diff --git a/.gitignore b/.gitignore
new file mode 100644
index 0000000..2b13c88
--- /dev/null
+++ b/.gitignore
@@ -0,0 +1,21 @@
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+**/__pycache__/
+**/.idea/
+*.py[oc]
+build/
+dist/
+wheels/
+*.egg-info
+*.spec
+*.pkl
+
+# Virtual environments
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+.models
+.whl
+output
+input
+libs
+activate.bat
+
+
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similarity index 56%
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deleted file mode 100644
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diff --git a/California Housing Prices/california housing prices.ipynb b/California Housing Prices/california housing prices.ipynb
deleted file mode 100644
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--- a/California Housing Prices/california housing prices.ipynb	
+++ /dev/null
@@ -1,1286 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "项目名称： 加利福尼亚房价预测"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## 分析数据特征"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### 将记录集装载到内存\n",
-    "\n",
-    "为了方便，建议将训练集的数据文件放在同一目录"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 27,
-   "metadata": {
-    "collapsed": true
-   },
-   "outputs": [],
-   "source": [
-    "import pandas as pd\n",
-    "import numpy as np\n",
-    "import matplotlib.pyplot as plt\n",
-    "%matplotlib inline"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 28,
-   "metadata": {
-    "collapsed": true
-   },
-   "outputs": [],
-   "source": [
-    "datafilename = \"train_set.csv\"\n",
-    "train_set_original = pd.read_csv(datafilename)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### 创建一个数据集的副本"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 29,
-   "metadata": {
-    "collapsed": true
-   },
-   "outputs": [],
-   "source": [
-    "train_set = train_set_original.copy()"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### 检查数据集的大小"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 30,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "(16512, 10)"
-      ]
-     },
-     "execution_count": 30,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "train_set.shape"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### 获得数据集的所有特征名称及数据类型\n",
-    "\n",
-    "其中:标签列为 : media_house_value"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 31,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "Index(['longitude', 'latitude', 'housing_median_age', 'total_rooms',\n",
-       "       'total_bedrooms', 'population', 'households', 'median_income',\n",
-       "       'median_house_value', 'ocean_proximity'],\n",
-       "      dtype='object')"
-      ]
-     },
-     "execution_count": 31,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "train_set.columns"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 32,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "longitude             float64\n",
-       "latitude              float64\n",
-       "housing_median_age    float64\n",
-       "total_rooms           float64\n",
-       "total_bedrooms        float64\n",
-       "population            float64\n",
-       "households            float64\n",
-       "median_income         float64\n",
-       "median_house_value    float64\n",
-       "ocean_proximity        object\n",
-       "dtype: object"
-      ]
-     },
-     "execution_count": 32,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "train_set.dtypes"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### 数据集的样本内容查看"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 33,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<div>\n",
-       "<style>\n",
-       "    .dataframe thead tr:only-child th {\n",
-       "        text-align: right;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe thead th {\n",
-       "        text-align: left;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe tbody tr th {\n",
-       "        vertical-align: top;\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",
-       "      <th>ocean_proximity</th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>0</th>\n",
-       "      <td>-117.03</td>\n",
-       "      <td>32.71</td>\n",
-       "      <td>33.0</td>\n",
-       "      <td>3126.0</td>\n",
-       "      <td>627.0</td>\n",
-       "      <td>2300.0</td>\n",
-       "      <td>623.0</td>\n",
-       "      <td>3.2596</td>\n",
-       "      <td>103000.0</td>\n",
-       "      <td>NEAR OCEAN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1</th>\n",
-       "      <td>-118.16</td>\n",
-       "      <td>33.77</td>\n",
-       "      <td>49.0</td>\n",
-       "      <td>3382.0</td>\n",
-       "      <td>787.0</td>\n",
-       "      <td>1314.0</td>\n",
-       "      <td>756.0</td>\n",
-       "      <td>3.8125</td>\n",
-       "      <td>382100.0</td>\n",
-       "      <td>NEAR OCEAN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2</th>\n",
-       "      <td>-120.48</td>\n",
-       "      <td>34.66</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>1897.0</td>\n",
-       "      <td>331.0</td>\n",
-       "      <td>915.0</td>\n",
-       "      <td>336.0</td>\n",
-       "      <td>4.1563</td>\n",
-       "      <td>172600.0</td>\n",
-       "      <td>NEAR OCEAN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>3</th>\n",
-       "      <td>-117.11</td>\n",
-       "      <td>32.69</td>\n",
-       "      <td>36.0</td>\n",
-       "      <td>1421.0</td>\n",
-       "      <td>367.0</td>\n",
-       "      <td>1418.0</td>\n",
-       "      <td>355.0</td>\n",
-       "      <td>1.9425</td>\n",
-       "      <td>93400.0</td>\n",
-       "      <td>NEAR OCEAN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>4</th>\n",
-       "      <td>-119.80</td>\n",
-       "      <td>36.78</td>\n",
-       "      <td>43.0</td>\n",
-       "      <td>2382.0</td>\n",
-       "      <td>431.0</td>\n",
-       "      <td>874.0</td>\n",
-       "      <td>380.0</td>\n",
-       "      <td>3.5542</td>\n",
-       "      <td>96500.0</td>\n",
-       "      <td>INLAND</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "   longitude  latitude  housing_median_age  total_rooms  total_bedrooms  \\\n",
-       "0    -117.03     32.71                33.0       3126.0           627.0   \n",
-       "1    -118.16     33.77                49.0       3382.0           787.0   \n",
-       "2    -120.48     34.66                 4.0       1897.0           331.0   \n",
-       "3    -117.11     32.69                36.0       1421.0           367.0   \n",
-       "4    -119.80     36.78                43.0       2382.0           431.0   \n",
-       "\n",
-       "   population  households  median_income  median_house_value ocean_proximity  \n",
-       "0      2300.0       623.0         3.2596            103000.0      NEAR OCEAN  \n",
-       "1      1314.0       756.0         3.8125            382100.0      NEAR OCEAN  \n",
-       "2       915.0       336.0         4.1563            172600.0      NEAR OCEAN  \n",
-       "3      1418.0       355.0         1.9425             93400.0      NEAR OCEAN  \n",
-       "4       874.0       380.0         3.5542             96500.0          INLAND  "
-      ]
-     },
-     "execution_count": 33,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "train_set.head()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 34,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<div>\n",
-       "<style>\n",
-       "    .dataframe thead tr:only-child th {\n",
-       "        text-align: right;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe thead th {\n",
-       "        text-align: left;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe tbody tr th {\n",
-       "        vertical-align: top;\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",
-       "      <th>ocean_proximity</th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>16507</th>\n",
-       "      <td>-117.96</td>\n",
-       "      <td>33.78</td>\n",
-       "      <td>35.0</td>\n",
-       "      <td>1330.0</td>\n",
-       "      <td>201.0</td>\n",
-       "      <td>658.0</td>\n",
-       "      <td>217.0</td>\n",
-       "      <td>6.3700</td>\n",
-       "      <td>229200.0</td>\n",
-       "      <td>&lt;1H OCEAN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>16508</th>\n",
-       "      <td>-117.43</td>\n",
-       "      <td>34.02</td>\n",
-       "      <td>33.0</td>\n",
-       "      <td>3084.0</td>\n",
-       "      <td>570.0</td>\n",
-       "      <td>1753.0</td>\n",
-       "      <td>449.0</td>\n",
-       "      <td>3.0500</td>\n",
-       "      <td>97800.0</td>\n",
-       "      <td>INLAND</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>16509</th>\n",
-       "      <td>-118.38</td>\n",
-       "      <td>34.03</td>\n",
-       "      <td>36.0</td>\n",
-       "      <td>2101.0</td>\n",
-       "      <td>569.0</td>\n",
-       "      <td>1756.0</td>\n",
-       "      <td>527.0</td>\n",
-       "      <td>2.9344</td>\n",
-       "      <td>222100.0</td>\n",
-       "      <td>&lt;1H OCEAN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>16510</th>\n",
