0,\n          504.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"median_income\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1.854511729691481,\n        \"min\": 0.4999,\n        \"max\": 15.0001,\n        \"num_unique_values\": 2578,\n        \"samples\": [\n          1.725,\n          0.7403,\n          2.6964\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"median_house_value\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 113119.68746964433,\n        \"min\": 22500.0,\n        \"max\": 500001.0,\n        \"num_unique_values\": 1784,\n        \"samples\": [\n          71900.0,\n          63000.0,\n          115800.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
+            }
+          },
+          "metadata": {},
+          "execution_count": 5
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "df.shape"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "8YBEQ5ZPtyRu",
+        "outputId": "b23eb485-b7f6-477f-b515-d46fedc41dca"
+      },
+      "execution_count": null,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "(3000, 9)"
+            ]
+          },
+          "metadata": {},
+          "execution_count": 10
+        }
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "## yt-dlp"
+      ],
+      "metadata": {
+        "id": "dthivj-_sn_w"
+      }
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "! apt-get install ffmpeg"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "BKdcB7l-vz_h",
+        "outputId": "16893d68-2951-49d0-96d2-c3653d6a44fb"
+      },
+      "execution_count": null,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "Reading package lists... Done\n",
+            "Building dependency tree... Done\n",
+            "Reading state information... Done\n",
+            "ffmpeg is already the newest version (7:4.4.2-0ubuntu0.22.04.1).\n",
+            "0 upgraded, 0 newly installed, 0 to remove and 49 not upgraded.\n"
+          ]
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "pip install yt-dlp"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "VegGCtSaspMK",
+        "outputId": "06c0b539-dc12-4eda-bb42-8231ebb8ec75"
+      },
+      "execution_count": null,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "Collecting yt-dlp\n",
+            "  Downloading yt_dlp-2024.11.4-py3-none-any.whl.metadata (172 kB)\n",
+            "\u001b[?25l     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m0.0/172.1 kB\u001b[0m \u001b[31m?\u001b[0m eta \u001b[36m-:--:--\u001b[0m\r\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m172.1/172.1 kB\u001b[0m \u001b[31m5.0 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[?25hDownloading yt_dlp-2024.11.4-py3-none-any.whl (3.2 MB)\n",
+            "\u001b[?25l   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m0.0/3.2 MB\u001b[0m \u001b[31m?\u001b[0m eta \u001b[36m-:--:--\u001b[0m\r\u001b[2K   \u001b[91m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[90m╺\u001b[0m\u001b[90m━━━━━━\u001b[0m \u001b[32m2.6/3.2 MB\u001b[0m \u001b[31m69.6 MB/s\u001b[0m eta \u001b[36m0:00:01\u001b[0m\r\u001b[2K   \u001b[91m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[91m╸\u001b[0m \u001b[32m3.2/3.2 MB\u001b[0m \u001b[31m65.8 MB/s\u001b[0m eta \u001b[36m0:00:01\u001b[0m\r\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m3.2/3.2 MB\u001b[0m \u001b[31m33.7 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[?25hInstalling collected packages: yt-dlp\n",
+            "Successfully installed yt-dlp-2024.11.4\n"
+          ]
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "import yt_dlp\n",
+        "\n",
+        "def download_audio(url):\n",
+        "    ydl_opts = {\n",
+        "        'format': 'bestaudio/best',\n",
+        "        'postprocessors': [{\n",
+        "            'key': 'FFmpegExtractAudio',\n",
+        "            'preferredcodec': 'mp3',\n",
+        "            'preferredquality': '192',\n",
+        "        }],\n",
+        "        'outtmpl': '%(title)s.%(ext)s',\n",
+        "        'verbose': True,  # Add this line\n",
+        "    }\n",
+        "\n",
+        "    with yt_dlp.YoutubeDL(ydl_opts) as ydl:\n",
+        "        ydl.download([url])"
+      ],
+      "metadata": {
+        "id": "NYJ03kwms7TY"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "URL = \"https://www.youtube.com/watch?v=UF8uR6Z6KLc\"\n",
+        "download_audio(URL)"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "wMM6oBSks8FZ",
+        "outputId": "d17918c9-7196-4aa4-83f8-1780a0739df7"
+      },
+      "execution_count": null,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stderr",
+          "text": [
+            "[debug] Encodings: locale UTF-8, fs utf-8, pref UTF-8, out UTF-8 (No ANSI), error UTF-8 (No ANSI), screen UTF-8 (No ANSI)\n",
+            "[debug] yt-dlp version stable@2024.11.04 from yt-dlp/yt-dlp [197d0b03b] (pip) API\n",
+            "[debug] params: {'format': 'bestaudio/best', 'postprocessors': [{'key': 'FFmpegExtractAudio', 'preferredcodec': 'mp3', 'preferredquality': '192'}], 'outtmpl': '%(title)s.%(ext)s', 'verbose': True, 'compat_opts': set(), 'http_headers': {'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/91.0.4472.124 Safari/537.36', 'Accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8', 'Accept-Language': 'en-us,en;q=0.5', 'Sec-Fetch-Mode': 'navigate'}}\n",
+            "[debug] Python 3.10.12 (CPython x86_64 64bit) - Linux-6.1.85+-x86_64-with-glibc2.35 (OpenSSL 3.0.2 15 Mar 2022, glibc 2.35)\n",
+            "[debug] exe versions: ffmpeg 4.4.2 (setts), ffprobe 4.4.2\n",
+            "[debug] Optional libraries: certifi-2024.08.30, requests-2.32.3, secretstorage-3.3.1, sqlite3-3.37.2, urllib3-2.2.3\n",
+            "[debug] Proxy map: {'colab_language_server': '/usr/colab/bin/language_service'}\n",
+            "[debug] Request Handlers: urllib, requests\n",
+            "[debug] Loaded 1838 extractors\n"
+          ]
+        },
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "[youtube] Extracting URL: https://www.youtube.com/watch?v=UF8uR6Z6KLc\n",
+            "[youtube] UF8uR6Z6KLc: Downloading webpage\n",
+            "[youtube] UF8uR6Z6KLc: Downloading ios player API JSON\n",
+            "[youtube] UF8uR6Z6KLc: Downloading mweb player API JSON\n",
+            "[youtube] UF8uR6Z6KLc: Downloading player 4e23410d\n"
+          ]
+        },
+        {
+          "output_type": "stream",
+          "name": "stderr",
+          "text": [
+            "[debug] Saving youtube-nsig.4e23410d to cache\n",
+            "[debug] [youtube] Decrypted nsig TODInL2VkpwBeZYW7 => wBKo3X3nM8BmSA\n",
+            "[debug] Loading youtube-nsig.4e23410d from cache\n",
+            "[debug] [youtube] Decrypted nsig vAeQv-NfW6cUtSuNm => 9nN6xXoPuOaU-A\n"
+          ]
+        },
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "[youtube] UF8uR6Z6KLc: Downloading m3u8 information\n"
+          ]
+        },
+        {
+          "output_type": "stream",
+          "name": "stderr",
+          "text": [
+            "[debug] Sort order given by extractor: quality, res, fps, hdr:12, source, vcodec, channels, acodec, lang, proto\n",
+            "[debug] Formats sorted by: hasvid, ie_pref, quality, res, fps, hdr:12(7), source, vcodec, channels, acodec, lang, proto, size, br, asr, vext, aext, hasaud, id\n"
+          ]
+        },
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "[info] UF8uR6Z6KLc: Downloading 1 format(s): 251\n"
+          ]
+        },
+        {
+          "output_type": "stream",
+          "name": "stderr",
+          "text": [
+            "[debug] Invoking http downloader on \"https://rr1---sn-qxo7rn7r.googlevideo.com/videoplayback?expire=1730771008&ei=4CMpZ4XhJpPBsfIP7deLmAo&ip=35.199.188.39&id=o-APTN0lKEb0Qfe0Jq0HNmcfAnPmHCwQ_vTDUQ-grBegFk&itag=251&source=youtube&requiressl=yes&xpc=EgVo2aDSNQ%3D%3D&met=1730749408%2C&mh=-6&mm=31%2C26&mn=sn-qxo7rn7r%2Csn-a5mekndl&ms=au%2Conr&mv=m&mvi=1&pl=20&rms=au%2Cau&vprv=1&svpuc=1&mime=audio%2Fwebm&rqh=1&gir=yes&clen=11436231&dur=904.241&lmt=1727658751589050&mt=1730749051&fvip=3&keepalive=yes&fexp=51312688%2C51326932&c=IOS&txp=4532434&sparams=expire%2Cei%2Cip%2Cid%2Citag%2Csource%2Crequiressl%2Cxpc%2Cvprv%2Csvpuc%2Cmime%2Crqh%2Cgir%2Cclen%2Cdur%2Clmt&sig=AJfQdSswRAIgdyRaqQwBtuq6sm2qQrZRZtYbW8LoccP0YWy2R9hHK70CIE3HXpRHAOJFUukFaZHGV2uQ-Sk6VmPSgZ74DwmAQICb&lsparams=met%2Cmh%2Cmm%2Cmn%2Cms%2Cmv%2Cmvi%2Cpl%2Crms&lsig=ACJ0pHgwRQIhAI2cNPYa2PUX70RTEbQQjQVfq6JLIv8EL0Te68Yfpqn-AiAOWu5_w37ZFpinBi-6Xt70X5Mdhlv6iviwRj7LeGV7Cg%3D%3D\"\n"
+          ]
+        },
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "[download] Destination: Steve Jobs' 2005 Stanford Commencement Address.webm\n",
+            "[download] 100% of   10.91MiB in 00:00:00 at 22.43MiB/s  \n"
+          ]
+        },
+        {
+          "output_type": "stream",
+          "name": "stderr",
+          "text": [
+            "[debug] ffmpeg command line: ffprobe -show_streams 'file:Steve Jobs'\"'\"' 2005 Stanford Commencement Address.webm'\n"
+          ]
+        },
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "[ExtractAudio] Destination: Steve Jobs' 2005 Stanford Commencement Address.mp3\n"
+          ]
+        },
+        {
+          "output_type": "stream",
+          "name": "stderr",
+          "text": [
+            "[debug] ffmpeg command line: ffmpeg -y -loglevel repeat+info -i 'file:Steve Jobs'\"'\"' 2005 Stanford Commencement Address.webm' -vn -acodec libmp3lame -b:a 192.0k -movflags +faststart 'file:Steve Jobs'\"'\"' 2005 Stanford Commencement Address.mp3'\n"
+          ]
+        },
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "Deleting original file Steve Jobs' 2005 Stanford Commencement Address.webm (pass -k to keep)\n"
+          ]
+        }
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "## scikit-learn"
+      ],
+      "metadata": {
+        "id": "gHB4HINduElj"
+      }
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "pip install scikit-learn -U"