-       "      <td>-121.96</td>\n",
-       "      <td>37.58</td>\n",
-       "      <td>15.0</td>\n",
-       "      <td>3575.0</td>\n",
-       "      <td>597.0</td>\n",
-       "      <td>1777.0</td>\n",
-       "      <td>559.0</td>\n",
-       "      <td>5.7192</td>\n",
-       "      <td>283500.0</td>\n",
-       "      <td>&lt;1H OCEAN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>16511</th>\n",
-       "      <td>-122.42</td>\n",
-       "      <td>37.77</td>\n",
-       "      <td>52.0</td>\n",
-       "      <td>4226.0</td>\n",
-       "      <td>1315.0</td>\n",
-       "      <td>2619.0</td>\n",
-       "      <td>1242.0</td>\n",
-       "      <td>2.5755</td>\n",
-       "      <td>325000.0</td>\n",
-       "      <td>NEAR BAY</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "       longitude  latitude  housing_median_age  total_rooms  total_bedrooms  \\\n",
-       "16507    -117.96     33.78                35.0       1330.0           201.0   \n",
-       "16508    -117.43     34.02                33.0       3084.0           570.0   \n",
-       "16509    -118.38     34.03                36.0       2101.0           569.0   \n",
-       "16510    -121.96     37.58                15.0       3575.0           597.0   \n",
-       "16511    -122.42     37.77                52.0       4226.0          1315.0   \n",
-       "\n",
-       "       population  households  median_income  median_house_value  \\\n",
-       "16507       658.0       217.0         6.3700            229200.0   \n",
-       "16508      1753.0       449.0         3.0500             97800.0   \n",
-       "16509      1756.0       527.0         2.9344            222100.0   \n",
-       "16510      1777.0       559.0         5.7192            283500.0   \n",
-       "16511      2619.0      1242.0         2.5755            325000.0   \n",
-       "\n",
-       "      ocean_proximity  \n",
-       "16507       <1H OCEAN  \n",
-       "16508          INLAND  \n",
-       "16509       <1H OCEAN  \n",
-       "16510       <1H OCEAN  \n",
-       "16511        NEAR BAY  "
-      ]
-     },
-     "execution_count": 34,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "train_set.tail()"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### 特征数据的分布情况"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 35,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "<1H OCEAN     7341\n",
-       "INLAND        5227\n",
-       "NEAR OCEAN    2086\n",
-       "NEAR BAY      1854\n",
-       "ISLAND           4\n",
-       "Name: ocean_proximity, dtype: int64"
-      ]
-     },
-     "execution_count": 35,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "train_set[\"ocean_proximity\"].value_counts()"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### 数据集的快速统计分析"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 36,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "<class 'pandas.core.frame.DataFrame'>\n",
-      "RangeIndex: 16512 entries, 0 to 16511\n",
-      "Data columns (total 10 columns):\n",
-      "longitude             16512 non-null float64\n",
-      "latitude              16512 non-null float64\n",
-      "housing_median_age    16512 non-null float64\n",
-      "total_rooms           16512 non-null float64\n",
-      "total_bedrooms        16512 non-null float64\n",
-      "population            16512 non-null float64\n",
-      "households            16512 non-null float64\n",
-      "median_income         16512 non-null float64\n",
-      "median_house_value    16512 non-null float64\n",
-      "ocean_proximity       16512 non-null object\n",
-      "dtypes: float64(9), object(1)\n",
-      "memory usage: 1.3+ MB\n"
-     ]
-    }
-   ],
-   "source": [
-    "train_set.info()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 37,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<div>\n",
-       "<style>\n",
-       "    .dataframe thead tr:only-child th {\n",
-       "        text-align: right;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe thead th {\n",
-       "        text-align: left;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe tbody tr th {\n",
-       "        vertical-align: top;\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>count</th>\n",
-       "      <td>16512.000000</td>\n",
-       "      <td>16512.000000</td>\n",
-       "      <td>16512.000000</td>\n",
-       "      <td>16512.000000</td>\n",
-       "      <td>16512.000000</td>\n",
-       "      <td>16512.000000</td>\n",
-       "      <td>16512.000000</td>\n",
-       "      <td>16512.000000</td>\n",
-       "      <td>16512.000000</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>mean</th>\n",
-       "      <td>-119.582290</td>\n",
-       "      <td>35.643149</td>\n",
-       "      <td>28.608285</td>\n",
-       "      <td>2642.004784</td>\n",
-       "      <td>538.496851</td>\n",
-       "      <td>1426.453004</td>\n",
-       "      <td>499.986919</td>\n",
-       "      <td>3.880754</td>\n",
-       "      <td>207194.693738</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>std</th>\n",
-       "      <td>2.005654</td>\n",
-       "      <td>2.136665</td>\n",
-       "      <td>12.602499</td>\n",
-       "      <td>2174.646744</td>\n",
-       "      <td>419.007096</td>\n",
-       "      <td>1137.056380</td>\n",
-       "      <td>380.967964</td>\n",
-       "      <td>1.904294</td>\n",
-       "      <td>115622.626448</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>min</th>\n",
-       "      <td>-124.350000</td>\n",
-       "      <td>32.550000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>2.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>3.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.499900</td>\n",
-       "      <td>14999.000000</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>25%</th>\n",
-       "      <td>-121.810000</td>\n",
-       "      <td>33.930000</td>\n",
-       "      <td>18.000000</td>\n",
-       "      <td>1454.000000</td>\n",
-       "      <td>296.750000</td>\n",
-       "      <td>789.000000</td>\n",
-       "      <td>280.000000</td>\n",
-       "      <td>2.566700</td>\n",
-       "      <td>119800.000000</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>50%</th>\n",
-       "      <td>-118.510000</td>\n",
-       "      <td>34.260000</td>\n",
-       "      <td>29.000000</td>\n",
-       "      <td>2129.000000</td>\n",
-       "      <td>437.000000</td>\n",
-       "      <td>1167.000000</td>\n",
-       "      <td>410.000000</td>\n",
-       "      <td>3.545800</td>\n",
-       "      <td>179850.000000</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>75%</th>\n",
-       "      <td>-118.010000</td>\n",
-       "      <td>37.720000</td>\n",
-       "      <td>37.000000</td>\n",
-       "      <td>3160.000000</td>\n",
-       "      <td>647.000000</td>\n",
-       "      <td>1726.000000</td>\n",
-       "      <td>606.000000</td>\n",
-       "      <td>4.773175</td>\n",
-       "      <td>265125.000000</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>max</th>\n",
-       "      <td>-114.310000</td>\n",
-       "      <td>41.950000</td>\n",
-       "      <td>52.000000</td>\n",
-       "      <td>39320.000000</td>\n",
-       "      <td>6445.000000</td>\n",
-       "      <td>35682.000000</td>\n",
-       "      <td>6082.000000</td>\n",
-       "      <td>15.000100</td>\n",
-       "      <td>500001.000000</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "          longitude      latitude  housing_median_age   total_rooms  \\\n",
-       "count  16512.000000  16512.000000        16512.000000  16512.000000   \n",
-       "mean    -119.582290     35.643149           28.608285   2642.004784   \n",
-       "std        2.005654      2.136665           12.602499   2174.646744   \n",
-       "min     -124.350000     32.550000            1.000000      2.000000   \n",
-       "25%     -121.810000     33.930000           18.000000   1454.000000   \n",
-       "50%     -118.510000     34.260000           29.000000   2129.000000   \n",
-       "75%     -118.010000     37.720000           37.000000   3160.000000   \n",
-       "max     -114.310000     41.950000           52.000000  39320.000000   \n",
-       "\n",
-       "       total_bedrooms    population    households  median_income  \\\n",
-       "count    16512.000000  16512.000000  16512.000000   16512.000000   \n",
-       "mean       538.496851   1426.453004    499.986919       3.880754   \n",
-       "std        419.007096   1137.056380    380.967964       1.904294   \n",
-       "min          1.000000      3.000000      1.000000       0.499900   \n",
-       "25%        296.750000    789.000000    280.000000       2.566700   \n",
-       "50%        437.000000   1167.000000    410.000000       3.545800   \n",
-       "75%        647.000000   1726.000000    606.000000       4.773175   \n",
-       "max       6445.000000  35682.000000   6082.000000      15.000100   \n",
-       "\n",
-       "       median_house_value  \n",
-       "count        16512.000000  \n",
-       "mean        207194.693738  \n",
-       "std         115622.626448  \n",