+      ],
+      "metadata": {
+        "id": "7A1yCVNlutQ_"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "from sklearn.datasets import make_hastie_10_2\n",
+        "from sklearn.ensemble import GradientBoostingClassifier\n",
+        "\n",
+        "X, y = make_hastie_10_2(random_state=0)\n",
+        "clf = GradientBoostingClassifier(n_estimators=100, learning_rate=1.0,\n",
+        "    max_depth=1, random_state=0).fit(X, y)\n",
+        "clf.feature_importances_"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "KVIBZ62euF87",
+        "outputId": "1bc8f2b9-3eae-48c3-b44a-2b5d89d25e7e"
+      },
+      "execution_count": null,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "array([0.10684213, 0.10461707, 0.11265447, 0.09863589, 0.09469133,\n",
+              "       0.10729306, 0.09163753, 0.09718194, 0.09581415, 0.09063242])"
+            ]
+          },
+          "metadata": {},
+          "execution_count": 11
+        }
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "## altair"
+      ],
+      "metadata": {
+        "id": "YFoTWdpdu_fV"
+      }
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "### Heatmap\n",
+        "\n",
+        "Here's how to create a Heatmap."
+      ],
+      "metadata": {
+        "id": "cAno9XZkvOor"
+      }
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "import altair as alt\n",
+        "import numpy as np\n",
+        "import pandas as pd\n",
+        "\n",
+        "# Compute x^2 + y^2 across a 2D grid\n",
+        "x, y = np.meshgrid(range(-5, 5), range(-5, 5))\n",
+        "z = x ** 2 + y ** 2\n",
+        "\n",
+        "# Convert this grid to columnar data expected by Altair\n",
+        "source = pd.DataFrame({'x': x.ravel(),\n",
+        "                     'y': y.ravel(),\n",
+        "                     'z': z.ravel()})\n",
+        "\n",
+        "alt.Chart(source).mark_rect().encode(\n",
+        "    x='x:O',\n",
+        "    y='y:O',\n",
+        "    color='z:Q'\n",
+        ")"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 262
+        },
+        "id": "7NSe5rKiuG82",
+        "outputId": "c56c460c-5cde-4100-f91e-e1e44ece081f"
+      },
+      "execution_count": null,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/html": [
+              "\n",
+              "<div id=\"altair-viz-5c8c3711123143b0907a7fb329ffbbce\"></div>\n",
+              "<script type=\"text/javascript\">\n",
+              "  var VEGA_DEBUG = (typeof VEGA_DEBUG == \"undefined\") ? {} : VEGA_DEBUG;\n",
+              "  (function(spec, embedOpt){\n",
+              "    let outputDiv = document.currentScript.previousElementSibling;\n",
+              "    if (outputDiv.id !== \"altair-viz-5c8c3711123143b0907a7fb329ffbbce\") {\n",
+              "      outputDiv = document.getElementById(\"altair-viz-5c8c3711123143b0907a7fb329ffbbce\");\n",
+              "    }\n",
+              "    const paths = {\n",
+              "      \"vega\": \"https://cdn.jsdelivr.net/npm//vega@5?noext\",\n",
+              "      \"vega-lib\": \"https://cdn.jsdelivr.net/npm//vega-lib?noext\",\n",
+              "      \"vega-lite\": \"https://cdn.jsdelivr.net/npm//vega-lite@4.17.0?noext\",\n",
+              "      \"vega-embed\": \"https://cdn.jsdelivr.net/npm//vega-embed@6?noext\",\n",
+              "    };\n",
+              "\n",
+              "    function maybeLoadScript(lib, version) {\n",
+              "      var key = `${lib.replace(\"-\", \"\")}_version`;\n",
+              "      return (VEGA_DEBUG[key] == version) ?\n",
+              "        Promise.resolve(paths[lib]) :\n",
+              "        new Promise(function(resolve, reject) {\n",
+              "          var s = document.createElement('script');\n",
+              "          document.getElementsByTagName(\"head\")[0].appendChild(s);\n",
+              "          s.async = true;\n",
+              "          s.onload = () => {\n",
+              "            VEGA_DEBUG[key] = version;\n",
+              "            return resolve(paths[lib]);\n",
+              "          };\n",
+              "          s.onerror = () => reject(`Error loading script: ${paths[lib]}`);\n",
+              "          s.src = paths[lib];\n",
+              "        });\n",
+              "    }\n",
+              "\n",
+              "    function showError(err) {\n",
+              "      outputDiv.innerHTML = `<div class=\"error\" style=\"color:red;\">${err}</div>`;\n",
+              "      throw err;\n",
+              "    }\n",
+              "\n",
+              "    function displayChart(vegaEmbed) {\n",
+              "      vegaEmbed(outputDiv, spec, embedOpt)\n",
+              "        .catch(err => showError(`Javascript Error: ${err.message}<br>This usually means there's a typo in your chart specification. See the javascript console for the full traceback.`));\n",
+              "    }\n",
+              "\n",
+              "    if(typeof define === \"function\" && define.amd) {\n",
+              "      requirejs.config({paths});\n",
+              "      require([\"vega-embed\"], displayChart, err => showError(`Error loading script: ${err.message}`));\n",
+              "    } else {\n",
+              "      maybeLoadScript(\"vega\", \"5\")\n",
+              "        .then(() => maybeLoadScript(\"vega-lite\", \"4.17.0\"))\n",
+              "        .then(() => maybeLoadScript(\"vega-embed\", \"6\"))\n",
+              "        .catch(showError)\n",
+              "        .then(() => displayChart(vegaEmbed));\n",
+              "    }\n",
+              "  })({\"config\": {\"view\": {\"continuousWidth\": 400, \"continuousHeight\": 300}}, \"data\": {\"name\": \"data-1487c93b91dee61ec4c167e470e512f4\"}, \"mark\": \"rect\", \"encoding\": {\"color\": {\"field\": \"z\", \"type\": \"quantitative\"}, \"x\": {\"field\": \"x\", \"type\": \"ordinal\"}, \"y\": {\"field\": \"y\", \"type\": \"ordinal\"}}, \"$schema\": \"https://vega.github.io/schema/vega-lite/v4.17.0.json\", \"datasets\": {\"data-1487c93b91dee61ec4c167e470e512f4\": [{\"x\": -5, \"y\": -5, \"z\": 50}, {\"x\": -4, \"y\": -5, \"z\": 41}, {\"x\": -3, \"y\": -5, \"z\": 34}, {\"x\": -2, \"y\": -5, \"z\": 29}, {\"x\": -1, \"y\": -5, \"z\": 26}, {\"x\": 0, \"y\": -5, \"z\": 25}, {\"x\": 1, \"y\": -5, \"z\": 26}, {\"x\": 2, \"y\": -5, \"z\": 29}, {\"x\": 3, \"y\": -5, \"z\": 34}, {\"x\": 4, \"y\": -5, \"z\": 41}, {\"x\": -5, \"y\": -4, \"z\": 41}, {\"x\": -4, \"y\": -4, \"z\": 32}, {\"x\": -3, \"y\": -4, \"z\": 25}, {\"x\": -2, \"y\": -4, \"z\": 20}, {\"x\": -1, \"y\": -4, \"z\": 17}, {\"x\": 0, \"y\": -4, \"z\": 16}, {\"x\": 1, \"y\": -4, \"z\": 17}, {\"x\": 2, \"y\": -4, \"z\": 20}, {\"x\": 3, \"y\": -4, \"z\": 25}, {\"x\": 4, \"y\": -4, \"z\": 32}, {\"x\": -5, \"y\": -3, \"z\": 34}, {\"x\": -4, \"y\": -3, \"z\": 25}, {\"x\": -3, \"y\": -3, \"z\": 18}, {\"x\": -2, \"y\": -3, \"z\": 13}, {\"x\": -1, \"y\": -3, \"z\": 10}, {\"x\": 0, \"y\": -3, \"z\": 9}, {\"x\": 1, \"y\": -3, \"z\": 10}, {\"x\": 2, \"y\": -3, \"z\": 13}, {\"x\": 3, \"y\": -3, \"z\": 18}, {\"x\": 4, \"y\": -3, \"z\": 25}, {\"x\": -5, \"y\": -2, \"z\": 29}, {\"x\": -4, \"y\": -2, \"z\": 20}, {\"x\": -3, \"y\": -2, \"z\": 13}, {\"x\": -2, \"y\": -2, \"z\": 8}, {\"x\": -1, \"y\": -2, \"z\": 5}, {\"x\": 0, \"y\": -2, \"z\": 4}, {\"x\": 1, \"y\": -2, \"z\": 5}, {\"x\": 2, \"y\": -2, \"z\": 8}, {\"x\": 3, \"y\": -2, \"z\": 13}, {\"x\": 4, \"y\": -2, \"z\": 20}, {\"x\": -5, \"y\": -1, \"z\": 26}, {\"x\": -4, \"y\": -1, \"z\": 17}, {\"x\": -3, \"y\": -1, \"z\": 10}, {\"x\": -2, \"y\": -1, \"z\": 5}, {\"x\": -1, \"y\": -1, \"z\": 2}, {\"x\": 0, \"y\": -1, \"z\": 1}, {\"x\": 1, \"y\": -1, \"z\": 2}, {\"x\": 2, \"y\": -1, \"z\": 5}, {\"x\": 3, \"y\": -1, \"z\": 10}, {\"x\": 4, \"y\": -1, \"z\": 17}, {\"x\": -5, \"y\": 0, \"z\": 25}, {\"x\": -4, \"y\": 0, \"z\": 16}, {\"x\": -3, \"y\": 0, \"z\": 9}, {\"x\": -2, \"y\": 0, \"z\": 4}, {\"x\": -1, \"y\": 0, \"z\": 1}, {\"x\": 0, \"y\": 0, \"z\": 0}, {\"x\": 1, \"y\": 0, \"z\": 1}, {\"x\": 2, \"y\": 0, \"z\": 4}, {\"x\": 3, \"y\": 0, \"z\": 9}, {\"x\": 4, \"y\": 0, \"z\": 16}, {\"x\": -5, \"y\": 1, \"z\": 26}, {\"x\": -4, \"y\": 1, \"z\": 17}, {\"x\": -3, \"y\": 1, \"z\": 10}, {\"x\": -2, \"y\": 1, \"z\": 5}, {\"x\": -1, \"y\": 1, \"z\": 2}, {\"x\": 0, \"y\": 1, \"z\": 1}, {\"x\": 1, \"y\": 1, \"z\": 2}, {\"x\": 2, \"y\": 1, \"z\": 5}, {\"x\": 3, \"y\": 1, \"z\": 10}, {\"x\": 4, \"y\": 1, \"z\": 17}, {\"x\": -5, \"y\": 2, \"z\": 29}, {\"x\": -4, \"y\": 2, \"z\": 20}, {\"x\": -3, \"y\": 2, \"z\": 13}, {\"x\": -2, \"y\": 2, \"z\": 8}, {\"x\": -1, \"y\": 2, \"z\": 5}, {\"x\": 0, \"y\": 2, \"z\": 4}, {\"x\": 1, \"y\": 2, \"z\": 5}, {\"x\": 2, \"y\": 2, \"z\": 8}, {\"x\": 3, \"y\": 2, \"z\": 13}, {\"x\": 4, \"y\": 2, \"z\": 20}, {\"x\": -5, \"y\": 3, \"z\": 34}, {\"x\": -4, \"y\": 3, \"z\": 25}, {\"x\": -3, \"y\": 3, \"z\": 18}, {\"x\": -2, \"y\": 3, \"z\": 13}, {\"x\": -1, \"y\": 3, \"z\": 10}, {\"x\": 0, \"y\": 3, \"z\": 9}, {\"x\": 1, \"y\": 3, \"z\": 10}, {\"x\": 2, \"y\": 3, \"z\": 13}, {\"x\": 3, \"y\": 3, \"z\": 18}, {\"x\": 4, \"y\": 3, \"z\": 25}, {\"x\": -5, \"y\": 4, \"z\": 41}, {\"x\": -4, \"y\": 4, \"z\": 32}, {\"x\": -3, \"y\": 4, \"z\": 25}, {\"x\": -2, \"y\": 4, \"z\": 20}, {\"x\": -1, \"y\": 4, \"z\": 17}, {\"x\": 0, \"y\": 4, \"z\": 16}, {\"x\": 1, \"y\": 4, \"z\": 17}, {\"x\": 2, \"y\": 4, \"z\": 20}, {\"x\": 3, \"y\": 4, \"z\": 25}, {\"x\": 4, \"y\": 4, \"z\": 32}]}}, {\"mode\": \"vega-lite\"});\n",
+              "</script>"
+            ],
+            "text/plain": [
+              "alt.Chart(...)"
+            ]
+          },
+          "metadata": {},
+          "execution_count": 12
+        }
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "### Stacked Area Chart"
+      ],
+      "metadata": {
+        "id": "1sGwP2h9vaKw"
+      }
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "import altair as alt\n",
+        "from vega_datasets import data\n",
+        "\n",
+        "source = data.iowa_electricity()\n",
+        "\n",
+        "alt.Chart(source).mark_area().encode(\n",
+        "    x=\"year:T\",\n",
+        "    y=\"net_generation:Q\",\n",
+        "    color=\"source:N\"\n",
+        ")"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 424
+        },
+        "id": "vDQc_4kLvH8l",
+        "outputId": "0c72c68a-d72e-4564-afe6-253793faf7a8"
+      },
+      "execution_count": null,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stderr",
+          "text": [
+            "/usr/local/lib/python3.10/dist-packages/altair/utils/core.py:384: FutureWarning: the convert_dtype parameter is deprecated and will be removed in a future version.  Do ``ser.astype(object).apply()`` instead if you want ``convert_dtype=False``.\n",
+            "  col = df[col_name].apply(to_list_if_array, convert_dtype=False)\n"
+          ]
+        },
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/html": [
+              "\n",
+              "<div id=\"altair-viz-b095170935ce4f0fbd49be2a5b595470\"></div>\n",
+              "<script type=\"text/javascript\">\n",
+              "  var VEGA_DEBUG = (typeof VEGA_DEBUG == \"undefined\") ? {} : VEGA_DEBUG;\n",
+              "  (function(spec, embedOpt){\n",
+              "    let outputDiv = document.currentScript.previousElementSibling;\n",
+              "    if (outputDiv.id !== \"altair-viz-b095170935ce4f0fbd49be2a5b595470\") {\n",
+              "      outputDiv = document.getElementById(\"altair-viz-b095170935ce4f0fbd49be2a5b595470\");\n",
+              "    }\n",
+              "    const paths = {\n",
+              "      \"vega\": \"https://cdn.jsdelivr.net/npm//vega@5?noext\",\n",
+              "      \"vega-lib\": \"https://cdn.jsdelivr.net/npm//vega-lib?noext\",\n",
+              "      \"vega-lite\": \"https://cdn.jsdelivr.net/npm//vega-lite@4.17.0?noext\",\n",
+              "      \"vega-embed\": \"https://cdn.jsdelivr.net/npm//vega-embed@6?noext\",\n",
+              "    };\n",
+              "\n",
+              "    function maybeLoadScript(lib, version) {\n",
+              "      var key = `${lib.replace(\"-\", \"\")}_version`;\n",
+              "      return (VEGA_DEBUG[key] == version) ?\n",
+              "        Promise.resolve(paths[lib]) :\n",
+              "        new Promise(function(resolve, reject) {\n",
+              "          var s = document.createElement('script');\n",
+              "          document.getElementsByTagName(\"head\")[0].appendChild(s);\n",
+              "          s.async = true;\n",
+              "          s.onload = () => {\n",
+              "            VEGA_DEBUG[key] = version;\n",
+              "            return resolve(paths[lib]);\n",
+              "          };\n",
+              "          s.onerror = () => reject(`Error loading script: ${paths[lib]}`);\n",
+              "          s.src = paths[lib];\n",
+              "        });\n",
+              "    }\n",
+              "\n",
+              "    function showError(err) {\n",
+              "      outputDiv.innerHTML = `<div class=\"error\" style=\"color:red;\">${err}</div>`;\n",
+              "      throw err;\n",
+              "    }\n",
+              "\n",
+              "    function displayChart(vegaEmbed) {\n",
+              "      vegaEmbed(outputDiv, spec, embedOpt)\n",
+              "        .catch(err => showError(`Javascript Error: ${err.message}<br>This usually means there's a typo in your chart specification. See the javascript console for the full traceback.`));\n",
+              "    }\n",
+              "\n",
+              "    if(typeof define === \"function\" && define.amd) {\n",
+              "      requirejs.config({paths});\n",
+              "      require([\"vega-embed\"], displayChart, err => showError(`Error loading script: ${err.message}`));\n",
+              "    } else {\n",
+              "      maybeLoadScript(\"vega\", \"5\")\n",
+              "        .then(() => maybeLoadScript(\"vega-lite\", \"4.17.0\"))\n",
+              "        .then(() => maybeLoadScript(\"vega-embed\", \"6\"))\n",
+              "        .catch(showError)\n",
+              "        .then(() => displayChart(vegaEmbed));\n",
+              "    }\n",
+              "  })({\"config\": {\"view\": {\"continuousWidth\": 400, \"continuousHeight\": 300}}, \"data\": {\"name\": \"data-bb61008ba0c766c5601afa5323d12ad4\"}, \"mark\": \"area\", \"encoding\": {\"color\": {\"field\": \"source\", \"type\": \"nominal\"}, \"x\": {\"field\": \"year\", \"type\": \"temporal\"}, \"y\": {\"field\": \"net_generation\", \"type\": \"quantitative\"}}, \"$schema\": \"https://vega.github.io/schema/vega-lite/v4.17.0.json\", \"datasets\": {\"data-bb61008ba0c766c5601afa5323d12ad4\": [{\"year\": \"2001-01-01T00:00:00\", \"source\": \"Fossil Fuels\", \"net_generation\": 35361}, {\"year\": \"2002-01-01T00:00:00\", \"source\": \"Fossil Fuels\", \"net_generation\": 35991}, {\"year\": \"2003-01-01T00:00:00\", \"source\": \"Fossil Fuels\", \"net_generation\": 36234}, {\"year\": \"2004-01-01T00:00:00\", \"source\": \"Fossil Fuels\", \"net_generation\": 36205}, {\"year\": \"2005-01-01T00:00:00\", \"source\": \"Fossil Fuels\", \"net_generation\": 36883}, {\"year\": \"2006-01-01T00:00:00\", \"source\": \"Fossil Fuels\", \"net_generation\": 37014}, {\"year\": \"2007-01-01T00:00:00\", \"source\": \"Fossil Fuels\", \"net_generation\": 41389}, {\"year\": \"2008-01-01T00:00:00\", \"source\": \"Fossil Fuels\", \"net_generation\": 42734}, {\"year\": \"2009-01-01T00:00:00\", \"source\": \"Fossil Fuels\", \"net_generation\": 38620}, {\"year\": \"2010-01-01T00:00:00\", \"source\": \"Fossil Fuels\", \"net_generation\": 42750}, {\"year\": \"2011-01-01T00:00:00\", \"source\": \"Fossil Fuels\", \"net_generation\": 39361}, {\"year\": \"2012-01-01T00:00:00\", \"source\": \"Fossil Fuels\", \"net_generation\": 37379}, {\"year\": \"2013-01-01T00:00:00\", \"source\": \"Fossil Fuels\", \"net_generation\": 34873}, {\"year\": \"2014-01-01T00:00:00\", \"source\": \"Fossil Fuels\", \"net_generation\": 35250}, {\"year\": \"2015-01-01T00:00:00\", \"source\": \"Fossil Fuels\", \"net_generation\": 32319}, {\"year\": \"2016-01-01T00:00:00\", \"source\": \"Fossil Fuels\", \"net_generation\": 28437}, {\"year\": \"2017-01-01T00:00:00\", \"source\": \"Fossil Fuels\", \"net_generation\": 29329}, {\"year\": \"2001-01-01T00:00:00\", \"source\": \"Nuclear Energy\", \"net_generation\": 3853}, {\"year\": \"2002-01-01T00:00:00\", \"source\": \"Nuclear Energy\", \"net_generation\": 4574}, {\"year\": \"2003-01-01T00:00:00\", \"source\": \"Nuclear Energy\", \"net_generation\": 3988}, {\"year\": \"2004-01-01T00:00:00\", \"source\": \"Nuclear Energy\", \"net_generation\": 4929}, {\"year\": \"2005-01-01T00:00:00\", \"source\": \"Nuclear Energy\", \"net_generation\": 4538}, {\"year\": \"2006-01-01T00:00:00\", \"source\": \"Nuclear Energy\", \"net_generation\": 5095}, {\"year\": \"2007-01-01T00:00:00\", \"source\": \"Nuclear Energy\", \"net_generation\": 4519}, {\"year\": \"2008-01-01T00:00:00\", \"source\": \"Nuclear Energy\", \"net_generation\": 5282}, {\"year\": \"2009-01-01T00:00:00\", \"source\": \"Nuclear Energy\", \"net_generation\": 4679}, {\"year\": \"2010-01-01T00:00:00\", \"source\": \"Nuclear Energy\", \"net_generation\": 4451}, {\"year\": \"2011-01-01T00:00:00\", \"source\": \"Nuclear Energy\", \"net_generation\": 5215}, {\"year\": \"2012-01-01T00:00:00\", \"source\": \"Nuclear Energy\", \"net_generation\": 4347}, {\"year\": \"2013-01-01T00:00:00\", \"source\": \"Nuclear Energy\", \"net_generation\": 5321}, {\"year\": \"2014-01-01T00:00:00\", \"source\": \"Nuclear Energy\", \"net_generation\": 4152}, {\"year\": \"2015-01-01T00:00:00\", \"source\": \"Nuclear Energy\", \"net_generation\": 5243}, {\"year\": \"2016-01-01T00:00:00\", \"source\": \"Nuclear Energy\", \"net_generation\": 4703}, {\"year\": \"2017-01-01T00:00:00\", \"source\": \"Nuclear Energy\", \"net_generation\": 5214}, {\"year\": \"2001-01-01T00:00:00\", \"source\": \"Renewables\", \"net_generation\": 1437}, {\"year\": \"2002-01-01T00:00:00\", \"source\": \"Renewables\", \"net_generation\": 1963}, {\"year\": \"2003-01-01T00:00:00\", \"source\": \"Renewables\", \"net_generation\": 1885}, {\"year\": \"2004-01-01T00:00:00\", \"source\": \"Renewables\", \"net_generation\": 2102}, {\"year\": \"2005-01-01T00:00:00\", \"source\": \"Renewables\", \"net_generation\": 2724}, {\"year\": \"2006-01-01T00:00:00\", \"source\": \"Renewables\", \"net_generation\": 3364}, {\"year\": \"2007-01-01T00:00:00\", \"source\": \"Renewables\", \"net_generation\": 3870}, {\"year\": \"2008-01-01T00:00:00\", \"source\": \"Renewables\", \"net_generation\": 5070}, {\"year\": \"2009-01-01T00:00:00\", \"source\": \"Renewables\", \"net_generation\": 8560}, {\"year\": \"2010-01-01T00:00:00\", \"source\": \"Renewables\", \"net_generation\": 10308}, {\"year\": \"2011-01-01T00:00:00\", \"source\": \"Renewables\", \"net_generation\": 11795}, {\"year\": \"2012-01-01T00:00:00\", \"source\": \"Renewables\", \"net_generation\": 14949}, {\"year\": \"2013-01-01T00:00:00\", \"source\": \"Renewables\", \"net_generation\": 16476}, {\"year\": \"2014-01-01T00:00:00\", \"source\": \"Renewables\", \"net_generation\": 17452}, {\"year\": \"2015-01-01T00:00:00\", \"source\": \"Renewables\", \"net_generation\": 19091}, {\"year\": \"2016-01-01T00:00:00\", \"source\": \"Renewables\", \"net_generation\": 21241}, {\"year\": \"2017-01-01T00:00:00\", \"source\": \"Renewables\", \"net_generation\": 21933}]}}, {\"mode\": \"vega-lite\"});\n",
+              "</script>"
+            ],
+            "text/plain": [
+              "alt.Chart(...)"
+            ]
+          },
+          "metadata": {},
+          "execution_count": 13
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [],
+      "metadata": {
+        "id": "xZ2fN6SLvMYe"
+      },
+      "execution_count": null,
+      "outputs": []
+    }
+  ]
+}
\ No newline at end of file