-       "min          14999.000000  \n",
-       "25%         119800.000000  \n",
-       "50%         179850.000000  \n",
-       "75%         265125.000000  \n",
-       "max         500001.000000  "
-      ]
-     },
-     "execution_count": 37,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "train_set.describe()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 38,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "longitude             0\n",
-       "latitude              0\n",
-       "housing_median_age    0\n",
-       "total_rooms           0\n",
-       "total_bedrooms        0\n",
-       "population            0\n",
-       "households            0\n",
-       "median_income         0\n",
-       "median_house_value    0\n",
-       "ocean_proximity       0\n",
-       "dtype: int64"
-      ]
-     },
-     "execution_count": 38,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "train_set.isnull().sum()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 39,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<div>\n",
-       "<style>\n",
-       "    .dataframe thead tr:only-child th {\n",
-       "        text-align: right;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe thead th {\n",
-       "        text-align: left;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe tbody tr th {\n",
-       "        vertical-align: top;\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",
-       "    <tr>\n",
-       "      <th>ocean_proximity</th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>&lt;1H OCEAN</th>\n",
-       "      <td>7341</td>\n",
-       "      <td>7341</td>\n",
-       "      <td>7341</td>\n",
-       "      <td>7341</td>\n",
-       "      <td>7341</td>\n",
-       "      <td>7341</td>\n",
-       "      <td>7341</td>\n",
-       "      <td>7341</td>\n",
-       "      <td>7341</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>INLAND</th>\n",
-       "      <td>5227</td>\n",
-       "      <td>5227</td>\n",
-       "      <td>5227</td>\n",
-       "      <td>5227</td>\n",
-       "      <td>5227</td>\n",
-       "      <td>5227</td>\n",
-       "      <td>5227</td>\n",
-       "      <td>5227</td>\n",
-       "      <td>5227</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>ISLAND</th>\n",
-       "      <td>4</td>\n",
-       "      <td>4</td>\n",
-       "      <td>4</td>\n",
-       "      <td>4</td>\n",
-       "      <td>4</td>\n",
-       "      <td>4</td>\n",
-       "      <td>4</td>\n",
-       "      <td>4</td>\n",
-       "      <td>4</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>NEAR BAY</th>\n",
-       "      <td>1854</td>\n",
-       "      <td>1854</td>\n",
-       "      <td>1854</td>\n",
-       "      <td>1854</td>\n",
-       "      <td>1854</td>\n",
-       "      <td>1854</td>\n",
-       "      <td>1854</td>\n",
-       "      <td>1854</td>\n",
-       "      <td>1854</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>NEAR OCEAN</th>\n",
-       "      <td>2086</td>\n",
-       "      <td>2086</td>\n",
-       "      <td>2086</td>\n",
-       "      <td>2086</td>\n",
-       "      <td>2086</td>\n",
-       "      <td>2086</td>\n",
-       "      <td>2086</td>\n",
-       "      <td>2086</td>\n",
-       "      <td>2086</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "                 longitude  latitude  housing_median_age  total_rooms  \\\n",
-       "ocean_proximity                                                         \n",
-       "<1H OCEAN             7341      7341                7341         7341   \n",
-       "INLAND                5227      5227                5227         5227   \n",
-       "ISLAND                   4         4                   4            4   \n",
-       "NEAR BAY              1854      1854                1854         1854   \n",
-       "NEAR OCEAN            2086      2086                2086         2086   \n",
-       "\n",
-       "                 total_bedrooms  population  households  median_income  \\\n",
-       "ocean_proximity                                                          \n",
-       "<1H OCEAN                  7341        7341        7341           7341   \n",
-       "INLAND                     5227        5227        5227           5227   \n",
-       "ISLAND                        4           4           4              4   \n",
-       "NEAR BAY                   1854        1854        1854           1854   \n",
-       "NEAR OCEAN                 2086        2086        2086           2086   \n",
-       "\n",
-       "                 median_house_value  \n",
-       "ocean_proximity                      \n",
-       "<1H OCEAN                      7341  \n",
-       "INLAND                         5227  \n",
-       "ISLAND                            4  \n",
-       "NEAR BAY                       1854  \n",
-       "NEAR OCEAN                     2086  "
-      ]
-     },
-     "execution_count": 39,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "train_set.groupby('ocean_proximity').count()"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### 可视化数据进行分析"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "每个列的数据直方图"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 40,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "array([[<matplotlib.axes._subplots.AxesSubplot object at 0x0000026A728262B0>,\n",
-       "        <matplotlib.axes._subplots.AxesSubplot object at 0x0000026A729DC5F8>,\n",
-       "        <matplotlib.axes._subplots.AxesSubplot object at 0x0000026A72A14518>],\n",
-       "       [<matplotlib.axes._subplots.AxesSubplot object at 0x0000026A72A4C518>,\n",
-       "        <matplotlib.axes._subplots.AxesSubplot object at 0x0000026A72A1A630>,\n",
-       "        <matplotlib.axes._subplots.AxesSubplot object at 0x0000026A72A1A6A0>],\n",
-       "       [<matplotlib.axes._subplots.AxesSubplot object at 0x0000026A72CA7F28>,\n",
-       "        <matplotlib.axes._subplots.AxesSubplot object at 0x0000026A72CDDF98>,\n",
-       "        <matplotlib.axes._subplots.AxesSubplot object at 0x0000026A72D220B8>]], dtype=object)"
-      ]
-     },
-     "execution_count": 40,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "data": {
-      "image/png": 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G1V6TSJIkSZLG1QXA64Fq928CfhNIn7pF/+k8araNV9VWYCvA+vXra8OGDYsM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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x26a72879b70>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "train_set.hist(bins=50,figsize=(20,15))"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "按地理位置的人口分布散点图"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 41,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "<matplotlib.legend.Legend at 0x26a6f776eb8>"
-      ]
-     },
-     "execution_count": 41,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "data": {
-      "image/png": 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hqQSKBITt4HNAeQeRlih78hz8Zgls02BEBniBt/ZAdhxMnqwRCkFZmeSSSwQj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ZwKVO\nCcFPijkz1e21FCiyie3YOEQJ08ir3ZZIROdf/7WaL395iETCY8aMIJdcEuP2210WLbJpa5NcdVU1\nEUwivD4OjSJ7AAAgAElEQVQEYxiCoSGLH/zgAFbRYv+eDLM7Imx/2cLzJEhw3SLBoEdtrUYu5xII\n+EjlNXx+k/dcU8U//5tGwIAvfUn1N0kkVC6j8h2oy3WyaWgI8sUvzsGyPOrqysZkMkgE0jt5deGl\nnPGdwC8O61g4JIRoLHkMjSg1dlDzY+thu7cA/aXnL3jN80+Unm85wvbHOsex6Ctd/N8NrBZCTBx2\nvGNyKqu5alECkQkhRBB4D/AvpUFehPJIzgd2nqoxlHk9AsGHiTKASyM6+lGu2bcn4ekR1a7qwgaY\nXiq7T6ZgeAyqK6EqDj58VDoNbMt47JIVGCGo9b/6WBdcEOXxx0MMD7vU1Oi4rqCuzmLWLMmsWSbV\n1cf+Gu7alcO2JcuXR2lvt/jtb11cN4QqPPHhOC579yZobBSYpqRo5QmFwvyP6yJUV2ok81BXpzyh\nLVvhl6XS3w9fBQsPa6Jg21CwIHKEHiiTpVDwSKUk0aggGHxnLFSJx8tyLG8ICe5JMial6qwfA9uk\nlN867KV7gRuAfy7d33PY87cIIX6FSsAnS8bgIeB/lZLjoDoh/o2UclwIkRZCrESFz64H/s9xznFU\npJR/Uvrz74UQj6Oksx6czHs9lZ5JI3BrKW+iAb+RUt4vhFiDEov8C1SC/pOncAxljkAIjRnHSDDu\nzcCtPeD3FShQ5KVuky/PDhDIafzrr+GADp4J118IZzQL1h6Yy6gFPQIeEfCpVmh9zfKKigqdiopD\nFTIf+9jkr5KrqkxsW5LJuOzZY1FREURKExUxBfCQUqcY9NHS6DGtSWc4Jalu8ZErwMdvhHklFYAN\nm1TFFsCGF5UxkRIefgJuvUv15lp1DnTOgD37YeFsVQ59NBIpWL1G5ZNmNNk8+nAGy5L4fILrrgsz\nY0Z5In+3IRF47km7EDgb+BjwshBiU+m5v0VN8L8RQnwC6EUtlQBVjfU+oBtVGnwTQMlo/APwQmm7\nbxzW7fYzHCoNfqB04xjneB1CiIpS+O3wzOLLpfsIcNzOukK+C2oXly1bJtevX3/8DcucFB44AI+M\nZygE+xHASM7HuXUeYzunsbpfQwvCSAFCEZjWCM0B6Cx5LuMW1Pjhk63HPMUbQkrJmjVJXnopw969\nGpFIhG9+08JxDk7UFpDFiPp4z8c1Lp+js6fH4bqb6qmOC1obDx1r42b43V2AgD+9HGprYfXT8C/f\nB3SoikCoAjpaYHqrMhJfuBHqShXWmYxkcBDq6yESEfyfW2E8AbouefyBJBedLaiu0hgc9LBsyTe+\nHsM0p2rG5u1BCLFhMnmMo1GzZIn84NNPT2rbn0Uib+pc7xSEEPdLKT8ghOjh9bkYKaU8xiWVorya\nqszrCBiSA944zfjR0fB5Pnba4+wJFthVNEhldEwL2sOSLWlBb0EwO6Th08CvQ+5NKPNmMi6bN+eR\nEhYtChKN6gghOPfcOOeeG+eXv8zxgx9kcBwXlQE6WAoM0rUI5Ez27/c4Y1mQ0+cJ8gVYs0Gtbl88\nD5YsgpYmdS7LUUbkhU0SKwsjY5KRgMBfIdjfB24Oqusgm1fbZ7OS//gPj2QSolH45Kc0hkYF7c0w\nNGDTu6/IHUN+tu/xkBEdXMnjLxR44LdBKo8i7S+l5BjJ2DJvAwUJO6yp9T+RUn6gdN9xoscoG5My\nWORJM45AEKOOJdWCioTFSCaKBKqDBXpcyaDoJ2s3oJtgGwb7xzTqa116sia78jArqDFYgDOi8F8v\nQ28KOmLwvg6on0SlrGV5/PjHowwNOQgB69Zl+exnawkEVMhBSsm3v51l/fpSW18slIiCAUSIRxNE\nCzpnnRXlve9VC3kfeBrWblahLE3A4vlQV3vwfHDp+bDmKY/+7UoSLC89wnGNWKvG2hdh+UJe8WxG\nRiCZhPZ2wb59klQSZrbD9m7Js4+lGBgU5LIOtIWhoIMueH6Lxi1/5XD7D41X8jCO47FmTZJnnpkg\nn/dYuDDCxRdXU1lZXgPyTsAvBdPl5MKTz53isbxVCCGO2bz64Cr8Y1E2JlOcPGk28Sj9HKBIgTAV\nnGtcybUz8+zMJggTYCSwh00HOvAKJkIXyBgIXJwRjYgQFP0ue21JralxThw27lVt25si0J+BH2+B\nLy2F4zUNHBpyGBlxmDZN5UJ6e4sMDtqvPF63zubFFz2EpiNfiWnbaJpFU5PLzJlBvvCFapYuPVQB\nkM0rxZWipVa6H47PB+evkMR9Es8T6Ag0D6xRSfsSCIShrepQMr6+HmpqYN8+SVUVNDTARy6HJ5+T\nrH9GUFEdJJe1S4qbQFQDB55bp8qq60tG7MEHx1izJkFzs5+qKsH27Tn27y9yyy0tBAKTW3nteZLu\n7gTPPtvP0FCWaNTHypWNdHbW4PNN7hi2LVm7VpLNSs48UyMWm1pX40dHlFpGTyn+d+k+gFplvxkV\n6joNldg/53gHKBuTKU4f2zlAHxomMarJkOAFHmOFfjH+ih562If0ctQSIxu3Kc4sqe4GLHy1KfK2\nzZy6US6pbeSz8UZeGoHnHGgs9VavDcG+FPQkYd5x1IfDYQ0poVj0EEJ5E+HwoURod7eDA4jOICCh\nawQc8OIBtJYQ0xfpzJxpMlgqgKyrgfefB7qmtLeWLnj9OTVNrXyPhZRGmGYoI3OgD6ZPhzPOkExM\nSCorBcGg4DOf0RgeVrmWYFBNOINJjZY5EXb2FaE6pgxJQKhfl5SEQwK99DYyGYe1a5O0twfQdbV/\nY6OPffsK7NiRZdGi43d18DzJvffuZu3aAeJxP5GISS7n8Nvf7mTdukFuuGE+weDxvZwnn5SsXi0x\nTdi71+PTn56y4oavRgInLwH/rkBKeSFAqYrsZinly6XHncBXJnOMsjGZ4uTI4OIRKsnwGJjYZNjN\nHwjiUk2eGm0W2bDDbtehtWMvRtEllwxTGZ0g4stQFcjQFDlAnosQhI+4jGoyaYGqKoOrrqrk3nsT\nSAlXXhmntvbQpFgo6AhTIP0CcMEQIPMQNaExxD0Dfn5yuQf7HEhYBGsllcsczjpL4ysXVeA7LBGe\nSMAdv4KxUcGcORpdWyXDYxKJpLZJZ9FSuPlaj7XP5nnhBY+ZMw0+9rEAgYDg8DW0ngc798GZK/w0\ntfu5/RHo2+2pOpyUJBCCD16uv7LQM51WgpcHDclBDEMwOmozGbq6RnnuuX46OmJomjqOz6dTUeGj\ntzfFo4/28oEPzDjucSYmJOEwxGIqhFfmMLwp55kcZO5BQwIgpdwihDh9MjuWjckUp5pmHDZgo2JA\napo+QAIfDgV22gVetMKEDIdV7ktsDC0gaOaIxtPE/eOk3RjGaBsxCuRIMT0eJmzAcA6qAjCWh6gP\npk2yjdqSJSFOP13VFR+cKJNJNfF/74c6jY1++nfkVSfGQhpR6SJjtfRmfKqYMmtDOgMe5Pca5PfA\n7x4y2Pq0zfe/6uO8UmT42edgYECt5h8f1/j8n0vWPKOcitNPF9x0A+zZ7TI25tHRodPd7TA87NHU\n9Oqrd02Ds06HZzeplsQ/+Uf4/+7T2LsZhAcXnQ1/d/Oh7SsrDTRNYNsepnno6teyJC0tkyuXfuqp\nA9TUBF/5fA6nqSnCunWDrFrVdlzv5LzzNHp6PMbH4aqrpuzk+ToKHuzKvd2jeNvYJoT4L+B2lI/2\nUWDbZHYsG5MpTguzmc1ietiOiY8w1XiMYpOj18lze/YyEm4l9cUR/KG56J7DhKhCotEk+6jWJkh7\nHk+N1dFV8PORBvjEQnhorwpvTY/BJdOOny85nNdOknfdBU88B76wwJeNcNoCiz27DKxGDd00yMeq\nYZdAWZCMmuE1wHMAHyQLbH3A4Jshh4d+qhLhoZBKwCeTEI7AjTcKrr5aeRoHJc2qqzWEgL17XcJh\nQSx25NDHeYtdZLZAZUzjzAUBZrcLdoxDhR+W1ikjc5BAQOeSS6q5554R4nED01RSMTNmBJkx4/i9\nT6SU9PdnaGs7slK4YWhIKUkmreMak/p6wV/+pVaStCkbk4MEgFmTjHKtO6UjeVu4CbVu5Qulx0+h\nVImPS9mYlGEZF9LCbNIkCBBgApf9bGKnU8VuZyZRJ8MYVWT1CJdZ95IIVlGljVHNMNVeEhkbxnb+\ngolcFb/sg1tmwA1HyE+cCFJKNmyw6R9wicYEQhr4AyYLr9LJd0QY3yro3SFAeAghkQFT9Y4vuiq2\nZvqgWISi5IU1FmvXuZy5ws9ZZ6q+8BMTcN65atPIYc31sllobNT5sz8LMTDgMnOmQTj8+gnX8yS3\n3jpBf7+N44BVjHLhhRHaj+GJnXVWnJoak+efT5LNepx1VpylSyswJtFHWAhBIGBg295RE+2ep7TN\nJoMQAr2cKnk9b6j7+R8PJV2uHwD/LaXc8Ub2LRuTMgg0GmmlsSQJVEctOVIkpUPOCzHT20NeBEBK\nho1aYmaGoUQLeTPMAv+dNBeS/M5LUuGfYDBfiVcqwz0ZPPZYkcHBAskRwVhKEgkbLLk4TOd5BoM1\nkqdT0PuyAM1FagIqwlC0ISAhI8BSMvQgyOck//adBDf9ay0vWRpaB5xxOsQrVT8T21FexJ2/h5de\nhnAYrv+ozsqVR59tCwXJwIBNe7tJMumxe3eRCy88fsvX2bPDzJ59YsrCK1c28NRTB2htfb13MjFR\noKUlQlVVucPjCaM0SackQojLgX8FfEBHKV/yDSnl5cfbt2xMyryOAHFW8mnuE+vRNI8MUZDQTi8p\nfyX5sRi27Wcw28SGmv10+u8gnEqwqZjgwgoTTUyuf3YmA7mcqow6UoLetiWPP17k/PN12tsFL2+X\nZHM2l650uWCFwXf2CGxBqX2JUDZDCjD8gIBgyUJoITBdihNpHnrSIvdAjvddEkECDw3BPetBH1K7\nGzaMdMGKuSpJf8+98LnPHv09hEIaCxcGeOmlAgCXXnrCjeomzYoVjWzYMMzQUJa6utArix5TqSLJ\nZJEPfWhSIq9HJZ1WizKnNFPUmKAacC1HiUgipdxUks4/LmVjUuaICARfMju5yxhgurWbuJMkrGUR\n0mbQaCZViCMF1IgxLNNgceAuouEPcnZ9HMnZiOOIvvf3w3/+p4pAnXceXHrp67dRnQolPT2Sn92a\nIpspIvFx23+YXHFRhA+3wJNNQBQY0wBPWYSDbU2EBiGhDEoxjaHbFBIuvQ/n8F8WwfNgzyZYtwMa\nBVhjUKVBKg0NKagx1fqU12Lb8MImGBqDhfPg6qvjnHmmjdQFNXWnfuFhRYWfT31qIXff3c3u3Ul0\nXeB5kurqAJ/85EKmTYud8LE3boRf/Qquvx46O0/ioN9NSKZsmAtwpJTJE1FlKBuTMkelRg/yZMjm\nfmsTPnuQ2cWXwLP4eexa2s0e/E6RUDbH78wr6azvYYG8lYDeToEgRVpwsKigFh+vr1LatUtNys3N\nsHbtkY2JzyeYNdvHLbeMkMv1KFlwAf/94HR+8xs/115r8tF50N8CuzMajGvgeqUW8BL8EtIWSBvT\ncBAaSAPsjJopBkZgUzdoFuxeC/kU2EWIReBpA85vgI9d9/px3fpLuPV3MKFBVTV85kOCD73Hx4E0\nDGch8hZoO1ZXB/nEJxYyOponlSoSCBg0NobftDRLNArxuArxTVUKLuxKvd2jeNvYIoS4FtCFELOA\nzwPPTmbHsjEpc0zqjBgfDwF6Dc7oMGk7xawd3fwk/mmiIsnPEjfhVvv4SuBfaA2PE8TCZjNJ9iKA\nABE6uQCTV+vSd3Sooqu+Pli+/Ojnr6nz4dhjys8RQaQExzrA5s2VXHutycoOuHIVPGPAhi6wUxrY\npfBWSqLj4YkMui7RdYntF8w9I8iBcXjoJRiTYO8DvQhODhCQSkAgADfdDPVxuPt+GBqGubMlnfME\nv78TehJQzILmwNqtsGQ2VEegMQ6plEd/v0MopNHWdmp/YjU1QWpqTl5+ZNYs+Nu/PWmHe1cS0GCW\n//jbwR9lNdefA3+H6jB3B/AQ8A+T2bFsTMocG60B/FcA/40WmkHSsXmw7xL2aa1o2SZybohQdZE9\nhQ4OZNvZkGvgoo5+mowWfPhJM06OFLHXNM1qa4MvflFVTTU3H/nUAKGgwO83cT0B0sHzPDzp0dNT\nIJMJsqBVY/ksMA2YvwC2vAQTBzR8aZdsrEBHm0vXi4JswiEYEMx/T4QFV8d4YTcgQTpga4faFQuh\n1tp4QGUMbv817O312L3L4tafw6oLBZblZ2wcXAfccSjk4Qc/gLAB4bBDPp/G8yS2LbnwwiCXXhp6\nU/+CXM6jv9/DNKG1VT/i+pIyJ5GpHeaaX7odVFC9ArgcJatyTMrGpMzxMVeAuQLNe5742H8Rrs7j\nFHRszw+Ghr3fx0OPXUpfahqYcF/DTr730S1UBuIIBH6OfOVcVaVux2L5Mo0VZzfz1OMpisU8Ao22\ntjamT3eZmHCJRDSuXgFnz4bRNFRcB+01Ak0LcfcTfv7whM3KCyJculwwa4ZBqFrnoRHB75+BQlpF\nwty4Cn9pIdBsCEbgwuVgAn394DkumYxHc5PGs2s9fD6XloDOgAehGGQHYVYbVEThD38oUCx6DA0l\nsKw8O3aEWL68jaqqo//UPE+Syai1L4WCIJNRzbwyWRgd8/jdbzMkExLPkyxd6uOqq4JlpeFTzdQ1\nJr9Ayads4Q2WIZSNSZnJU7GCuL+Zv/JtY8+u3ezLteOkTfx9afY5s2AGoEl2Tczn87+NcPfHRmhg\nBgEmV911JCIRwa9ur+Rb317E/feNUVlpcPbZPkIhqK5WJbtCQHOVuh3OlRfoXHnB68t6z4/AiiAM\nm5AJwoAOTZ3gjinfftoSCDbBvdshJUF31ZqU0XGIhiUrzxYsmFDlxNOnw8QBCJTCIpblsW+fhRB5\nhDDZuTPD8LBNvNJgoACehMYAHFxSUihIbrutyO7dHrm8ZHBEZ906l8ERgRE2qasXzGjRuer9EiEk\nzz9vEa/00dRsMH2aCse9m/G8Q17hO4YpXBoMjEgp7zuRHcvGpMwbw9/C8uYWrn80ybdvT1AUDqMz\nqwl2pqlKJyHoMdZQhV0oUFc0iflrj3/M41BVJfjmP0T40l8EefrpLK4L55wTIhQ69iwk5ZFLjjUB\nLSFYWKEm9/4YtC2HxgpYPwy6qeaSe9bCzhTYWw0GtmuYOlxxmeR/XK6xY7cSkDzvTNiyBe65B3Qd\n2tv9DA5mSaUgny8wc6aPcL3J/90NQ0VAQsyE69uhIQBdXQ7r17s8/bTBnh6HoukpS2NCMVGgJ2Uy\nPu5jyWkWrY2w+WXIWGptTEsTfOL6U29QikWPNWsmqK/30dl5cmqG+/rgjjtUmPN974MVK07KYU8K\nBRd2Tbzdo3jb+FpJTuVR4BWd7cN61x+VsjEpc0KE7BjekIMjPfw1RQLDLrbfgHFBvCZF04wDuJkH\nAD/4T06NaVWVzhVXTE7ka+1OuGONmuA/cQF0th96rSYKK6bD2t3KsLRVw6cuhC2D0JWC9iqVv0+P\ng2PDtjFBoF7HsWDzTrjrfvjyLWCUfj0rV0JLC6RS0Nzs59lnq7jjDh8VFQ5f+UqMhxIGCRvaS6mT\ncQt+uR++MFOVRj/xhM7wMMgglHRg1H3YgJxNIa+xYSOMt7m4UqdzgY5pQs8+6N4DnfNPysd7VHbt\nynHvvaNEIjpf+1p40qvrj8WvfwNPr5Ns2uzyo595/PM34IYb3hktjgMazJpkTcMfYQL+JmAuKsp7\n0D+TQNmYlDk1XPEBePiRSp7fnSRcN0S4Ic9wugnNdPGSGo3VB/BEBNx94M4BzwXz2JfQrivZsMFh\nfFzS2WnQ0nJik1b/OPzj3ZAoQCIPe4bhts9BRWkyFwIuXwKnt6tui82VEPJD9yhUlCaRMRf2tcHu\nYZARsKuhAGxMg7sH3jcACw9rTdzScujvyy7zc9llKu6VtmHvTmg9bHKq8kFvDkaKSksrEPCUF2Vq\n4HiAVNl9XQPdI2DkqYwFOH2RRrTK/6o2wN5bEI5pafEzb16Y1lb/STEkAC9tg+c3uKQTFh46f/8P\nRVauNJgz5x0Q85raYa5FUsqFJ7Jj2ZiUOSHq6+FXt2k81lXJN5/0kTS7mNmxg0LSj+Z5nBHcRoWU\nFFMa/hf/CVwLt+NcevpgvLub+LRpTF+1CuOwGM3DD9s8+aRNICB49lmHW24JUFf3xieXgQSM51R/\no7wDu4ZhInvImIAyKO01r96vOgx7xsA04TeDkDU9ZAWgCRxXgg2OJ9hQI3jP7+HDbXBuK5zeoib1\nfYMwPA5VUTi7Uym7HMyNHGyq7XmS1EiBZEZiNfkoFjVWrdJ48imH3jGNYlaqg3keSAfhZqgIwEeu\njfHeC+H7P1YeCSjF4xkn3GR18sTjJp/+dMvxN3wDtLar6wuBMqa2Ixkedt8ZxgSmcgJ+rRBivpRy\n6xvdsWxMypwwhgFnzgF/xmLvgXa0IYEvmKe6ZYzOqkU8WFFJ25OPMt0XJ+5rJvHQj+kbbsJf10bv\nM89gZbN0XnPNK8fr6nJpatIIBAT79qly2KMZk+40jBZhURyCr/kWT6tVnkamoHz1thpoOGxReBHV\npN7/mq//slZ4bi+8lPBI+zNkdRenKgz1OgwIZRFmSBAwjOCn3aqrpExApR+6+lSJckc1PL8T/uZD\nEPTBkjisT4C+P0nXk0MMj9nEffA/b3MwjAiWXc9ZF/hx1gMjkE4ZSOERsMapiLosW17DJavUQsJP\nfxy271Lhubmz372LC6+6AtY8q7GlSyI9ycL5BgsXvkOmo6ldGnwOcIMQogeVMxGAlFKWS4PLnFo2\nDsOzQYdIvEDRDWJF/fQfaOS503uZbzYwYkp2mFmaNZ1ApJ9sh43lFqkIz2N066svfqZP11i/3qWi\nQiIl1NQc2ZD05+Ene8CRcCAPV7W++vXqKHzro/DTp8BnwM0Xqda9fUzQxRDj5JASPDtEm1vP6WYl\nFQbUR+HGM+Djz6cpFBxSyTCyoEGHhAqhZFpqUSKSpiDtg7VFiNlQkVQGzNBhzziM52HpZvjgGXBx\nNTx8R4Y/3JlAFxqxSJhI1GFrxiBtaiTcLDHLBxGd6UG4+EwQPpNksoH5s11MkWdszCEcNqiogOVL\nT83/8q1k8UL44Xc1nlrjx294XHapTjz+Dip3nrphriNoUUyOsjEp86Z45ADkekNoukGgNkcxHSAz\nEiY1FGV7Q5KdZ1xAzfBewrERKpvnY25K0RLYTc4t0ipWvupY73+/j0jEZnhYsmyZftSciSdL0luU\nUgwlJJK9dJNgnJmtc/nWdYfckW0MspEDRPFTLSOsTcGAXWS1sQ03EWNxHApmhHTUwH/WMM0Jh9za\nmXipEH6ZJ18MIUOG6qBoARMSagROCMZqQR8GnwVhU43J8+DR7XDmXNjwgsfDP7ewcpU4UYNRXaNr\nQiANQTjo4CNBQ1WeyOwK2prhs9dAY6WaWHt6PL73PYuZ041Tvpr+rWbOLJgzS0MVHbxzKNiwa4p2\nnpRS7jvRff+4vp1l3nJCAuj1kanyYTk+nAkdaZicHfezmwgiZDLaOEKVu48DmXaMegs9tY26xWka\n6ue+6lh+3eXiFVkIhpVLcRRaQnBtu2SXkyEcT/AQLu1EqUWnh13oGOxmO6ej6k1TFNhEPzWE0dHo\nK8JeK0/WHCSFSzqYY02imZrafRh4GBEbwzUJxXP4tRzuy35ytg4OMIrqniSkSsq0AkEwopBOgF5Q\nlWBNlRANwnd/Cc8/6tA/EcINGjhFB3I65AUUJGndhNpanuotYA4I2vfDrGb40gfUe+3oMPnrv45R\nVfXOmnD/mAnoMGuSFdB/hNVcJ0zZmJR5U9y8EP72YQ0KAisdVN+oQJFpLa24QBd5HB3yMohPt4g0\n5onXQWVNE2PmFtY/q9O1epx5/ffTau0h0hTAG00wHj2NyjMvYtYll+BJl2I6Rbi6DsPvRyLJxPsZ\nTvcQnbAJBKM8H8kSRqeGIC554lS/MsZ9TJTEhNWEPORNMCgSODhkdR+636IhMoDuufidIsLwyGtB\nzGAeXdfRQ0US4Tj4BNilsl0/qi+vVMdMCmiKwjQ/FIqwYBqMJ+GxNRDxCZxpAjcpwC55N2kgIqBW\nqH7jXgh7GnRvhR/dBTecr8J1ALW1hxZejo3BE09Aa+shTbPRUYeuriKOI5k7109z86lXLp4sjz6a\nZnjY4Zpr4u+ebo5TO2dywpSNSZk3RXUYNn5K54Jfe6QCLnXBAj/58H569Cyr6GQvObaJGsbMHHPi\n24m6GeoKfmrkQjaue4mh4c3Mn9lNYImNMThA7rkUO5ta6I7sIPufj9F25z8R+5O5iJYYga44F51x\nC+l4mN8NPkXFnm0ciOvEcwXqLYNERzv19eeyVGsi74T5arLA00UXoWmsqvBzTkjiYNNr7Wdf/yyq\nq/qpqx8goFlkCZLXArh+k6ITIECeUDxPYqgK0V7E7LOwiz7Qhcqb+FA5lBKOA/0FlRiv0qC1Gn7/\nAhRC4EU1XEdCHrCBdGlSjQg1aXkoj2cRUAV7D8DWPRByYccOJa2ybKlS833wQejqgvXrYdo08DyH\nH/5wAtuW6Do89liOm26KM3PmO2PNRne3xeCgjWVJgsF3iTGBqZwzOWHKxqTMm2ZxIyS/qPEAW7Bx\nkQhMdOL4+TJzSOozyNKP61+JU9yOXTXB7s3dFFrGKcxrYK13DhkzTNPOHdQuK+DEDeoyBVKPdDE8\nkKJ/nYm2bBnRQI50+hcMRJeT7+8mg4NeWYEQFsWwxWhqnNsjvewdqUBqWTI+E9s1ka6PHSN1OHX7\naRN5NvW2EJQZzqh5Hk+YjMlKgkJHAKP5MJbjI2TmiOtJvEaB1HUiS1JMDNSAKdGEiycNCKLKxSzw\nCkrXyxcAoxG25GCHCzIGhaSukvYzJWwSKjwWA+Ko0FkOZVRK9cO2B7//HQQ8iFXAtu2w7gX43GeU\nYXn5ZdWnPhSCe+7JoOvQ2Ki8kVTK5b770vzFX1Qf+Z/1FnPDDZU4jiQYPHaYznXh8Sdhx06YMxsu\nPMyTEmUAACAASURBVJ+3r51w2TM5IcrGpMxJ4yxmspFeXFxOpx2jFFaqxkc100CfhhdaxIjVxdo9\nP2H40jq8vIZnaPjtInZlFMe08eeKFP0+AtfPYaJbEkil0boHsFY0ky4Os9Xeg39fAm0ihR42mair\nYL/ZytbAfIpagFSNh+7Z5MYC6MJG112EUaBv5EXmmU9widuMryKDobuM5mrxazZ+z0IzIlQNJ3ls\n/woCNXkW+LYQdXzUNA2jtTnsWD+P4WIjhuaQsaJIqYMLZg5CBjTXwIIWJcGydgDcCPiqwZKgDWt4\nERdCHvgN5aEUUFUEPlQITQIp0POQGIIzz1Cfa1UV7O+DjS/CqlUwe7byUiIRSKdfPVEHgxrj4++c\nmTAQmFyu54UNsPoxqK9T95EIrDxGa4JTTtkzecOUjUmZk0aMEBcy95jbaJiEip3sP7AA091CKhYl\nkCqQNONYAR3XM9C0Aq5Po5B00GyJZtnoEQNb0/FyY+SkZGTOIgoFk0iVSzBQZH+oBTyJdNTlvWuY\nBPUk8YF+mivGGahoZcSM0+uvYnpoJ5WhURKZavSsh88o0OXrZCjVyOBzTdhDAXKxCC/OOY053ib8\nWhKjwWSGfz/1RoIMFQy6YQzHpD4Al3ZC1wRkEnAg5eL4HebNtRnZFiKf15CNIDMamgQv6kKzLHWA\nRE1aUVRBU49EKwiaTKipPPSZpXNwIA3rX4Kzz4L2w6RhZs82Wb06Rzgs0DTBwIDDaae9+9Qfh0cg\nEla3TAhGRt++sRRs2NX/9p3/3UrZmJR5ywmFdBx5Bvm+fqKzshRjPtoSe2nfvZPdM2aRjddgptLI\nPaNo1XU4712Ad1ojETfLuFfDyGAj+2OteFENCbTre7AIYAoHW3MxPAtHmIiw5Eyzi4biIMNiP+eH\nH8Od8LALKeqq9lP78hhzd25hZCiML1jkB+2fY9BtxtM1MCUFwiQro8x56j58d+UxZ55HLFbJqGym\nyjSZ31Dgo/N3MC26G6kNsD1zAM0e5bepS9mgdVA3TyN3IEi8V2NIb6CYDMASQyVW8iiPpM+DtISz\nJeHqJG3PhrhsURB/BvpT8OIByfMvS7IZQf0OgaPDJz8E1VWSri6J5wVpaXHZv19p8nV0mMyeHWLT\nJo+2NkFV1bsjT3FaJzz/AuzrBQQsXPD2jSWgw6zjtEY4SLma6xBlY1LmLUfXBZctn8atv7+Mnsv6\n0GvTbMzFWZBs5KrHbsOsM7H8Pnwr38dYp8uu6S66LOKlfWzf20llMcGYr5q4m2Aw3IDMmYiAh+UE\nAIFEYGAza3w74coUVtjgDN/z1Fhj7EvHGQx1EBgNYOcFvZtHSRRChLNbWeZfz31zWtA6bOb4trFw\nziamPf4Yxq5evEGLTTM62H/6TGpHnyZSmSMRg+/lYuhDNi3+URZUdrNVn8tgk0Xc6qXRswjXFXGk\nTn+sma2j80nGqsCVsBflmcwC6gRMk+RFhMGFEzyeDHLDYvjhnbB3r0c+JGCuJDMs+bf/1Ni5GxZ0\neAzvh2AQisUwl18epqMDfv5zj3//dw/wqK6G66/XmTdPkEi4PP10FseRvPe9UeLxQz99z5N0d+dw\nHMns2SEM460vQ57WDp+7WXW0bKiHxkaYmJBMTPD/t3feQXJVd77/nBs6d093z/TkKE0QygIRJCRA\nIJKIfmB7jQ0sXhucdr1evyrv1nqTn3fLft6q3S0HHIAF/DBe48UGr8nJRBkhEMpZmtHkntA53nvP\n++MOSKAsNBoN3E9VV82cPn3vOR3u9/7O73d+P2prwec7xaLoLHMdN46YOEwJ550XIR5v4eWHQxR8\ngkahoGW6eKthJTdfoxOKzAPFXq45hzhj5MjFU2x97VlyzRAI11IIeokkkswXb7E90MmAUktZGOSl\nh/n967l15CdsnrcI4VHYp7QwSAPn6a/QN+imz92M2jdAn1FFqSlKqi9JXbwbdaHJzBnbmeHbg27m\n6Yl0kFnWhb9vmI49r+Kf7yW4dxeBjKQ46GXwjPn0RmewgRaelhdSp/eimiaBbJaoOcqebCfrRxaS\nHfSjxw2oNcGvQhR782ONBCmgIJAeBSussekN+I8cNC6X9CoGhHXwA14o99sX/98+AZ+8Etwuu5jW\nG2/A2xvh3gfB71MIuC02bCgzOFhmzpxR1q7NUVfnw+PReeQRha45AVatgkXzFJ56apQXXrBzri9Y\nEORTn6o96PN66KFhMhmTW2+tnbRKj/X19gOgp0dy990mpimIROCOOxQCgVMkKI4D/oRwxMRhSlAU\nwXXX1XHeeVF27MhQLFq0tvpoazvjoItVlBhRgBa4+gst/Gj1q1zU+zzd/haayn30VDfQPdSEx5Vl\nTKklmB/l+t//nLiaIl9nUlmTpcGbpls20eNqxquWSJqSckUE6U8T6hsg2dTMUGsLnRVbudb9CJuN\nWbypn4t7VgprvIzmjWO9PUztfz1J5DOtRIvj7I7HKG1KEVqaJmf40VSDftmKVVTxR7JkIn4SIxUU\nd2sU+7wUpYCMhAZsr/yYhJcsaFChTSBbVZI9AdQ4xHMQmyWItkF6ZGKDZN5Oj14ZgW5VYJoSgFIJ\nimX4/o8gV1CxUpJ0ogAZg3UbLJb1mbh0i6oqC9DYtlvhxY0mv3nW4pNXGJTyaerr3bjdgo0bM1iW\nPOgziMfLZDImpnnwc5PBmjUWui5oaBDs3SvZuxfmnpxKBseGIybHzaSJiRDCA7yIvb1LA34tpfyH\nA57/PnCblPLEy/A5THtqatzU1LiPuf+lkSBbz5zNc2v3kgw2sMU/i43+2ciMBqpEagqB4hhJ1YO/\nNwtuDWEaCGmiYyBNhdj4EPtiMSr8WYwbz6G/rOHtHWDB5rtZWRWlP9wJAY35xY3soQFTMVF6M7z+\n6S+yRPkjFd5B4hmNTGMne3OLMXuDWJYg0JzGzCjkekIkZSWmUMFtYRZc9p6UJJARsNmCnAleYYcF\naxZUqbBBwojArMtSNgVWqZ9IfQQjWYGIW5zh0oieU0ZVJF+7Q2PNaxIhQNMkJaFiItGDFqMuCUEP\nZEyMHpO3Nwj++Vte0mlJoWBhGgqFAlRWCuLDFj6Pi76+HABz5/oPKRaf/3wdlgW6fmqWwKqqBOm0\nxO2WSCkJnpyaXMdEoQQ7ek/d+T4sTKZlUgQullJmhBA68LIQ4nEp5WohxGLsKHsHh+NCFYLbauvY\nm0rw066FFLUAKHZ6eISCMC0qa8d4ft4qrn1xK/Vr19F3+VLSskQwnySWGWbGjrcYifuJh2vpKG5F\n/+1WlC278Na7WTd4BT2tbciIil+VqAWFYbOZwrxm8q4AA5leZmjD9IVnscuag6jwUCp6yaS84JWo\nOYmFglHSQIBUNUxFsXe557FFRVcgZ9lpWYYnJla20EIlDNOFu73MTUv+H5XBUXBBn3ITVYFWzmiF\nP5kLUgqiUYUlZwvGxyXbtkm+9R0DIwPZ0ESUWN6CgAJ6CZfbzWc+EyYYtDdubNyYxjdUZtlcia5K\nmpoqOOusiokd9IdOQ3yqROQdli4VFIvQ3S1ZsUKhpeXU+Uw8GnQcY4FQxwG/n0kTEymlBDIT/+oT\nDymEUIHvATcBH5us8zt8eKlA59LZ83ghv4Ut3gUYmgsZtNNl+USaqMxwZu51RpYvouHF1zmj9tck\n6uqpyKVo270JVSmw4Omn0Nap7NpbYN+gRIup7LrgajRdoiQLlD0hBkUd8d01FCoCSJFHWCabC2dS\n4bEYNFuwTI2gnkXHQvcUSOyM4KooIgyBUCSqy6CQ9VA2XPatlRfb91EJlFRImvZyiluAaaH4LdCg\nJtZPVSBO71AT0egISfeb/O6uFi67UHB9p05djf0+VFcLnnzS5Lv/ZrCnx3a9mAXQYzqGBrJg0FAn\nuP4a17tCAvDlL+s89FCBYh5KApYs8dDefnqteOu64LLLpjASzVnmOm4m9Rs0IRxrgXbgh1LKPwoh\nvgo8KqUcEIcq0O3gcAxcMf9Kune+woPiTXqsegqWh5CvwKxwicv7wrT9z17aK4dYt2GM4Iw0vtFt\nICUpvy06A4bA4ymTV+yNhYZpkil70ctllKLOWKEGvydPqegms62CgqxCLLQwyi62m2WalH0MG7Vo\npoHMKMz07eTlPctp7diDS5TZ625FGhrJzVGoVO10KTr2jncBtAvQVcib4JeoKQszqyGaJDnDj1lU\nqHSPEKhIES9VkW8q8sh/uvAlFP72L2BWO8Tjkp/9zGTLdhUrAJQs2CfRCgaBgMbcNjerLnbzhc+9\n16q48EIPjY0aY2MmdXUqjY2nh5Bs3g5SwpyuKR7ISay0KIS4B7gaGJZSzp1oiwL/BbRix/V9Qko5\nLuwL4n8Aq7AXQP9USvnmxGtuBb45cdhvSynvm2g/C7gX+1blMeCrUkp5uHOcnFkdmkn9FkkpTWCh\nECIM/EYIcQHwceCio71WCHE7cDtAc3PzZA7TYRqiCoUvti9jpSzxtDnOsCjQSAXL1QrqfUnWhOdi\nVs5hbvuLdK/tJbosj5kuoRUlhqkRChZJd0CmDKUxQW2ozJ4BD9mVHZgyjO4vkTF8pPGTT3sQTWAN\nK7h6Slzie5o52hYeL17FHrOVXNlDyqqgo3YHNz7yMEP1NWRrAmwdm00x6YcAUA8MSHtzosS2Rqrs\npS9dKaFGLBTdwgpKRuLV/OrZm5jbtJ7h7io2FOdjjSjIrOSxxyR/fpvAMOCR38ErGYFVq9h7VsIK\naCbGZpNyWuIyFNIJ8W6t+gOZOVNj5syj//wHB2HzZmhuhvb2k/sZ9vRkqK314nLZVtPTL9o5zqZc\nTOBkWib3Aj8A7j+g7a+BZ6WU3xFC/PXE/98ArsQOFu8AzgXuBM6dEIZ/ABZjf3vWCiEenRCHO7Gv\nk6uxxeQK4PEjnGPSOCW3JFLKhBDiBWAFtpWyc8Iq8QkhdkopD/qaSil/CvwUYPHixfJUjNNheiGE\noFO46VTeF8pa56eys5Oh3buJda6kc3QdDMQRLaNY/gwCgXBVMLzbxVA2i1EtmSP7qBt6jnXPpUkE\nayls8bKjsYOcP4BSJzGTKmIIbpj9Ky6J/IF6qx9XoMS3R/8Ot6/AsIyh6ILqhUPMH97I28p8iobX\nzsFlQXVzP2l/iNKYB1U3scISAw8MahiKRAmWIWhRTPghr9Kba6a3v9m+P93JxHFMZFHhpR1glOEn\nL4CFCl4JYWFnIq5RYSEUhiVbDIO9LwpydRYfv0hj6RyFfB62b4eurqNXaczl4Gc/s6PFTBO+9KX3\n1rr/IJRKJo8/vo9LLqmnvd2uO3PbJ23LZMo5iaHBUsoXhRCt72u+jv031PcBL2Bf6K8D7p9wEawW\nQoSFEHUTfZ+WUo4BCCGeBq6YuKaGpJSvTbTfD1yPLSaHO8ekMZnRXDGgPCEkXmAl8F0pZe0BfTKH\nEhIHhw/KnE98gi0PP8zQ5s0IMRd3OkFwn4sZl5+PXltDOu0m1BYkdN4W+td8k9CLfcRH40TXbGRx\noMBq5SYi4RQJfwzRZmG16oTcCeYGtrDV28mudCtvVJ2Nz5ulZOkkU2HMhIsHzrqJS3LPc052La+M\nXEDR8IOEiCdJfWyAHn8rhlAp5zWMHNALUtMp1ukTyR4lDGI/ytjLYl4gKcGtUmwWPFqA1W/BJk3a\nr6mcSB7pB7ISzlCRumTIErAdvv9PGt//liQQsrhuhYIswq23wGWXHfk9zGYhn7etku5uSKWO7zPY\ntQvGx+Gss+D9K9oul8rNN3fg9e735YROYcTWkSiUYMfeY+5eJYR444D/fzpxI3wkaqSUAwATy/3V\nE+0NwL4D+vVOtB2pvfcQ7Uc6x6QxmZZJHXDfhN9EAX4lpfyfSTyfg8O76D4f8z/zGbLxOIXxcTSP\nh1BjI0Kx/QfuOrtf+tlefOMVFDNQF85TEGmqe99gcbSXV8KXctfsOxhprcRQTUxdZXOii7rcbt7u\nuADNYxDxjjKYrCFUkWLF+AtcnH4eRVqsN+dTUzlEz0ALoNKfbWBZw0u4lSLxsRi9mWYYwPafnMP+\n/FwDYiKEGPsOGewIsICAkKQ8D7QQDPmh1GxCr4SsYveRAhoEaNJe9spg10tJAkVBJg8P/LfF8rME\n9fVH91dWVcGSJbB6tb3ENXPm8X0GDz8MAwPQ1gaVh0hi7POdHr6a9+PRoaPu2Pq+DiNSysUn6dSH\n+lDkCbRPCZMZzbUeWHSUPs4eE4dJxR+L4Y8dPs4zvnkrucEupLEa1QNtI/2kCy5Mf5TEjAraSzsh\nBfsiTZh5eGXXAi6elcCllewlJk1SFR6hbniI2lA/+ZSXDnMHncGtpNt0fvb8n1Mc9ZEWAZ7fdyFq\nVlISGuWie8KqwI70srBDhYPsr3GiYQuMhW2ldIIVsChJBb0SQp0W4oxxxu8JI1MaNAJ1UK/2UjVr\nlMHNtQynaqEG6MOud1yGt7aYrF2rMXfukQVFCLjmGrjiCtBPoN7Wxz8OY2N21uPDsbfbYtduk1hM\nYf7cqco5/z4mfwf8kBCibsJiqGN/gHgvdu3Od2gE+ifaL3pf+wsT7Y2H6H+kc0waTi1Qh480iqLg\nqetib0kg86AUodJTJkCa2swwfpFl9t5NdhjvgEmh2+K5+PmkZYCi6kIVFn4lR4PsI+/2Yegae/3N\npNUg8wKb+dj5v6K9fTOVVcOgguFW0fymLQ5g31sOAxEL3BNLXOrEQx7QB8AHoXZJXa1F0C1pr9QJ\nVqYIf24c/coi1EHEPcK8hg1EoqMsXPAWAV/SDgAQ2IW9hCCTU7j/AQvDOLb36GhCIqXEMA6+IW5t\nhTPPPHiJC+yUMN/+To7rb0jyqdvKXHp9ia/+7zyl0ungNMEW8GN5nBiPArdO/H0r8MgB7bcIm/OA\n5MRS1ZPAZUKIiBAiAlwGPDnxXFoIcd5EJNgt7zvWoc4xaZyedqaDwymiet48dj31FInI1YyEf0eL\nB7xliUcd57rRR6nLDPKjti/h7UtQHd/D8vBvGF84j1FRj+gfQ8mkKLpcGB6dWalNIARCtzBMnf5I\nPfMiGyhV6iTXV7G1NJuMCGH6VIhYaDkDaQqUchl6QI1ZlFweLJ9qR3sV2S8oPmCGSX2DyaaCRcnS\nibh0brB8DEaf5gnfJYwlatErDaQPcqN+3BRxecswdsCEBaBK1m0RPPhLk8VnKXR0gKYdf5i+lJI/\n/rHA88/nyGQkLS0aq1b5aWw8uhnzzHMGP7qnzHhCp1DQUBA89JsS160qcfHFx54RYVI4iZaJEOJB\nbKuiSgjRix2V9R3gV0KIPwN6sCNcwY7GWoUdcpEDbgOQUo4JIf4PsGai37feccYDX2R/aPDjEw+O\ncI5JwxETh480tQsX0v2HP1C3eCl7X5X09T/DeaECrmyZsiLRY2m8c0ZofD3HxekHmJd5mX5R4u24\nRWlPGlN1oWXH8bSnaNzTixJSiDLCxopOEmYFMX2ExnA/eXeIoC9DMhnFEgqd7m1UKaPkhRtxhoFV\n0umbW0udZ4CFmfX0r25g7ZpzGE9E7F9pm8XZlxu0yixDAz6GRJll9YLvLBxgaOhJakd17u+/nEQu\nQiIfJqyNMTxeQyITsS2fdy6OKuCCgoC3N8CmjRZdXfDpTyu4XMcnKK+9VuDRRzPU1WlEo4KxMYu7\n7krxla+Eqao68pLVL35rMFZyoUYKuDKC0pBCMSN58cXTQEzgpO0zkVJ+6jBPXXKIvhL48mGOcw9w\nzyHa3wAOylompRw91DkmE0dMHD7SuEMhFn72s6z/+c+pmTuPcnsHa7p34jJ2E2zRaLl9HvfVN1Oz\nbAEbfv4yG/yDVHsSzDD2kny9n3IBVBcYwRibhhuoVYdJx2rIBXTqBrrxpYqMdUUwEhpepYS3PkM+\n66N5bB9aTZlOBkiGKtDqilTWDHGZ+jwVtSk87WU+f9U9bF3fQdIbJT7/T7m6Kcydr7uoieWJWhqD\nm718t28Rld7/y8wqF1fP1nk7XqKv2MmOYUFybxBrSNhJJXVhL2prJsKAygYF4YUZ9bBtm+TFFyXt\n7YLGRg65L+X9mKbk+edz1Ndr71ZTjEZV+vsN1q4tcPnlh487NgzJ+HgB0wDLUDBKAiENNE0SDE79\nynuhADu2T/Uoph+OmDh85Ak1NLDk619nbOdOUn19aG43lR0dBGoP2L8iYN6Nf0vokQdZ9/Pf4bt4\nA6OXBBjeDZ5smqp7X+Gssa0Mn9VBubaFuswY7vgIgZgg84cw7cWd+Nwu8pqH0WqFS3Y+S0+gBcsS\nNHXvpmb3ML0rWgnVpukptlCnDhAVY9Q25pgl0vT5BnluNMaQEcAomhgJlb49Cu0LFJLFBko5+IuL\nIRaC+irJ1j3wq9/DAymDXaaFFAoULdSypCIsWbBQZWwi2ZHXC//+75J582D2bLj55qO/Z6WSJJeT\nxGLvvfh7vYJ4/MhrRK+8kiLqSRBweUhlNESmiKZLWprcXHLJ1FeJ9Lig4xj3STu5ufbjiImDAzCm\nbyF9xj7qzliMj5pD9tH8fmbe9Dna5G3sEqM8ltvM+NBzNPzgfupGu9HnuWlUxwhvHWPYFyVtqOQi\nNbh6DCq9I6ixAOmhKOMuhV0NM+kc2MagqCVQzGOqbraKTuawhYLpZtwKczbr2ZcsUvYLetM+0lFQ\nW1R6xlVcWQj6oSIAQQ32jUBTFVSFAASz2+AfvwK3/y+FL3+jQH9aRxiSkRGLcFhgARU+e17pNJTL\ndjngLVvsXehHs048HkEsppJKWYRC+wUllbJYvvzIPpO1a/P4PILbP27y+JNpshmdmloX//B3IRYs\nOIGwsZONU8/khHDExOEjT4kMQ7yJiotB1jCjeDHmK7+DQh5l6bWI8HtjWxWh0kE1X/VVU7rqQnZd\n/he4HruWtd8eZTBSQ0dbEiVnUgr6MbJ+RquqGPHHmBnI0F5ZS625gScXXUo6GWDm+G7i7hiPtVzJ\