From d494f8093073990fcf77061bd740a0e4c2d40020 Mon Sep 17 00:00:00 2001
From: Chanin Nantasenamat <51851491+dataprofessor@users.noreply.github.com>
Date: Tue, 12 Nov 2024 20:19:44 -0800
Subject: [PATCH 07/11] Delete python/google_colab_first_notebook.ipynb

---
 python/google_colab_first_notebook.ipynb | 983 -----------------------
 1 file changed, 983 deletions(-)
 delete mode 100644 python/google_colab_first_notebook.ipynb

diff --git a/python/google_colab_first_notebook.ipynb b/python/google_colab_first_notebook.ipynb
deleted file mode 100644
index 13386f1..0000000
--- a/python/google_colab_first_notebook.ipynb
+++ /dev/null
@@ -1,983 +0,0 @@
-{
-  "nbformat": 4,
-  "nbformat_minor": 0,
-  "metadata": {
-    "colab": {
-      "provenance": []
-    },
-    "kernelspec": {
-      "name": "python3",
-      "display_name": "Python 3"
-    },
-    "language_info": {
-      "name": "python"
-    }
-  },
-  "cells": [
-    {
-      "cell_type": "markdown",
-      "source": [
-        "# My First Notebook\n"
-      ],
-      "metadata": {
-        "id": "yWsgD4dxrhSX"
-      }
-    },
-    {
-      "cell_type": "markdown",
-      "source": [
-        "# H1 heading"
-      ],
-      "metadata": {
-        "id": "zRVndNmir2M4"
-      }
-    },
-    {
-      "cell_type": "markdown",
-      "source": [
-        "## H2 heading"
-      ],
-      "metadata": {
-        "id": "ByuA1cDmrqhb"
-      }
-    },
-    {
-      "cell_type": "markdown",
-      "source": [
-        "### H3 heading"
-      ],
-      "metadata": {
-        "id": "HM0mR4v4sAXP"
-      }
-    },
-    {
-      "cell_type": "markdown",
-      "source": [
-        "# Load API key"
-      ],
-      "metadata": {
-        "id": "qC1RLhLKwswk"
-      }
-    },
-    {
-      "cell_type": "code",
-      "source": [
-        "from google.colab import userdata\n",
-        "dummy_api_key = userdata.get('DUMMY_KEY')"
-      ],
-      "metadata": {
-        "id": "8idhWq95wgKl"
-      },
-      "execution_count": null,
-      "outputs": []
-    },
-    {
-      "cell_type": "markdown",
-      "source": [
-        "# Examples"
-      ],
-      "metadata": {
-        "id": "ECEbeZCFsIh5"
-      }
-    },
-    {
-      "cell_type": "markdown",
-      "source": [
-        "## pandas"
-      ],
-      "metadata": {
-        "id": "RmJPQguLsKip"
-      }
-    },
-    {
-      "cell_type": "code",
-      "source": [
-        "import pandas as pd"
-      ],
-      "metadata": {
-        "id": "dw1W26YmroA8"
-      },
-      "execution_count": null,
-      "outputs": []
-    },
-    {
-      "cell_type": "code",
-      "source": [
-        "df = pd.read_csv('sample_data/california_housing_test.csv')\n",
-        "df.head()"
-      ],
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 206
-        },
-        "id": "wGnYqBtFsPnf",
-        "outputId": "d4142036-ab13-4905-856a-aa8f4ee3d17b"
-      },
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "execute_result",
-          "data": {
-            "text/plain": [
-              "   longitude  latitude  housing_median_age  total_rooms  total_bedrooms  \\\n",
-              "0    -122.05     37.37                27.0       3885.0           661.0   \n",
-              "1    -118.30     34.26                43.0       1510.0           310.0   \n",
-              "2    -117.81     33.78                27.0       3589.0           507.0   \n",
-              "3    -118.36     33.82                28.0         67.0            15.0   \n",
-              "4    -119.67     36.33                19.0       1241.0           244.0   \n",
-              "\n",
-              "   population  households  median_income  median_house_value  \n",
-              "0      1537.0       606.0         6.6085            344700.0  \n",
-              "1       809.0       277.0         3.5990            176500.0  \n",
-              "2      1484.0       495.0         5.7934            270500.0  \n",
-              "3        49.0        11.0         6.1359            330000.0  \n",
-              "4       850.0       237.0         2.9375             81700.0  "
-            ],
-            "text/html": [
-              "\n",
-              "  <div id=\"df-38079fa8-4818-4a2e-9fac-8ed19b81bcc7\" class=\"colab-df-container\">\n",
-              "    <div>\n",
-              "<style scoped>\n",
-              "    .dataframe tbody tr th:only-of-type {\n",
-              "        vertical-align: middle;\n",
-              "    }\n",
-              "\n",
-              "    .dataframe tbody tr th {\n",
-              "        vertical-align: top;\n",
-              "    }\n",
-              "\n",
-              "    .dataframe thead th {\n",
-              "        text-align: right;\n",
-              "    }\n",
-              "</style>\n",
-              "<table border=\"1\" class=\"dataframe\">\n",
-              "  <thead>\n",
-              "    <tr style=\"text-align: right;\">\n",
-              "      <th></th>\n",
-              "      <th>longitude</th>\n",
-              "      <th>latitude</th>\n",
-              "      <th>housing_median_age</th>\n",
-              "      <th>total_rooms</th>\n",
-              "      <th>total_bedrooms</th>\n",
-              "      <th>population</th>\n",
-              "      <th>households</th>\n",
-              "      <th>median_income</th>\n",
-              "      <th>median_house_value</th>\n",
-              "    </tr>\n",
-              "  </thead>\n",
-              "  <tbody>\n",
-              "    <tr>\n",
-              "      <th>0</th>\n",
-              "      <td>-122.05</td>\n",
-              "      <td>37.37</td>\n",
-              "      <td>27.0</td>\n",
-              "      <td>3885.0</td>\n",
-              "      <td>661.0</td>\n",
-              "      <td>1537.0</td>\n",
-              "      <td>606.0</td>\n",
-              "      <td>6.6085</td>\n",
-              "      <td>344700.0</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>1</th>\n",
-              "      <td>-118.30</td>\n",
-              "      <td>34.26</td>\n",
-              "      <td>43.0</td>\n",
-              "      <td>1510.0</td>\n",
-              "      <td>310.0</td>\n",
-              "      <td>809.0</td>\n",
-              "      <td>277.0</td>\n",
-              "      <td>3.5990</td>\n",
-              "      <td>176500.0</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>2</th>\n",
-              "      <td>-117.81</td>\n",
-              "      <td>33.78</td>\n",
-              "      <td>27.0</td>\n",
-              "      <td>3589.0</td>\n",
-              "      <td>507.0</td>\n",
-              "      <td>1484.0</td>\n",
-              "      <td>495.0</td>\n",
-              "      <td>5.7934</td>\n",
-              "      <td>270500.0</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>3</th>\n",
-              "      <td>-118.36</td>\n",
-              "      <td>33.82</td>\n",
-              "      <td>28.0</td>\n",
-              "      <td>67.0</td>\n",
-              "      <td>15.0</td>\n",
-              "      <td>49.0</td>\n",
-              "      <td>11.0</td>\n",
-              "      <td>6.1359</td>\n",
-              "      <td>330000.0</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>4</th>\n",
-              "      <td>-119.67</td>\n",
-              "      <td>36.33</td>\n",
-              "      <td>19.0</td>\n",
-              "      <td>1241.0</td>\n",
-              "      <td>244.0</td>\n",
-              "      <td>850.0</td>\n",
-              "      <td>237.0</td>\n",
-              "      <td>2.9375</td>\n",
-              "      <td>81700.0</td>\n",
-              "    </tr>\n",
-              "  </tbody>\n",
-              "</table>\n",
-              "</div>\n",
-              "    <div class=\"colab-df-buttons\">\n",
-              "\n",
-              "  <div class=\"colab-df-container\">\n",
-              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-38079fa8-4818-4a2e-9fac-8ed19b81bcc7')\"\n",
-              "            title=\"Convert this dataframe to an interactive table.\"\n",
-              "            style=\"display:none;\">\n",
-              "\n",
-              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
-              "    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
-              "  </svg>\n",
-              "    </button>\n",
-              "\n",
-              "  <style>\n",
-              "    .colab-df-container {\n",
-              "      display:flex;\n",
-              "      gap: 12px;\n",
-              "    }\n",
-              "\n",
-              "    .colab-df-convert {\n",
-              "      background-color: #E8F0FE;\n",
-              "      border: none;\n",
-              "      border-radius: 50%;\n",
-              "      cursor: pointer;\n",
-              "      display: none;\n",
-              "      fill: #1967D2;\n",
-              "      height: 32px;\n",
-              "      padding: 0 0 0 0;\n",
-              "      width: 32px;\n",
-              "    }\n",
-              "\n",
-              "    .colab-df-convert:hover {\n",
-              "      background-color: #E2EBFA;\n",
-              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
-              "      fill: #174EA6;\n",
-              "    }\n",
-              "\n",
-              "    .colab-df-buttons div {\n",
-              "      margin-bottom: 4px;\n",
-              "    }\n",
-              "\n",
-              "    [theme=dark] .colab-df-convert {\n",
-              "      background-color: #3B4455;\n",
-              "      fill: #D2E3FC;\n",
-              "    }\n",
-              "\n",
-              "    [theme=dark] .colab-df-convert:hover {\n",
-              "      background-color: #434B5C;\n",
-              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
-              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
-              "      fill: #FFFFFF;\n",
-              "    }\n",
-              "  </style>\n",
-              "\n",
-              "    <script>\n",
-              "      const buttonEl =\n",
-              "        document.querySelector('#df-38079fa8-4818-4a2e-9fac-8ed19b81bcc7 button.colab-df-convert');\n",
-              "      buttonEl.style.display =\n",
-              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
-              "\n",
-              "      async function convertToInteractive(key) {\n",
-              "        const element = document.querySelector('#df-38079fa8-4818-4a2e-9fac-8ed19b81bcc7');\n",
-              "        const dataTable =\n",
-              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
-              "                                                    [key], {});\n",
-              "        if (!dataTable) return;\n",
-              "\n",
-              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
-              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
-              "          + ' to learn more about interactive tables.';\n",
-              "        element.innerHTML = '';\n",
-              "        dataTable['output_type'] = 'display_data';\n",
-              "        await google.colab.output.renderOutput(dataTable, element);\n",
-              "        const docLink = document.createElement('div');\n",
-              "        docLink.innerHTML = docLinkHtml;\n",
-              "        element.appendChild(docLink);\n",
-              "      }\n",
-              "    </script>\n",
-              "  </div>\n",
-              "\n",
-              "\n",
-              "<div id=\"df-86dfe127-37d4-496d-9eb6-7ecaac21241f\">\n",
-              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-86dfe127-37d4-496d-9eb6-7ecaac21241f')\"\n",
-              "            title=\"Suggest charts\"\n",
-              "            style=\"display:none;\">\n",
-              "\n",
-              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
-              "     width=\"24px\">\n",
-              "    <g>\n",
-              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
-              "    </g>\n",
-              "</svg>\n",
-              "  </button>\n",
-              "\n",
-              "<style>\n",
-              "  .colab-df-quickchart {\n",
-              "      --bg-color: #E8F0FE;\n",
-              "      --fill-color: #1967D2;\n",
-              "      --hover-bg-color: #E2EBFA;\n",
-              "      --hover-fill-color: #174EA6;\n",
-              "      --disabled-fill-color: #AAA;\n",
-              "      --disabled-bg-color: #DDD;\n",
-              "  }\n",
-              "\n",
-              "  [theme=dark] .colab-df-quickchart {\n",
-              "      --bg-color: #3B4455;\n",