nuBKmMpdkkXsdmlVmV6KdvtEG3mhaRKOvketqIOeCYTeEfVBlQT4LSQOiwf3iYEh4NQfjJpxfrfL5\nT+t8715JsQRSgWClhkuDlpi9XGWaklmzFPbtg/PPB0WRWBZHrFsihODqq/3ce2+KXM7C6xUkEhax\nmMrChYf3eZimZPNmwVtvFTnnHLjqShd/8ifVdHV58XhOo1x9TqXF48YRE4ePPBpevFSRJ07QrKf8\n4N+T63kMS7VwbX4Y/9cfOXR8K+BCcIZWhbzoC6x/6gWKu0xeWh9m4fytqGhs7+6iZ0kjskdD6mHe\nVnOsLsawijl+3XojzBEo0kLPlglYKZ7RL2ZN8RzYbqHmLXwxi/qxMF+ZrfNmHjxFmOOHiBvqo1CX\ntpdlLpgD+sSv+fU8/E8avArsKsNfXeFi9myLV9+WvLUJdm+DOrcklYAXXihTLMK//IvOggVgmkW+\n973taJrg9tu7CAYPbym0t7v40pfCvP56npERkyVLvJx5phuf7/B+D1UVXH99BbW1OkuWCObN89Hc\nfBo43A/EsUxOCEdMHD7yKKi0cQUGeVwFk9zIBkpVflSClFI78eYSKP7IEY8h/KvYfmUN9d0bKA0O\n8VTfKvIzPKgLQe2XFPUAA1oHvzcNkoUwkgBmSIMi1FgDfE65B38uw3PmhbyaWUZhr4+mhm5CkSIB\n7yA/XCOomV3FipAdJSUl9OThjqXgeV/gVMYCWYREN6QrQUahtVmhtRluugb+4weSV1dLsukc4XCJ\nYNBHJgMVFbB5c554vICiwNBQ/l0x6e4ukEoZtLR4CIX2Xzbq6zWuv/748qBcfbWHq6+eet/I4SgU\nHQf8ieCIiYMDoKDhIgjuMkr9TJT+XoSRhVgjwhs6+gHUKtzhZYwG6gl3bKVxuJuUsBgZCFEqVTKn\nbin342J8HMpSAWviYqoolC0XO12tNDDIRcmXeS57CeWii/hoDVY+idZcJGWM4QtlyBfb8KoKRcsO\n0DpUzapzvfDweti4HhaEwex6rw/k3HMEkYhg0/o8697K8c1vurnsMjfJpEmxqHHBBTVomqC11U5Q\nsXZtil//Oo6Utq/kL/+yiXD4NPBtTBIeN3QcY8bA1/84uWOZTjhi4uBwIJqO+5pvYa1/ANPM4D3r\nVoRybGk+Gir8bBuZR3V4DjFXFv9Ygnoh8DfE2ORSSOYzGMILfgFx5d3aJgk1ygZrIZ3F/2bUHcWq\nEChxk1zSh8fKsXOnj3PP6SUasugdyGNm/fRk4cIYZA0Ive+6XqHCrS3w6B5oqQH1fcM/7xw4Z7Gk\n5/wQ8+e7WbHCjaYJBgfLrF9f5Oabm1AUQaEA994Ljz+eobNTpacnQ3d3HpD8zd+04XZPfRivw+mD\nIyYODu9DBKvwnf/V437d2Q2wbgAQCro/SIV///LPMCXMYhmCXjAnsv0KiaoYGFIwYlRilhTeNBfR\nrOxj35lNGOt1UvkwLQ172O6uYNeeSs70WmimwQyfxnAeHuyBOw6RgHHJfOhstiO+DuXu2bixyC9+\nkeKLX4wQjdqXga4uD11d+5ef+vpgxw4YH1f5yU/SlEpl2toUxsYMurvzdHYeJYf9tMbxwB8vjpg4\nOJwkmisg6oNMCQKu9z7nBVweA6VgYfpUghUjBGQRr56jUPRiZFReyF2AJVQqzCRNo7t5pXMFDIAM\ngankKYXG2aqnMMoeukIuoh4Y6IvRtTvAmfUQep8bojIMo2P2JryG+vc+19ios3Klj1jsYKtr+y57\nWayhAWbOtHjoIRMhVKSU9PRIFIVjWubK5SyKRYhEppsF43jgTwRHTBwcThKKAhe2wq83gT/yXoug\nA5WXPDqx8jAGOpfNepy+/iYGMg3M9G6no2Y7b0QWk4n6EUGJP5ugsbyXQXc98WIMlzBABT2kE3GN\n0q+o9Jgh+gbLrN5ucHZE5fsrBIEDrvGDQ/Cju6FUhhuvhcUH5PCORlVWrjw4aXffANzzS3surnKO\np54sMzJWRkgNv19DyjI33lhDdbXroNceSCpl8cMfZshkJLfc4qWr68j9Tz8cMTleHDFxcDiJj6+s\nOAAACaRJREFULKqDbSOwdQSaKva3V6OyCJ3XAjpt7l1UiREqginO52UWJdbyZusiOlq3kNTDlJM6\nckwh5hlitDGKOlaCqMCwdLI5D+6Al2pZYtBngVDJCItRKdiRVFlUtf+ciaQdmaQqMHSMCciDAYhU\nwPi4wROPlenLaKRFFaSGIWUSigR4bnuQIQuuWQKuwxgoqZRFMmlhmjA8LOk6HUrxHiOFgsWOHaWp\nHsa0wxETB4eTiKrADbPhwQ2wcxQaK+w2gJWE0GWaVGGYqH+Mmtww0cwoI+EYq0NL6M83oBkGLaG9\nFMZcqMKFbpWoqEkSEWMUVD9ZK0LZ9FMnw2SVEpG5Bfr36JR1eEM3aLJ0qiYKgLXPgBXL7QqJy5Yc\n2/hDQfirO2BgQOG1Z6B3kwThAuyaMKlxhbWrDbKGysx6WHiYqKeGBpXrr/eSSFgsXjy9rBKPBzo6\njs0yed3Jp/Iujpg4OJxkPDp8ZgE8uQNWTxRVjfnBqytcpDTSv+9RYsoQlge2W+081raKYasWxiRG\ntU6f2UB9ZS/xXDVnBLbS4u6hNObG48ljeVS2qwvpEx4GBsJU6TreNpOFAXtn/D2lIl9yewgIgabB\nlSuPPt7h4QJvv51gxYpqNE1B16G5WeEb3/Dx4nV5MGwLyM5fLxkbsWvCu45w9RBCcN55p9lmxGNG\n4jjgj5/p5hlzcJgW6CpcPQu+sRxWdUK+DD0J6EsKst557Hi8jqFeLy+5Z1NOlZCKRbHOg8fMUTC8\nqBUGiWIliUwVq4fOZ7cxk3gxRkiM06jtYMDKE/NmaBFuwrrK3pJCjVDIAf3W/gthLiexM5sfnvHx\nEhs2JCmV9r+uXJb0Dmv4Kt2ANVFXxUTxWuTdKs88BU88wTEX2DoSAwMG69YV6ek5CQc7aZjH+HB4\nB8cycXCYRIJuWNoM5zbCeB6KJiSSFi/d+QCvhK+itmWImJaiaPXxpnY+A+kGmrO7GE/FCOg5/Eoa\nKRXGyjH8xRSFlJdQOMmIkiTg8uAzFNyqJFuGgiUxhcQ94fjftq3MvfcWWLZM56qrDr/jvKsrRGdn\nEDERMfD4UwWeerrAL1d7yQUVKKsTpYUtfI2Crc9rlNPw18/Aa2vggR8f3ndyNHbsKHHvvXb6YsuC\nG27ws3jxVFs0TjTXieCIiYPDKUBVoGpiW0YgVY+rME74XD8FlyQ/VkR6Kwj2p9n9eBdjq6vRrixT\nP3cfoXACVZgoWJhlDbe3RH+pCre3jFaUuLs14kUTo0IyGLY4U9UoDCh87zUY6YVkWpLPHzwew5CM\njpaJxXQURbwrJHu6Tf75BxaywsuQEOBV99epzwoyQxYEwdUFcg+8+goMj0HjoRMtH5F160a4++44\njY11RCIq+bzFc8/lHTGZpjhi4uBwitFrGxmfNYt2LUFKGuwOt5Lr9ZJ4IgL9CuQh0D+GttQkJUNU\nWCmElDR4+hgpVZIL+XBLGP5DIwP9GmgqLbpFY1ZQXyv48TOCpihUNujoAZXrrjt41+IvfhFn06Yc\nF10U4sor92dFFgKSKYV8QUFRLEyB7T4wAZcAn4CQhVlUEBVw5iKorTyx92FkJE8mk6dYtJfhSiVw\nu6c+c7AdzZWd6mFMOxwxcXA41WgKDd/6GOrvXyXQEiKtRHj1DyvZt7fV/kWqEK5LUNjhQbRLBjJ1\neDNZdo60gV/hosZulsTP5qVUBdWtEFAEwwmVnz8JW2bBmj3gckFzFNJ5hVxO0tdnUlsriEZtN+nw\ncAnDsBgeLvPb3+ZobNRYvNhFS5PCNRdJXltbQjMMthUElDTb916UtoUyG/wq3HAu/ORvjq0y46FY\nubKJ+fPrueuuND09BroOn/jE8SWNnAw8HkFHx7G5k51orv04YuLgcIrx4KbdNZPN5dVUvzXEUKGe\n7C+D0CagDHRDen2Q0NIkosfCk8qwN9jB/PTbtC5NMkO/kEarhgpdUDPhq9gyBH43zIhBaSa8ugPU\nmXDlWZL77iswMCAJBuGrX/Xi9wtuuaWa3bsLzJjh5cc/zpHLSRYvdiGE4Nt/72Fw0GRvr4dLrzfJ\npcuAgLxEUS3Ut9x0XAB3fdPe3PhBqK5W+drXQoyP20W2AoHTISbIWeY6ERwxcXA4xSgIFng+hufC\nTbzx2DpiPXswiirW69q78ZWjz9aQHo0g2kqELkui7THQGmB582xMNMYjeXQ1SCILIS8ks1AdArcL\n5raDPwR/dSkEPfDELyW1tYKhIYtMRuL3C6qrXe/uYv/614O4XPuXlxRFUF+vUV0NV1yh8thvDco5\nC5dfQdF0zLLC4rYPLiTv4PUqeL2ng4i8gyMmJ8Lp9Ak6OHxk0IWbuS3/BK47+dfg9xi6phKCgAsI\nAdVQKulUtIxh9OrMaOuFyjOoVEIYQNQv+LNL7L0e/eOwrAPqaqAvAT3jcO1CqKqwfRDXXquTz8Py\n5TrV1Qf7JPx+BV0/uF3T4F//EZYu1whEXFhCx5QKsxbYGxs/3DihwceLY5k4OEwVQuGSyxv41ztz\n0OyBJRbsERC00Pxl3IEiqXQl4Uo3gUglHlFiQGSJoTEfL/5K+Mur9x9uVxwGUlAThI7q/e3nnqtz\n7rknFrvb1gz33QkPPQqbtsCsLvjkddDU8AHnfhpTKJjs2JGa6mFMOxwxcXCYQpqaBP95q4fl/1ak\nOMMNJoi0wEIjG3TBPsGM8yXzpMLFMZUVuAmjoXOwJTEzZj9ONo318LUvnPzjnq7YDvhjSwHjOOD3\n4yxzOThMMWd3qfzXrS4q1xuQlchKBcuvwYjCdasEy/wqrS6Fy2pUYuiHFBKHk42zzHW8OJaJg8Np\nwHVLVC68W+Xhl+GPe4AohNvspINnVcLyaghPr3yJ0xjHAX8iOGLi4HCaEA7BZ1fBZyf+fyel1qEq\nJTpMJo6YnAiOmDg4nKY4IjKVOGJyvDhi4uDg4HAAhYLBjh0jUz2MaYcjJg4ODg4H4PEodHT4j6mv\nE821H0dMHBwcHN6D4zM5ERwxcXBwcDgIp9Li8SKOVoXtdEAIEQe6T/Jhm4Gek3zMU8l0Hz9M/zk4\n4596DjWHFinlCW/fFEI8AVQdY/cRKeUVJ3quDxPTQkwmAyFE/IN84aaa6T5+mP5zcMY/9XwY5vBh\n4aO8Az4x1QP4gEz38cP0n4Mz/qnnwzCHDwUfZTFJTvUAPiDTffww/efgjH/q+TDM4UPBR1lMfjrV\nA/iATPfxw/SfgzP+qefDMIcPBR9Zn4mDg4ODw8njo2yZODg4ODicJBwxcXBwcHD4wDhi4uDg4ODw\ngXHExMHBwcHhA+OIiYODg4PDB+b/A/LMvXYksuoIAAAAAElFTkSuQmCC\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x26a7330c828>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "train_set.plot(kind='scatter',x='longitude', y='latitude', alpha=0.4, s=train_set['population']/100,label='population', c='median_house_value',cmap=plt.get_cmap(\"jet\"),colorbar=True)\n",
-    "plt.legend()"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### 研究样本属性之间的关系"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 42,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<div>\n",
-       "<style>\n",
-       "    .dataframe thead tr:only-child th {\n",
-       "        text-align: right;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe thead th {\n",
-       "        text-align: left;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe tbody tr th {\n",
-       "        vertical-align: top;\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>longitude</th>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>-0.924485</td>\n",
-       "      <td>-0.101818</td>\n",
-       "      <td>0.038676</td>\n",
-       "      <td>0.063064</td>\n",
-       "      <td>0.094276</td>\n",
-       "      <td>0.049306</td>\n",
-       "      <td>-0.017040</td>\n",
-       "      <td>-0.046349</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>latitude</th>\n",
-       "      <td>-0.924485</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.005296</td>\n",
-       "      <td>-0.029224</td>\n",
-       "      <td>-0.059998</td>\n",
-       "      <td>-0.102499</td>\n",
-       "      <td>-0.064061</td>\n",
-       "      <td>-0.076571</td>\n",
-       "      <td>-0.142983</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>housing_median_age</th>\n",
-       "      <td>-0.101818</td>\n",
-       "      <td>0.005296</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>-0.360922</td>\n",
-       "      <td>-0.320624</td>\n",
-       "      <td>-0.292283</td>\n",
-       "      <td>-0.302796</td>\n",
-       "      <td>-0.121711</td>\n",
-       "      <td>0.103706</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>total_rooms</th>\n",
-       "      <td>0.038676</td>\n",
-       "      <td>-0.029224</td>\n",
-       "      <td>-0.360922</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.930489</td>\n",
-       "      <td>0.857936</td>\n",
-       "      <td>0.920482</td>\n",
-       "      <td>0.198268</td>\n",
-       "      <td>0.133989</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>total_bedrooms</th>\n",
-       "      <td>0.063064</td>\n",
-       "      <td>-0.059998</td>\n",
-       "      <td>-0.320624</td>\n",
-       "      <td>0.930489</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.878932</td>\n",
-       "      <td>0.980255</td>\n",
-       "      <td>-0.009141</td>\n",
-       "      <td>0.047980</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>population</th>\n",
-       "      <td>0.094276</td>\n",
-       "      <td>-0.102499</td>\n",
-       "      <td>-0.292283</td>\n",
-       "      <td>0.857936</td>\n",
-       "      <td>0.878932</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.907452</td>\n",
-       "      <td>0.004122</td>\n",
-       "      <td>-0.026032</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>households</th>\n",
-       "      <td>0.049306</td>\n",
-       "      <td>-0.064061</td>\n",
-       "      <td>-0.302796</td>\n",
-       "      <td>0.920482</td>\n",
-       "      <td>0.980255</td>\n",
-       "      <td>0.907452</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.012776</td>\n",
-       "      <td>0.063714</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>median_income</th>\n",