-              "      --fill-color: #D2E3FC;\n",
-              "      --hover-bg-color: #434B5C;\n",
-              "      --hover-fill-color: #FFFFFF;\n",
-              "      --disabled-bg-color: #3B4455;\n",
-              "      --disabled-fill-color: #666;\n",
-              "  }\n",
-              "\n",
-              "  .colab-df-quickchart {\n",
-              "    background-color: var(--bg-color);\n",
-              "    border: none;\n",
-              "    border-radius: 50%;\n",
-              "    cursor: pointer;\n",
-              "    display: none;\n",
-              "    fill: var(--fill-color);\n",
-              "    height: 32px;\n",
-              "    padding: 0;\n",
-              "    width: 32px;\n",
-              "  }\n",
-              "\n",
-              "  .colab-df-quickchart:hover {\n",
-              "    background-color: var(--hover-bg-color);\n",
-              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
-              "    fill: var(--button-hover-fill-color);\n",
-              "  }\n",
-              "\n",
-              "  .colab-df-quickchart-complete:disabled,\n",
-              "  .colab-df-quickchart-complete:disabled:hover {\n",
-              "    background-color: var(--disabled-bg-color);\n",
-              "    fill: var(--disabled-fill-color);\n",
-              "    box-shadow: none;\n",
-              "  }\n",
-              "\n",
-              "  .colab-df-spinner {\n",
-              "    border: 2px solid var(--fill-color);\n",
-              "    border-color: transparent;\n",
-              "    border-bottom-color: var(--fill-color);\n",
-              "    animation:\n",
-              "      spin 1s steps(1) infinite;\n",
-              "  }\n",
-              "\n",
-              "  @keyframes spin {\n",
-              "    0% {\n",
-              "      border-color: transparent;\n",
-              "      border-bottom-color: var(--fill-color);\n",
-              "      border-left-color: var(--fill-color);\n",
-              "    }\n",
-              "    20% {\n",
-              "      border-color: transparent;\n",
-              "      border-left-color: var(--fill-color);\n",
-              "      border-top-color: var(--fill-color);\n",
-              "    }\n",
-              "    30% {\n",
-              "      border-color: transparent;\n",
-              "      border-left-color: var(--fill-color);\n",
-              "      border-top-color: var(--fill-color);\n",
-              "      border-right-color: var(--fill-color);\n",
-              "    }\n",
-              "    40% {\n",
-              "      border-color: transparent;\n",
-              "      border-right-color: var(--fill-color);\n",
-              "      border-top-color: var(--fill-color);\n",
-              "    }\n",
-              "    60% {\n",
-              "      border-color: transparent;\n",
-              "      border-right-color: var(--fill-color);\n",
-              "    }\n",
-              "    80% {\n",
-              "      border-color: transparent;\n",
-              "      border-right-color: var(--fill-color);\n",
-              "      border-bottom-color: var(--fill-color);\n",
-              "    }\n",
-              "    90% {\n",
-              "      border-color: transparent;\n",
-              "      border-bottom-color: var(--fill-color);\n",
-              "    }\n",
-              "  }\n",
-              "</style>\n",
-              "\n",
-              "  <script>\n",
-              "    async function quickchart(key) {\n",
-              "      const quickchartButtonEl =\n",
-              "        document.querySelector('#' + key + ' button');\n",
-              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
-              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
-              "      try {\n",
-              "        const charts = await google.colab.kernel.invokeFunction(\n",
-              "            'suggestCharts', [key], {});\n",
-              "      } catch (error) {\n",
-              "        console.error('Error during call to suggestCharts:', error);\n",
-              "      }\n",
-              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
-              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
-              "    }\n",
-              "    (() => {\n",
-              "      let quickchartButtonEl =\n",
-              "        document.querySelector('#df-86dfe127-37d4-496d-9eb6-7ecaac21241f button');\n",
-              "      quickchartButtonEl.style.display =\n",
-              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
-              "    })();\n",
-              "  </script>\n",
-              "</div>\n",
-              "\n",
-              "    </div>\n",
-              "  </div>\n"
-            ],
-            "application/vnd.google.colaboratory.intrinsic+json": {
-              "type": "dataframe",
-              "variable_name": "df",
-              "summary": "{\n  \"name\": \"df\",\n  \"rows\": 3000,\n  \"fields\": [\n    {\n      \"column\": \"longitude\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1.9949362939550161,\n        \"min\": -124.18,\n        \"max\": -114.49,\n        \"num_unique_values\": 607,\n        \"samples\": [\n          -121.15,\n          -121.46,\n          -121.02\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"latitude\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 2.1296695233438325,\n        \"min\": 32.56,\n        \"max\": 41.92,\n        \"num_unique_values\": 587,\n        \"samples\": [\n          40.17,\n          33.69,\n          39.61\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"housing_median_age\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 12.555395554955755,\n        \"min\": 1.0,\n        \"max\": 52.0,\n        \"num_unique_values\": 52,\n        \"samples\": [\n          14.0,\n          49.0,\n          7.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"total_rooms\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 2155.59333162558,\n        \"min\": 6.0,\n        \"max\": 30450.0,\n        \"num_unique_values\": 2215,\n        \"samples\": [\n          1961.0,\n          1807.0,\n          680.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"total_bedrooms\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 415.6543681363232,\n        \"min\": 2.0,\n        \"max\": 5419.0,\n        \"num_unique_values\": 1055,\n        \"samples\": [\n          532.0,\n          764.0,\n          2162.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"population\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1030.5430124122422,\n        \"min\": 5.0,\n        \"max\": 11935.0,\n        \"num_unique_values\": 1802,\n        \"samples\": [\n          947.0,\n          1140.0,\n          2019.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"households\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 365.42270980552604,\n        \"min\": 2.0,\n        \"max\": 4930.0,\n        \"num_unique_values\": 1026,\n        \"samples\": [\n          646.0,\n          629.0,\n          504.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"median_income\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1.854511729691481,\n        \"min\": 0.4999,\n        \"max\": 15.0001,\n        \"num_unique_values\": 2578,\n        \"samples\": [\n          1.725,\n          0.7403,\n          2.6964\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"median_house_value\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 113119.68746964433,\n        \"min\": 22500.0,\n        \"max\": 500001.0,\n        \"num_unique_values\": 1784,\n        \"samples\": [\n          71900.0,\n          63000.0,\n          115800.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
-            }
-          },
-          "metadata": {},
-          "execution_count": 5
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "source": [
-        "df.shape"
-      ],
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "id": "8YBEQ5ZPtyRu",
-        "outputId": "b23eb485-b7f6-477f-b515-d46fedc41dca"
-      },
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "execute_result",
-          "data": {
-            "text/plain": [
-              "(3000, 9)"
-            ]
-          },
-          "metadata": {},
-          "execution_count": 10
-        }
-      ]
-    },
-    {
-      "cell_type": "markdown",
-      "source": [
-        "## yt-dlp"
-      ],
-      "metadata": {
-        "id": "dthivj-_sn_w"
-      }
-    },
-    {
-      "cell_type": "code",
-      "source": [
-        "! apt-get install ffmpeg"
-      ],
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "id": "BKdcB7l-vz_h",
-        "outputId": "16893d68-2951-49d0-96d2-c3653d6a44fb"
-      },
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "stream",
-          "name": "stdout",
-          "text": [
-            "Reading package lists... Done\n",
-            "Building dependency tree... Done\n",
-            "Reading state information... Done\n",
-            "ffmpeg is already the newest version (7:4.4.2-0ubuntu0.22.04.1).\n",
-            "0 upgraded, 0 newly installed, 0 to remove and 49 not upgraded.\n"
-          ]
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "source": [
-        "pip install yt-dlp"
-      ],
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "id": "VegGCtSaspMK",
-        "outputId": "06c0b539-dc12-4eda-bb42-8231ebb8ec75"
-      },
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "stream",
-          "name": "stdout",
-          "text": [
-            "Collecting yt-dlp\n",
-            "  Downloading yt_dlp-2024.11.4-py3-none-any.whl.metadata (172 kB)\n",
-            "\u001b[?25l     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m0.0/172.1 kB\u001b[0m \u001b[31m?\u001b[0m eta \u001b[36m-:--:--\u001b[0m\r\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m172.1/172.1 kB\u001b[0m \u001b[31m5.0 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
-            "\u001b[?25hDownloading yt_dlp-2024.11.4-py3-none-any.whl (3.2 MB)\n",
-            "\u001b[?25l   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m0.0/3.2 MB\u001b[0m \u001b[31m?\u001b[0m eta \u001b[36m-:--:--\u001b[0m\r\u001b[2K   \u001b[91m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[90m╺\u001b[0m\u001b[90m━━━━━━\u001b[0m \u001b[32m2.6/3.2 MB\u001b[0m \u001b[31m69.6 MB/s\u001b[0m eta \u001b[36m0:00:01\u001b[0m\r\u001b[2K   \u001b[91m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[91m╸\u001b[0m \u001b[32m3.2/3.2 MB\u001b[0m \u001b[31m65.8 MB/s\u001b[0m eta \u001b[36m0:00:01\u001b[0m\r\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m3.2/3.2 MB\u001b[0m \u001b[31m33.7 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
-            "\u001b[?25hInstalling collected packages: yt-dlp\n",
-            "Successfully installed yt-dlp-2024.11.4\n"
-          ]
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "source": [
-        "import yt_dlp\n",
-        "\n",
-        "def download_audio(url):\n",
-        "    ydl_opts = {\n",
-        "        'format': 'bestaudio/best',\n",
-        "        'postprocessors': [{\n",
-        "            'key': 'FFmpegExtractAudio',\n",
-        "            'preferredcodec': 'mp3',\n",
-        "            'preferredquality': '192',\n",
-        "        }],\n",
-        "        'outtmpl': '%(title)s.%(ext)s',\n",
-        "        'verbose': True,  # Add this line\n",
-        "    }\n",
-        "\n",
-        "    with yt_dlp.YoutubeDL(ydl_opts) as ydl:\n",
-        "        ydl.download([url])"
-      ],
-      "metadata": {
-        "id": "NYJ03kwms7TY"
-      },
-      "execution_count": null,
-      "outputs": []
-    },
-    {
-      "cell_type": "code",
-      "source": [
-        "URL = \"https://www.youtube.com/watch?v=UF8uR6Z6KLc\"\n",
-        "download_audio(URL)"
-      ],
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "id": "wMM6oBSks8FZ",
-        "outputId": "d17918c9-7196-4aa4-83f8-1780a0739df7"
-      },
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "stream",
-          "name": "stderr",
-          "text": [
-            "[debug] Encodings: locale UTF-8, fs utf-8, pref UTF-8, out UTF-8 (No ANSI), error UTF-8 (No ANSI), screen UTF-8 (No ANSI)\n",
-            "[debug] yt-dlp version stable@2024.11.04 from yt-dlp/yt-dlp [197d0b03b] (pip) API\n",
-            "[debug] params: {'format': 'bestaudio/best', 'postprocessors': [{'key': 'FFmpegExtractAudio', 'preferredcodec': 'mp3', 'preferredquality': '192'}], 'outtmpl': '%(title)s.%(ext)s', 'verbose': True, 'compat_opts': set(), 'http_headers': {'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/91.0.4472.124 Safari/537.36', 'Accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8', 'Accept-Language': 'en-us,en;q=0.5', 'Sec-Fetch-Mode': 'navigate'}}\n",
-            "[debug] Python 3.10.12 (CPython x86_64 64bit) - Linux-6.1.85+-x86_64-with-glibc2.35 (OpenSSL 3.0.2 15 Mar 2022, glibc 2.35)\n",
-            "[debug] exe versions: ffmpeg 4.4.2 (setts), ffprobe 4.4.2\n",
-            "[debug] Optional libraries: certifi-2024.08.30, requests-2.32.3, secretstorage-3.3.1, sqlite3-3.37.2, urllib3-2.2.3\n",
-            "[debug] Proxy map: {'colab_language_server': '/usr/colab/bin/language_service'}\n",
-            "[debug] Request Handlers: urllib, requests\n",
-            "[debug] Loaded 1838 extractors\n"
-          ]
-        },
-        {
-          "output_type": "stream",
-          "name": "stdout",
-          "text": [
-            "[youtube] Extracting URL: https://www.youtube.com/watch?v=UF8uR6Z6KLc\n",
-            "[youtube] UF8uR6Z6KLc: Downloading webpage\n",
-            "[youtube] UF8uR6Z6KLc: Downloading ios player API JSON\n",
-            "[youtube] UF8uR6Z6KLc: Downloading mweb player API JSON\n",
-            "[youtube] UF8uR6Z6KLc: Downloading player 4e23410d\n"
-          ]
-        },
-        {
-          "output_type": "stream",
-          "name": "stderr",
-          "text": [
-            "[debug] Saving youtube-nsig.4e23410d to cache\n",
-            "[debug] [youtube] Decrypted nsig TODInL2VkpwBeZYW7 => wBKo3X3nM8BmSA\n",
-            "[debug] Loading youtube-nsig.4e23410d from cache\n",
-            "[debug] [youtube] Decrypted nsig vAeQv-NfW6cUtSuNm => 9nN6xXoPuOaU-A\n"
-          ]
-        },
-        {
-          "output_type": "stream",
-          "name": "stdout",
-          "text": [
-            "[youtube] UF8uR6Z6KLc: Downloading m3u8 information\n"
-          ]
-        },
-        {
-          "output_type": "stream",
-          "name": "stderr",
-          "text": [
-            "[debug] Sort order given by extractor: quality, res, fps, hdr:12, source, vcodec, channels, acodec, lang, proto\n",
-            "[debug] Formats sorted by: hasvid, ie_pref, quality, res, fps, hdr:12(7), source, vcodec, channels, acodec, lang, proto, size, br, asr, vext, aext, hasaud, id\n"
-          ]
-        },
-        {
-          "output_type": "stream",
-          "name": "stdout",
-          "text": [
-            "[info] UF8uR6Z6KLc: Downloading 1 format(s): 251\n"
-          ]
-        },
-        {
-          "output_type": "stream",
-          "name": "stderr",
-          "text": [
-            "[debug] Invoking http downloader on \"https://rr1---sn-qxo7rn7r.googlevideo.com/videoplayback?expire=1730771008&ei=4CMpZ4XhJpPBsfIP7deLmAo&ip=35.199.188.39&id=o-APTN0lKEb0Qfe0Jq0HNmcfAnPmHCwQ_vTDUQ-grBegFk&itag=251&source=youtube&requiressl=yes&xpc=EgVo2aDSNQ%3D%3D&met=1730749408%2C&mh=-6&mm=31%2C26&mn=sn-qxo7rn7r%2Csn-a5mekndl&ms=au%2Conr&mv=m&mvi=1&pl=20&rms=au%2Cau&vprv=1&svpuc=1&mime=audio%2Fwebm&rqh=1&gir=yes&clen=11436231&dur=904.241&lmt=1727658751589050&mt=1730749051&fvip=3&keepalive=yes&fexp=51312688%2C51326932&c=IOS&txp=4532434&sparams=expire%2Cei%2Cip%2Cid%2Citag%2Csource%2Crequiressl%2Cxpc%2Cvprv%2Csvpuc%2Cmime%2Crqh%2Cgir%2Cclen%2Cdur%2Clmt&sig=AJfQdSswRAIgdyRaqQwBtuq6sm2qQrZRZtYbW8LoccP0YWy2R9hHK70CIE3HXpRHAOJFUukFaZHGV2uQ-Sk6VmPSgZ74DwmAQICb&lsparams=met%2Cmh%2Cmm%2Cmn%2Cms%2Cmv%2Cmvi%2Cpl%2Crms&lsig=ACJ0pHgwRQIhAI2cNPYa2PUX70RTEbQQjQVfq6JLIv8EL0Te68Yfpqn-AiAOWu5_w37ZFpinBi-6Xt70X5Mdhlv6iviwRj7LeGV7Cg%3D%3D\"\n"
-          ]
-        },
-        {
-          "output_type": "stream",
-          "name": "stdout",
-          "text": [
-            "[download] Destination: Steve Jobs' 2005 Stanford Commencement Address.webm\n",
-            "[download] 100% of   10.91MiB in 00:00:00 at 22.43MiB/s  \n"
-          ]
-        },
-        {
-          "output_type": "stream",
-          "name": "stderr",
-          "text": [
-            "[debug] ffmpeg command line: ffprobe -show_streams 'file:Steve Jobs'\"'\"' 2005 Stanford Commencement Address.webm'\n"
-          ]
-        },
-        {
-          "output_type": "stream",
-          "name": "stdout",
-          "text": [
-            "[ExtractAudio] Destination: Steve Jobs' 2005 Stanford Commencement Address.mp3\n"
-          ]
-        },
-        {
-          "output_type": "stream",
-          "name": "stderr",
-          "text": [
-            "[debug] ffmpeg command line: ffmpeg -y -loglevel repeat+info -i 'file:Steve Jobs'\"'\"' 2005 Stanford Commencement Address.webm' -vn -acodec libmp3lame -b:a 192.0k -movflags +faststart 'file:Steve Jobs'\"'\"' 2005 Stanford Commencement Address.mp3'\n"
-          ]
-        },
-        {
-          "output_type": "stream",
-          "name": "stdout",
-          "text": [
-            "Deleting original file Steve Jobs' 2005 Stanford Commencement Address.webm (pass -k to keep)\n"
-          ]
-        }
-      ]
-    },
-    {
-      "cell_type": "markdown",
-      "source": [
-        "## scikit-learn"
-      ],
-      "metadata": {
-        "id": "gHB4HINduElj"
-      }
-    },
-    {
-      "cell_type": "code",
-      "source": [
-        "pip install scikit-learn -U"
-      ],
-      "metadata": {
-        "id": "7A1yCVNlutQ_"
-      },
-      "execution_count": null,
-      "outputs": []
-    },
-    {
-      "cell_type": "code",
-      "source": [
-        "from sklearn.datasets import make_hastie_10_2\n",
-        "from sklearn.ensemble import GradientBoostingClassifier\n",
-        "\n",
-        "X, y = make_hastie_10_2(random_state=0)\n",
-        "clf = GradientBoostingClassifier(n_estimators=100, learning_rate=1.0,\n",
-        "    max_depth=1, random_state=0).fit(X, y)\n",
-        "clf.feature_importances_"
-      ],
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "id": "KVIBZ62euF87",
-        "outputId": "1bc8f2b9-3eae-48c3-b44a-2b5d89d25e7e"
-      },
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "execute_result",
-          "data": {
-            "text/plain": [
-              "array([0.10684213, 0.10461707, 0.11265447, 0.09863589, 0.09469133,\n",
-              "       0.10729306, 0.09163753, 0.09718194, 0.09581415, 0.09063242])"
-            ]
-          },
-          "metadata": {},
-          "execution_count": 11
-        }
-      ]
-    },
-    {
-      "cell_type": "markdown",
-      "source": [
-        "## altair"
-      ],
-      "metadata": {
-        "id": "YFoTWdpdu_fV"
-      }
-    },
-    {
-      "cell_type": "markdown",
-      "source": [
-        "### Heatmap\n",
-        "\n",
-        "Here's how to create a Heatmap."
-      ],
-      "metadata": {
-        "id": "cAno9XZkvOor"
-      }
-    },
-    {
-      "cell_type": "code",
-      "source": [
-        "import altair as alt\n",
-        "import numpy as np\n",
-        "import pandas as pd\n",
-        "\n",
-        "# Compute x^2 + y^2 across a 2D grid\n",
-        "x, y = np.meshgrid(range(-5, 5), range(-5, 5))\n",
-        "z = x ** 2 + y ** 2\n",
-        "\n",
-        "# Convert this grid to columnar data expected by Altair\n",
-        "source = pd.DataFrame({'x': x.ravel(),\n",
-        "                     'y': y.ravel(),\n",
-        "                     'z': z.ravel()})\n",
-        "\n",
-        "alt.Chart(source).mark_rect().encode(\n",
-        "    x='x:O',\n",
-        "    y='y:O',\n",
-        "    color='z:Q'\n",
-        ")"
-      ],
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 262
-        },
-        "id": "7NSe5rKiuG82",
-        "outputId": "c56c460c-5cde-4100-f91e-e1e44ece081f"
-      },
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "execute_result",
-          "data": {
-            "text/html": [
-              "\n",
-              "<div id=\"altair-viz-5c8c3711123143b0907a7fb329ffbbce\"></div>\n",
-              "<script type=\"text/javascript\">\n",
-              "  var VEGA_DEBUG = (typeof VEGA_DEBUG == \"undefined\") ? {} : VEGA_DEBUG;\n",
-              "  (function(spec, embedOpt){\n",
-              "    let outputDiv = document.currentScript.previousElementSibling;\n",
-              "    if (outputDiv.id !== \"altair-viz-5c8c3711123143b0907a7fb329ffbbce\") {\n",
-              "      outputDiv = document.getElementById(\"altair-viz-5c8c3711123143b0907a7fb329ffbbce\");\n",
-              "    }\n",
-              "    const paths = {\n",
-              "      \"vega\": \"https://cdn.jsdelivr.net/npm//vega@5?noext\",\n",
-              "      \"vega-lib\": \"https://cdn.jsdelivr.net/npm//vega-lib?noext\",\n",
-              "      \"vega-lite\": \"https://cdn.jsdelivr.net/npm//vega-lite@4.17.0?noext\",\n",
-              "      \"vega-embed\": \"https://cdn.jsdelivr.net/npm//vega-embed@6?noext\",\n",
-              "    };\n",
-              "\n",
-              "    function maybeLoadScript(lib, version) {\n",
-              "      var key = `${lib.replace(\"-\", \"\")}_version`;\n",
-              "      return (VEGA_DEBUG[key] == version) ?\n",
-              "        Promise.resolve(paths[lib]) :\n",
-              "        new Promise(function(resolve, reject) {\n",
-              "          var s = document.createElement('script');\n",
-              "          document.getElementsByTagName(\"head\")[0].appendChild(s);\n",
-              "          s.async = true;\n",
-              "          s.onload = () => {\n",
-              "            VEGA_DEBUG[key] = version;\n",
-              "            return resolve(paths[lib]);\n",
-              "          };\n",
-              "          s.onerror = () => reject(`Error loading script: ${paths[lib]}`);\n",
-              "          s.src = paths[lib];\n",
-              "        });\n",
-              "    }\n",
-              "\n",
-              "    function showError(err) {\n",
-              "      outputDiv.innerHTML = `<div class=\"error\" style=\"color:red;\">${err}</div>`;\n",
-              "      throw err;\n",
-              "    }\n",
-              "\n",
-              "    function displayChart(vegaEmbed) {\n",
-              "      vegaEmbed(outputDiv, spec, embedOpt)\n",
-              "        .catch(err => showError(`Javascript Error: ${err.message}<br>This usually means there's a typo in your chart specification. See the javascript console for the full traceback.`));\n",
-              "    }\n",
-              "\n",
-              "    if(typeof define === \"function\" && define.amd) {\n",
-              "      requirejs.config({paths});\n",
-              "      require([\"vega-embed\"], displayChart, err => showError(`Error loading script: ${err.message}`));\n",
-              "    } else {\n",
-              "      maybeLoadScript(\"vega\", \"5\")\n",
-              "        .then(() => maybeLoadScript(\"vega-lite\", \"4.17.0\"))\n",
-              "        .then(() => maybeLoadScript(\"vega-embed\", \"6\"))\n",
-              "        .catch(showError)\n",
-              "        .then(() => displayChart(vegaEmbed));\n",
-              "    }\n",