-       "      <td>-0.017040</td>\n",
-       "      <td>-0.076571</td>\n",
-       "      <td>-0.121711</td>\n",
-       "      <td>0.198268</td>\n",
-       "      <td>-0.009141</td>\n",
-       "      <td>0.004122</td>\n",
-       "      <td>0.012776</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.690647</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>median_house_value</th>\n",
-       "      <td>-0.046349</td>\n",
-       "      <td>-0.142983</td>\n",
-       "      <td>0.103706</td>\n",
-       "      <td>0.133989</td>\n",
-       "      <td>0.047980</td>\n",
-       "      <td>-0.026032</td>\n",
-       "      <td>0.063714</td>\n",
-       "      <td>0.690647</td>\n",
-       "      <td>1.000000</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "                    longitude  latitude  housing_median_age  total_rooms  \\\n",
-       "longitude            1.000000 -0.924485           -0.101818     0.038676   \n",
-       "latitude            -0.924485  1.000000            0.005296    -0.029224   \n",
-       "housing_median_age  -0.101818  0.005296            1.000000    -0.360922   \n",
-       "total_rooms          0.038676 -0.029224           -0.360922     1.000000   \n",
-       "total_bedrooms       0.063064 -0.059998           -0.320624     0.930489   \n",
-       "population           0.094276 -0.102499           -0.292283     0.857936   \n",
-       "households           0.049306 -0.064061           -0.302796     0.920482   \n",
-       "median_income       -0.017040 -0.076571           -0.121711     0.198268   \n",
-       "median_house_value  -0.046349 -0.142983            0.103706     0.133989   \n",
-       "\n",
-       "                    total_bedrooms  population  households  median_income  \\\n",
-       "longitude                 0.063064    0.094276    0.049306      -0.017040   \n",
-       "latitude                 -0.059998   -0.102499   -0.064061      -0.076571   \n",
-       "housing_median_age       -0.320624   -0.292283   -0.302796      -0.121711   \n",
-       "total_rooms               0.930489    0.857936    0.920482       0.198268   \n",
-       "total_bedrooms            1.000000    0.878932    0.980255      -0.009141   \n",
-       "population                0.878932    1.000000    0.907452       0.004122   \n",
-       "households                0.980255    0.907452    1.000000       0.012776   \n",
-       "median_income            -0.009141    0.004122    0.012776       1.000000   \n",
-       "median_house_value        0.047980   -0.026032    0.063714       0.690647   \n",
-       "\n",
-       "                    median_house_value  \n",
-       "longitude                    -0.046349  \n",
-       "latitude                     -0.142983  \n",
-       "housing_median_age            0.103706  \n",
-       "total_rooms                   0.133989  \n",
-       "total_bedrooms                0.047980  \n",
-       "population                   -0.026032  \n",
-       "households                    0.063714  \n",
-       "median_income                 0.690647  \n",
-       "median_house_value            1.000000  "
-      ]
-     },
-     "execution_count": 42,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "corr_matrix = train_set.corr()\n",
-    "corr_matrix"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 43,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "median_house_value    1.000000\n",
-       "median_income         0.690647\n",
-       "total_rooms           0.133989\n",
-       "housing_median_age    0.103706\n",
-       "households            0.063714\n",
-       "total_bedrooms        0.047980\n",
-       "population           -0.026032\n",
-       "longitude            -0.046349\n",
-       "latitude             -0.142983\n",
-       "Name: median_house_value, dtype: float64"
-      ]
-     },
-     "execution_count": 43,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "corr_matrix[\"median_house_value\"].sort_values(ascending=False)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 44,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "C:\\ProgramData\\Anaconda3\\lib\\site-packages\\ipykernel_launcher.py:3: FutureWarning: 'pandas.tools.plotting.scatter_matrix' is deprecated, import 'pandas.plotting.scatter_matrix' instead.\n",
-      "  This is separate from the ipykernel package so we can avoid doing imports until\n"
-     ]
-    },
-    {
-     "data": {
-      "text/plain": [
-       "array([[<matplotlib.axes._subplots.AxesSubplot object at 0x0000026A72DB6C50>,\n",
-       "        <matplotlib.axes._subplots.AxesSubplot object at 0x0000026A73C30198>,\n",
-       "        <matplotlib.axes._subplots.AxesSubplot object at 0x0000026A7387B198>,\n",
-       "        <matplotlib.axes._subplots.AxesSubplot object at 0x0000026A73964198>],\n",
-       "       [<matplotlib.axes._subplots.AxesSubplot object at 0x0000026A738E3208>,\n",
-       "        <matplotlib.axes._subplots.AxesSubplot object at 0x0000026A738E3240>,\n",
-       "        <matplotlib.axes._subplots.AxesSubplot object at 0x0000026A73C02C88>,\n",
-       "        <matplotlib.axes._subplots.AxesSubplot object at 0x0000026A73C7FC88>],\n",
-       "       [<matplotlib.axes._subplots.AxesSubplot object at 0x0000026A73CBAC88>,\n",
-       "        <matplotlib.axes._subplots.AxesSubplot object at 0x0000026A73C181D0>,\n",
-       "        <matplotlib.axes._subplots.AxesSubplot object at 0x0000026A73D276D8>,\n",
-       "        <matplotlib.axes._subplots.AxesSubplot object at 0x0000026A73D62BA8>],\n",
-       "       [<matplotlib.axes._subplots.AxesSubplot object at 0x0000026A73DA3128>,\n",
-       "        <matplotlib.axes._subplots.AxesSubplot object at 0x0000026A73DC2EF0>,\n",
-       "        <matplotlib.axes._subplots.AxesSubplot object at 0x0000026A73E0B198>,\n",
-       "        <matplotlib.axes._subplots.AxesSubplot object at 0x0000026A73E41518>]], dtype=object)"
-      ]
-     },
-     "execution_count": 44,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "data": {
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MWWe1qOM4LooksqUrRLFu8tiZFWazVSzb4WOHhviHF1dQJJHfe/cOJtfKHJnO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CS5sgNIHFdy5HIGy9TJV2wm8zW6G8PMlmxioQAh0+D10WmqjouU0JEM0hS1iAVNDvUm+Q/f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\nLqfCv79vA5sSIf7ni5MI4Od39uJ2yJzL1FB1i2JNbwXjliVsScXTS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WCywJ4a6xvjm3A1iu2Z3f2z7k2lH3jhdQbFi8slLjkaMr1E0xRgwCEZ/utznGInpdcLy2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\nAAAASUVORK5CYII=\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x26a73e82470>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "from pandas.tools.plotting import scatter_matrix\n",
-    "attributes = [\"median_house_value\",\"median_income\",\"total_rooms\",\"housing_median_age\"]\n",
-    "scatter_matrix(train_set[attributes],figsize=(12,8))"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "collapsed": true
-   },
-   "outputs": [],
-   "source": []
-  }
- ],
- "metadata": {
-  "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": "3.6.3"
-  },
-  "toc": {
-   "nav_menu": {},
-   "number_sections": true,
-   "sideBar": true,
-   "skip_h1_title": false,
-   "title_cell": "Table of Contents",
-   "title_sidebar": "Contents",
-   "toc_cell": false,
-   "toc_position": {},
-   "toc_section_display": true,
-   "toc_window_display": true
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 2
-}
diff --git a/California Housing Prices/main.py b/California Housing Prices/main.py
deleted file mode 100644
index 6b24150..0000000
--- a/California Housing Prices/main.py	
+++ /dev/null
@@ -1,146 +0,0 @@
-# -*- coding:utf-8 -*-
-
-# ******************************************************************************
-# 模块说明 ：应用程序的主调用程序
-#            执行 process_training_model() 进行模型训练
-#            执行 process_predict()        进行实际预测
-#
-# 开发人员 ：Edwin.Zhang
-# 开发时间 : 2018-5-18
-# ******************************************************************************
-
-import numpy as np
-
-from sklearn.linear_model import LinearRegression
-from sklearn.tree import DecisionTreeRegressor
-from sklearn.ensemble import RandomForestRegressor
-
-import load_data as myload
-import prepare_data as myprepare
-import train_model as mytrain
-
-
-def myprint(message):
-    """
-    说明：一个小函数，为了缩减文件，使重点突出，没有加共用函数库，冗余了这段代码
-    """
-    import time
-    print(time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(time.time())) + " : " + message)
-
-
-def get_default_model(modeltype):
-    """
-    说明：
-        获得缺省参数的模型实例
-    输入：
-        modeltype:(string) - 自定义模型类型标识符
-    输出：
-        reg_model:(scikit-Learn model) - 输入的标识符必须能正确匹配，否则返回 None
-    """
-    reg_model = None
-
-    if modeltype == "linear":
-        reg_model = LinearRegression()
-    if modeltype == "decisiontree":
-        reg_model = DecisionTreeRegressor()
-    if modeltype == "randomforest":
-        reg_model = RandomForestRegressor()
-
-    return reg_model
-
-
-def process_training_model():
-    """
-    说明：
-        执行模型的训练，需要反复调试，以获得最好的训练模型
-    """
-    # step 1 : 获取，并装载训练数据集
-    myprint("Ready to load train data set ...")