-              "  })({\"config\": {\"view\": {\"continuousWidth\": 400, \"continuousHeight\": 300}}, \"data\": {\"name\": \"data-1487c93b91dee61ec4c167e470e512f4\"}, \"mark\": \"rect\", \"encoding\": {\"color\": {\"field\": \"z\", \"type\": \"quantitative\"}, \"x\": {\"field\": \"x\", \"type\": \"ordinal\"}, \"y\": {\"field\": \"y\", \"type\": \"ordinal\"}}, \"$schema\": \"https://vega.github.io/schema/vega-lite/v4.17.0.json\", \"datasets\": {\"data-1487c93b91dee61ec4c167e470e512f4\": [{\"x\": -5, \"y\": -5, \"z\": 50}, {\"x\": -4, \"y\": -5, \"z\": 41}, {\"x\": -3, \"y\": -5, \"z\": 34}, {\"x\": -2, \"y\": -5, \"z\": 29}, {\"x\": -1, \"y\": -5, \"z\": 26}, {\"x\": 0, \"y\": -5, \"z\": 25}, {\"x\": 1, \"y\": -5, \"z\": 26}, {\"x\": 2, \"y\": -5, \"z\": 29}, {\"x\": 3, \"y\": -5, \"z\": 34}, {\"x\": 4, \"y\": -5, \"z\": 41}, {\"x\": -5, \"y\": -4, \"z\": 41}, {\"x\": -4, \"y\": -4, \"z\": 32}, {\"x\": -3, \"y\": -4, \"z\": 25}, {\"x\": -2, \"y\": -4, \"z\": 20}, {\"x\": -1, \"y\": -4, \"z\": 17}, {\"x\": 0, \"y\": -4, \"z\": 16}, {\"x\": 1, \"y\": -4, \"z\": 17}, {\"x\": 2, \"y\": -4, \"z\": 20}, {\"x\": 3, \"y\": -4, \"z\": 25}, {\"x\": 4, \"y\": -4, \"z\": 32}, {\"x\": -5, \"y\": -3, \"z\": 34}, {\"x\": -4, \"y\": -3, \"z\": 25}, {\"x\": -3, \"y\": -3, \"z\": 18}, {\"x\": -2, \"y\": -3, \"z\": 13}, {\"x\": -1, \"y\": -3, \"z\": 10}, {\"x\": 0, \"y\": -3, \"z\": 9}, {\"x\": 1, \"y\": -3, \"z\": 10}, {\"x\": 2, \"y\": -3, \"z\": 13}, {\"x\": 3, \"y\": -3, \"z\": 18}, {\"x\": 4, \"y\": -3, \"z\": 25}, {\"x\": -5, \"y\": -2, \"z\": 29}, {\"x\": -4, \"y\": -2, \"z\": 20}, {\"x\": -3, \"y\": -2, \"z\": 13}, {\"x\": -2, \"y\": -2, \"z\": 8}, {\"x\": -1, \"y\": -2, \"z\": 5}, {\"x\": 0, \"y\": -2, \"z\": 4}, {\"x\": 1, \"y\": -2, \"z\": 5}, {\"x\": 2, \"y\": -2, \"z\": 8}, {\"x\": 3, \"y\": -2, \"z\": 13}, {\"x\": 4, \"y\": -2, \"z\": 20}, {\"x\": -5, \"y\": -1, \"z\": 26}, {\"x\": -4, \"y\": -1, \"z\": 17}, {\"x\": -3, \"y\": -1, \"z\": 10}, {\"x\": -2, \"y\": -1, \"z\": 5}, {\"x\": -1, \"y\": -1, \"z\": 2}, {\"x\": 0, \"y\": -1, \"z\": 1}, {\"x\": 1, \"y\": -1, \"z\": 2}, {\"x\": 2, \"y\": -1, \"z\": 5}, {\"x\": 3, \"y\": -1, \"z\": 10}, {\"x\": 4, \"y\": -1, \"z\": 17}, {\"x\": -5, \"y\": 0, \"z\": 25}, {\"x\": -4, \"y\": 0, \"z\": 16}, {\"x\": -3, \"y\": 0, \"z\": 9}, {\"x\": -2, \"y\": 0, \"z\": 4}, {\"x\": -1, \"y\": 0, \"z\": 1}, {\"x\": 0, \"y\": 0, \"z\": 0}, {\"x\": 1, \"y\": 0, \"z\": 1}, {\"x\": 2, \"y\": 0, \"z\": 4}, {\"x\": 3, \"y\": 0, \"z\": 9}, {\"x\": 4, \"y\": 0, \"z\": 16}, {\"x\": -5, \"y\": 1, \"z\": 26}, {\"x\": -4, \"y\": 1, \"z\": 17}, {\"x\": -3, \"y\": 1, \"z\": 10}, {\"x\": -2, \"y\": 1, \"z\": 5}, {\"x\": -1, \"y\": 1, \"z\": 2}, {\"x\": 0, \"y\": 1, \"z\": 1}, {\"x\": 1, \"y\": 1, \"z\": 2}, {\"x\": 2, \"y\": 1, \"z\": 5}, {\"x\": 3, \"y\": 1, \"z\": 10}, {\"x\": 4, \"y\": 1, \"z\": 17}, {\"x\": -5, \"y\": 2, \"z\": 29}, {\"x\": -4, \"y\": 2, \"z\": 20}, {\"x\": -3, \"y\": 2, \"z\": 13}, {\"x\": -2, \"y\": 2, \"z\": 8}, {\"x\": -1, \"y\": 2, \"z\": 5}, {\"x\": 0, \"y\": 2, \"z\": 4}, {\"x\": 1, \"y\": 2, \"z\": 5}, {\"x\": 2, \"y\": 2, \"z\": 8}, {\"x\": 3, \"y\": 2, \"z\": 13}, {\"x\": 4, \"y\": 2, \"z\": 20}, {\"x\": -5, \"y\": 3, \"z\": 34}, {\"x\": -4, \"y\": 3, \"z\": 25}, {\"x\": -3, \"y\": 3, \"z\": 18}, {\"x\": -2, \"y\": 3, \"z\": 13}, {\"x\": -1, \"y\": 3, \"z\": 10}, {\"x\": 0, \"y\": 3, \"z\": 9}, {\"x\": 1, \"y\": 3, \"z\": 10}, {\"x\": 2, \"y\": 3, \"z\": 13}, {\"x\": 3, \"y\": 3, \"z\": 18}, {\"x\": 4, \"y\": 3, \"z\": 25}, {\"x\": -5, \"y\": 4, \"z\": 41}, {\"x\": -4, \"y\": 4, \"z\": 32}, {\"x\": -3, \"y\": 4, \"z\": 25}, {\"x\": -2, \"y\": 4, \"z\": 20}, {\"x\": -1, \"y\": 4, \"z\": 17}, {\"x\": 0, \"y\": 4, \"z\": 16}, {\"x\": 1, \"y\": 4, \"z\": 17}, {\"x\": 2, \"y\": 4, \"z\": 20}, {\"x\": 3, \"y\": 4, \"z\": 25}, {\"x\": 4, \"y\": 4, \"z\": 32}]}}, {\"mode\": \"vega-lite\"});\n",
-              "</script>"
-            ],
-            "text/plain": [
-              "alt.Chart(...)"
-            ]
-          },
-          "metadata": {},
-          "execution_count": 12
-        }
-      ]
-    },
-    {
-      "cell_type": "markdown",
-      "source": [
-        "### Stacked Area Chart"
-      ],
-      "metadata": {
-        "id": "1sGwP2h9vaKw"
-      }
-    },
-    {
-      "cell_type": "code",
-      "source": [
-        "import altair as alt\n",
-        "from vega_datasets import data\n",
-        "\n",
-        "source = data.iowa_electricity()\n",
-        "\n",
-        "alt.Chart(source).mark_area().encode(\n",
-        "    x=\"year:T\",\n",
-        "    y=\"net_generation:Q\",\n",
-        "    color=\"source:N\"\n",
-        ")"
-      ],
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 424
-        },
-        "id": "vDQc_4kLvH8l",
-        "outputId": "0c72c68a-d72e-4564-afe6-253793faf7a8"
-      },
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "stream",
-          "name": "stderr",
-          "text": [
-            "/usr/local/lib/python3.10/dist-packages/altair/utils/core.py:384: FutureWarning: the convert_dtype parameter is deprecated and will be removed in a future version.  Do ``ser.astype(object).apply()`` instead if you want ``convert_dtype=False``.\n",
-            "  col = df[col_name].apply(to_list_if_array, convert_dtype=False)\n"
-          ]
-        },
-        {
-          "output_type": "execute_result",
-          "data": {
-            "text/html": [
-              "\n",
-              "<div id=\"altair-viz-b095170935ce4f0fbd49be2a5b595470\"></div>\n",
-              "<script type=\"text/javascript\">\n",
-              "  var VEGA_DEBUG = (typeof VEGA_DEBUG == \"undefined\") ? {} : VEGA_DEBUG;\n",
-              "  (function(spec, embedOpt){\n",
-              "    let outputDiv = document.currentScript.previousElementSibling;\n",
-              "    if (outputDiv.id !== \"altair-viz-b095170935ce4f0fbd49be2a5b595470\") {\n",
-              "      outputDiv = document.getElementById(\"altair-viz-b095170935ce4f0fbd49be2a5b595470\");\n",
-              "    }\n",
-              "    const paths = {\n",
-              "      \"vega\": \"https://cdn.jsdelivr.net/npm//vega@5?noext\",\n",
-              "      \"vega-lib\": \"https://cdn.jsdelivr.net/npm//vega-lib?noext\",\n",
-              "      \"vega-lite\": \"https://cdn.jsdelivr.net/npm//vega-lite@4.17.0?noext\",\n",
-              "      \"vega-embed\": \"https://cdn.jsdelivr.net/npm//vega-embed@6?noext\",\n",
-              "    };\n",
-              "\n",
-              "    function maybeLoadScript(lib, version) {\n",
-              "      var key = `${lib.replace(\"-\", \"\")}_version`;\n",
-              "      return (VEGA_DEBUG[key] == version) ?\n",
-              "        Promise.resolve(paths[lib]) :\n",
-              "        new Promise(function(resolve, reject) {\n",
-              "          var s = document.createElement('script');\n",
-              "          document.getElementsByTagName(\"head\")[0].appendChild(s);\n",
-              "          s.async = true;\n",
-              "          s.onload = () => {\n",
-              "            VEGA_DEBUG[key] = version;\n",
-              "            return resolve(paths[lib]);\n",
-              "          };\n",
-              "          s.onerror = () => reject(`Error loading script: ${paths[lib]}`);\n",
-              "          s.src = paths[lib];\n",
-              "        });\n",
-              "    }\n",
-              "\n",
-              "    function showError(err) {\n",
-              "      outputDiv.innerHTML = `<div class=\"error\" style=\"color:red;\">${err}</div>`;\n",
-              "      throw err;\n",
-              "    }\n",
-              "\n",
-              "    function displayChart(vegaEmbed) {\n",
-              "      vegaEmbed(outputDiv, spec, embedOpt)\n",
-              "        .catch(err => showError(`Javascript Error: ${err.message}<br>This usually means there's a typo in your chart specification. See the javascript console for the full traceback.`));\n",
-              "    }\n",
-              "\n",
-              "    if(typeof define === \"function\" && define.amd) {\n",
-              "      requirejs.config({paths});\n",
-              "      require([\"vega-embed\"], displayChart, err => showError(`Error loading script: ${err.message}`));\n",
-              "    } else {\n",
-              "      maybeLoadScript(\"vega\", \"5\")\n",
-              "        .then(() => maybeLoadScript(\"vega-lite\", \"4.17.0\"))\n",
-              "        .then(() => maybeLoadScript(\"vega-embed\", \"6\"))\n",
-              "        .catch(showError)\n",
-              "        .then(() => displayChart(vegaEmbed));\n",
-              "    }\n",
-              "  })({\"config\": {\"view\": {\"continuousWidth\": 400, \"continuousHeight\": 300}}, \"data\": {\"name\": \"data-bb61008ba0c766c5601afa5323d12ad4\"}, \"mark\": \"area\", \"encoding\": {\"color\": {\"field\": \"source\", \"type\": \"nominal\"}, \"x\": {\"field\": \"year\", \"type\": \"temporal\"}, \"y\": {\"field\": \"net_generation\", \"type\": \"quantitative\"}}, \"$schema\": \"https://vega.github.io/schema/vega-lite/v4.17.0.json\", \"datasets\": {\"data-bb61008ba0c766c5601afa5323d12ad4\": [{\"year\": \"2001-01-01T00:00:00\", \"source\": \"Fossil Fuels\", \"net_generation\": 35361}, {\"year\": \"2002-01-01T00:00:00\", \"source\": \"Fossil Fuels\", \"net_generation\": 35991}, {\"year\": \"2003-01-01T00:00:00\", \"source\": \"Fossil Fuels\", \"net_generation\": 36234}, {\"year\": \"2004-01-01T00:00:00\", \"source\": \"Fossil Fuels\", \"net_generation\": 36205}, {\"year\": \"2005-01-01T00:00:00\", \"source\": \"Fossil Fuels\", \"net_generation\": 36883}, {\"year\": \"2006-01-01T00:00:00\", \"source\": \"Fossil Fuels\", \"net_generation\": 37014}, {\"year\": \"2007-01-01T00:00:00\", \"source\": \"Fossil Fuels\", \"net_generation\": 41389}, {\"year\": \"2008-01-01T00:00:00\", \"source\": \"Fossil Fuels\", \"net_generation\": 42734}, {\"year\": \"2009-01-01T00:00:00\", \"source\": \"Fossil Fuels\", \"net_generation\": 38620}, {\"year\": \"2010-01-01T00:00:00\", \"source\": \"Fossil Fuels\", \"net_generation\": 42750}, {\"year\": \"2011-01-01T00:00:00\", \"source\": \"Fossil Fuels\", \"net_generation\": 39361}, {\"year\": \"2012-01-01T00:00:00\", \"source\": \"Fossil Fuels\", \"net_generation\": 37379}, {\"year\": \"2013-01-01T00:00:00\", \"source\": \"Fossil Fuels\", \"net_generation\": 34873}, {\"year\": \"2014-01-01T00:00:00\", \"source\": \"Fossil Fuels\", \"net_generation\": 35250}, {\"year\": \"2015-01-01T00:00:00\", \"source\": \"Fossil Fuels\", \"net_generation\": 32319}, {\"year\": \"2016-01-01T00:00:00\", \"source\": \"Fossil Fuels\", \"net_generation\": 28437}, {\"year\": \"2017-01-01T00:00:00\", \"source\": \"Fossil Fuels\", \"net_generation\": 29329}, {\"year\": \"2001-01-01T00:00:00\", \"source\": \"Nuclear Energy\", \"net_generation\": 3853}, {\"year\": \"2002-01-01T00:00:00\", \"source\": \"Nuclear Energy\", \"net_generation\": 4574}, {\"year\": \"2003-01-01T00:00:00\", \"source\": \"Nuclear Energy\", \"net_generation\": 3988}, {\"year\": \"2004-01-01T00:00:00\", \"source\": \"Nuclear Energy\", \"net_generation\": 4929}, {\"year\": \"2005-01-01T00:00:00\", \"source\": \"Nuclear Energy\", \"net_generation\": 4538}, {\"year\": \"2006-01-01T00:00:00\", \"source\": \"Nuclear Energy\", \"net_generation\": 5095}, {\"year\": \"2007-01-01T00:00:00\", \"source\": \"Nuclear Energy\", \"net_generation\": 4519}, {\"year\": \"2008-01-01T00:00:00\", \"source\": \"Nuclear Energy\", \"net_generation\": 5282}, {\"year\": \"2009-01-01T00:00:00\", \"source\": \"Nuclear Energy\", \"net_generation\": 4679}, {\"year\": \"2010-01-01T00:00:00\", \"source\": \"Nuclear Energy\", \"net_generation\": 4451}, {\"year\": \"2011-01-01T00:00:00\", \"source\": \"Nuclear Energy\", \"net_generation\": 5215}, {\"year\": \"2012-01-01T00:00:00\", \"source\": \"Nuclear Energy\", \"net_generation\": 4347}, {\"year\": \"2013-01-01T00:00:00\", \"source\": \"Nuclear Energy\", \"net_generation\": 5321}, {\"year\": \"2014-01-01T00:00:00\", \"source\": \"Nuclear Energy\", \"net_generation\": 4152}, {\"year\": \"2015-01-01T00:00:00\", \"source\": \"Nuclear Energy\", \"net_generation\": 5243}, {\"year\": \"2016-01-01T00:00:00\", \"source\": \"Nuclear Energy\", \"net_generation\": 4703}, {\"year\": \"2017-01-01T00:00:00\", \"source\": \"Nuclear Energy\", \"net_generation\": 5214}, {\"year\": \"2001-01-01T00:00:00\", \"source\": \"Renewables\", \"net_generation\": 1437}, {\"year\": \"2002-01-01T00:00:00\", \"source\": \"Renewables\", \"net_generation\": 1963}, {\"year\": \"2003-01-01T00:00:00\", \"source\": \"Renewables\", \"net_generation\": 1885}, {\"year\": \"2004-01-01T00:00:00\", \"source\": \"Renewables\", \"net_generation\": 2102}, {\"year\": \"2005-01-01T00:00:00\", \"source\": \"Renewables\", \"net_generation\": 2724}, {\"year\": \"2006-01-01T00:00:00\", \"source\": \"Renewables\", \"net_generation\": 3364}, {\"year\": \"2007-01-01T00:00:00\", \"source\": \"Renewables\", \"net_generation\": 3870}, {\"year\": \"2008-01-01T00:00:00\", \"source\": \"Renewables\", \"net_generation\": 5070}, {\"year\": \"2009-01-01T00:00:00\", \"source\": \"Renewables\", \"net_generation\": 8560}, {\"year\": \"2010-01-01T00:00:00\", \"source\": \"Renewables\", \"net_generation\": 10308}, {\"year\": \"2011-01-01T00:00:00\", \"source\": \"Renewables\", \"net_generation\": 11795}, {\"year\": \"2012-01-01T00:00:00\", \"source\": \"Renewables\", \"net_generation\": 14949}, {\"year\": \"2013-01-01T00:00:00\", \"source\": \"Renewables\", \"net_generation\": 16476}, {\"year\": \"2014-01-01T00:00:00\", \"source\": \"Renewables\", \"net_generation\": 17452}, {\"year\": \"2015-01-01T00:00:00\", \"source\": \"Renewables\", \"net_generation\": 19091}, {\"year\": \"2016-01-01T00:00:00\", \"source\": \"Renewables\", \"net_generation\": 21241}, {\"year\": \"2017-01-01T00:00:00\", \"source\": \"Renewables\", \"net_generation\": 21933}]}}, {\"mode\": \"vega-lite\"});\n",
-              "</script>"
-            ],
-            "text/plain": [
-              "alt.Chart(...)"
-            ]
-          },
-          "metadata": {},
-          "execution_count": 13
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "source": [],
-      "metadata": {
-        "id": "xZ2fN6SLvMYe"
-      },
-      "execution_count": null,
-      "outputs": []
-    }
-  ]
-}
\ No newline at end of file

From b99bda9287a8f3c69d00f6fdd9f8f2bd2f68542c Mon Sep 17 00:00:00 2001
From: Chanin Nantasenamat <51851491+dataprofessor@users.noreply.github.com>
Date: Sat, 10 Jan 2026 00:23:20 -0800
Subject: [PATCH 08/11] Update README.md

---
 README.md | 2 ++
 1 file changed, 2 insertions(+)

diff --git a/README.md b/README.md
index dd32105..520d3f4 100644
--- a/README.md
+++ b/README.md
@@ -9,3 +9,5 @@ Folder | Description
 [shiny](https://github.com/dataprofessor/code/tree/master/shiny) | Codes for building *web applications* in R with *shiny* package.
 
 > Note: More to come. Please stay tuned!
+
+<iframe src="https://embeds.beehiiv.com/86bc34d8-cba0-46bf-8a88-930adb8ecbb8?slim=true" data-test-id="beehiiv-embed" height="52" frameborder="0" scrolling="no" style="margin: 0; border-radius: 0px !important; background-color: transparent;"></iframe>

From 1abd57fef5503f6d2693913e23cb268a5ad97e5a Mon Sep 17 00:00:00 2001
From: Chanin Nantasenamat <51851491+dataprofessor@users.noreply.github.com>
Date: Sat, 10 Jan 2026 00:24:48 -0800
Subject: [PATCH 09/11] Update README.md

---
 README.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/README.md b/README.md
index 520d3f4..be0cfe5 100644
--- a/README.md
+++ b/README.md
@@ -10,4 +10,4 @@ Folder | Description
 
 > Note: More to come. Please stay tuned!
 
-<iframe src="https://embeds.beehiiv.com/86bc34d8-cba0-46bf-8a88-930adb8ecbb8?slim=true" data-test-id="beehiiv-embed" height="52" frameborder="0" scrolling="no" style="margin: 0; border-radius: 0px !important; background-color: transparent;"></iframe>
+** Subscribe to my Newsletter:** https://dataprofessor.beehiiv.com/

From 820a84022d66523efce6260ab2fd2e1b68f0a599 Mon Sep 17 00:00:00 2001
From: Chanin Nantasenamat <51851491+dataprofessor@users.noreply.github.com>
Date: Sat, 10 Jan 2026 00:25:10 -0800
Subject: [PATCH 10/11] Update README.md

---
 README.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/README.md b/README.md
index be0cfe5..2139429 100644
--- a/README.md
+++ b/README.md
@@ -10,4 +10,4 @@ Folder | Description
 
 > Note: More to come. Please stay tuned!
 
-** Subscribe to my Newsletter:** https://dataprofessor.beehiiv.com/
+**Subscribe to my Newsletter:** https://dataprofessor.beehiiv.com/

From d05a1b139d03880269634926a2ca7d45538b1cbb Mon Sep 17 00:00:00 2001
From: Chanin Nantasenamat <51851491+dataprofessor@users.noreply.github.com>
Date: Sat, 10 Jan 2026 00:25:58 -0800
Subject: [PATCH 11/11] Add sparkle emoji to newsletter subscription line

---
 README.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/README.md b/README.md
index 2139429..957e9e5 100644
--- a/README.md
+++ b/README.md
@@ -10,4 +10,4 @@ Folder | Description
 
 > Note: More to come. Please stay tuned!
 
-**Subscribe to my Newsletter:** https://dataprofessor.beehiiv.com/
+✨ **Subscribe to my Newsletter:** https://dataprofessor.beehiiv.com/