-    dataloader = myload.DataLoader()
-    train_set = dataloader.load_train_set()
-    myprint("Load train data complete.")
-
-    # step 2 : 清理数据 （基于特征分析的结果，并将根据性能做相应调整）
-    myprint("Ready to prepare Data ... ")
-    preparer = myprepare.PrepareData(train_set)
-    preparer.prepare_data()
-    train_prepared = preparer.train_prepared
-    train_label = preparer.train_label
-    myprint("Prepare data complete.")
-
-    # step 3 : 反复调整参数，训练模型，并记录模型的性能评分，以获得最好的训练模型
-    myprint("Ready to training models and compare performance score ... ")
-
-    # 基本模型利用缺省参数进行训练，并进行交叉验证
-    trainer = mytrain.TrainModel("lin_model_1", get_default_model("linear"), train_prepared, train_label)
-    trainer.train_model()
-
-    trainer = mytrain.TrainModel("decision_model_1", get_default_model("decisiontree"), train_prepared, train_label)
-    trainer.train_model()
-
-    trainer = mytrain.TrainModel("random_model_1", get_default_model("randomforest"), train_prepared, train_label)
-    trainer.train_model()
-
-    # 自定义参数的训练模型，训练并进行交叉验证
-    reg_model = RandomForestRegressor(n_estimators=10, max_features=4, bootstrap=False)
-    trainer = mytrain.TrainModel("random_model_s1", reg_model, train_prepared, train_label)
-    trainer.train_model()
-
-    # GridSearchCV 训练 （耗时1,2分钟）
-    param_grid = [
-        {'n_estimators': [3, 10, 30], 'max_features':[2, 4, 6, 8]},
-        {'bootstrap': [False], 'n_estimators':[3, 10], 'max_features':[2, 3, 4]}
-    ]
-    trainer = mytrain.GridSearchModel("random_grid_1", get_default_model("randomforest"),
-                                      param_grid, train_prepared, train_label)
-    trainer.train_model()  # 若传入参数 True, 将显示所有参数组合的性能评分
-
-    myprint("")
-    myprint("Training and compare models complete. ")
-    myprint("All trained models are saved in folder 'trainmodels' with the same name you provided. ")
-    myprint("Please choose the best model for actual predict. Thanks ! ")
-    myprint("")
-
-
-def process_predict():
-    """
-    说明：
-        当已经训练好模型后， 利用最佳模型进行预测
-    """
-    # step 1 : 获取，并装载原始测试数据集 或实际待预测的数据
-    myprint("Ready to load test data set ...")
-    dataloader = myload.DataLoader()
-    test_set = dataloader.load_test_set()
-
-    # 有一个问题要解决：若测试文本字段的分类数量跟训练集不一致，则会造成特征列个数不同的情况，需要考虑如何处理
-    # 在大数据情况下没有关系，若只取几十条，或单条进行预测，会引起报错（待解决）
-    myprint("Load test data complete.")
-
-    # step 2 : 清理数据
-    myprint("Ready to prepare Data ... ")
-    preparer = myprepare.PrepareData(test_set)
-    preparer.prepare_data()
-    test_prepared = preparer.train_prepared
-    test_label = preparer.train_label
-    myprint("Prepare data complete.")
-
-    # step 3 : 用最好的训练模型进行预测
-    myprint("Ready to predict.")
-    best_model_name = 'random_grid_1'
-    trainer = mytrain.TrainModel(best_model_name)
-    test_pred, test_rmse_score = trainer.predict(test_prepared, test_label)
-    myprint("Predict complete.")
-    myprint("")
-
-    myprint("Show or use predict result : ")
-    # step 4 : 使用预测结果，供后续系统使用
-    print(np.c_[test_label[:20], test_pred[:20]])
-    print(np.c_[test_prepared[:5], test_label[:5], test_pred[:5]])
-
-
-if __name__ == "__main__":
-    # 训练模型
-    process_training_model()
-
-    # 执行预测
-    process_predict()
diff --git a/California Housing Prices/trainmodels/decision_model_1.pkl b/California Housing Prices/trainmodels/decision_model_1.pkl
deleted file mode 100644
index 98d18e7..0000000
Binary files a/California Housing Prices/trainmodels/decision_model_1.pkl and /dev/null differ
diff --git a/California Housing Prices/trainmodels/lin_model_1.pkl b/California Housing Prices/trainmodels/lin_model_1.pkl
deleted file mode 100644
index 4195e3c..0000000
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diff --git a/California Housing Prices/trainmodels/random_model_1.pkl b/California Housing Prices/trainmodels/random_model_1.pkl
deleted file mode 100644
index fd01f06..0000000
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diff --git a/California Housing Prices/trainmodels/random_model_s1.pkl b/California Housing Prices/trainmodels/random_model_s1.pkl
deleted file mode 100644
index 49e5b1e..0000000
Binary files a/California Housing Prices/trainmodels/random_model_s1.pkl and /dev/null differ
diff --git a/Netural Style Transfer/app/__pycache__/my.cpython-36.pyc b/Netural Style Transfer/app/__pycache__/my.cpython-36.pyc
deleted file mode 100644
index 1edfcd9..0000000
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deleted file mode 100644
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deleted file mode 100644
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deleted file mode 100644
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deleted file mode 100644
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deleted file mode 100644
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diff --git a/Netural Style Transfer/app/views/__pycache__/win_main.cpython-36.pyc b/Netural Style Transfer/app/views/__pycache__/win_main.cpython-36.pyc
deleted file mode 100644
index 2c6fef9..0000000
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diff --git a/Netural Style Transfer/app/views/__pycache__/win_main_dataset.cpython-36.pyc b/Netural Style Transfer/app/views/__pycache__/win_main_dataset.cpython-36.pyc
deleted file mode 100644
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diff --git a/Netural Style Transfer/app/views/__pycache__/win_main_datasource.cpython-36.pyc b/Netural Style Transfer/app/views/__pycache__/win_main_datasource.cpython-36.pyc
deleted file mode 100644
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diff --git a/Netural Style Transfer/framework/__pycache__/__init__.cpython-36.pyc b/Netural Style Transfer/framework/__pycache__/__init__.cpython-36.pyc
deleted file mode 100644
index 43d9c7b..0000000
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diff --git a/Netural Style Transfer/framework/__pycache__/tk_utils.cpython-36.pyc b/Netural Style Transfer/framework/__pycache__/tk_utils.cpython-36.pyc
deleted file mode 100644
index a2e529a..0000000
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diff --git a/Netural Style Transfer/framework/__pycache__/utils.cpython-36.pyc b/Netural Style Transfer/framework/__pycache__/utils.cpython-36.pyc
deleted file mode 100644
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diff --git a/Netural Style Transfer/run.bat b/Netural Style Transfer/run.bat
deleted file mode 100644
index 7a84f97..0000000
--- a/Netural Style Transfer/run.bat	
+++ /dev/null
@@ -1 +0,0 @@
-python main.py
\ No newline at end of file
diff --git a/Netural Style Transfer/workspace/temp_result.png b/Netural Style Transfer/workspace/temp_result.png
deleted file mode 100644
index 9304bcd..0000000
Binary files a/Netural Style Transfer/workspace/temp_result.png and /dev/null differ
diff --git a/Netural Style Transfer/README.md b/Netural_Style_Transfer/README.md
similarity index 65%
rename from Netural Style Transfer/README.md
rename to Netural_Style_Transfer/README.md
index 1a1911c..fb144d2 100644
--- a/Netural Style Transfer/README.md	
+++ b/Netural_Style_Transfer/README.md
@@ -8,10 +8,5 @@ https://pan.baidu.com/s/1pYEKpQ48TabncoMy2btBLQ
 提取码: rao4
 
 
-开发环境中主要的库版本：
-* tensorflow==1.12.0
-* keras==2.1.2
-* numpy==1.15.4
-* scipy==1.1.0
-* cv2==3.3.0.10
-* PIL==5.3.0
+下载后的模型文件，请复制到用户目录下的 .keras\models 中，
+如： C:\Users\Edwin\.keras\models
\ No newline at end of file
diff --git a/Netural Style Transfer/app/my.py b/Netural_Style_Transfer/app/my.py
similarity index 99%
rename from Netural Style Transfer/app/my.py
rename to Netural_Style_Transfer/app/my.py
index 966d937..94a174b 100644
--- a/Netural Style Transfer/app/my.py	
+++ b/Netural_Style_Transfer/app/my.py
@@ -10,6 +10,7 @@
 
 session = dict()
 
+
 def img(img_name):
     """ 传入文件名，返回完整的图片路径 """
     return os.path.join(Setting.APP_DIR, "res\\images\\", img_name)
diff --git a/Netural Style Transfer/app/res/colors.py b/Netural_Style_Transfer/app/res/colors.py
similarity index 100%
rename from Netural Style Transfer/app/res/colors.py
rename to Netural_Style_Transfer/app/res/colors.py
diff --git a/Netural Style Transfer/app/res/consts.py b/Netural_Style_Transfer/app/res/consts.py
similarity index 100%
rename from Netural Style Transfer/app/res/consts.py
rename to Netural_Style_Transfer/app/res/consts.py
diff --git a/Netural Style Transfer/app/res/fonts.py b/Netural_Style_Transfer/app/res/fonts.py
similarity index 100%
rename from Netural Style Transfer/app/res/fonts.py
rename to Netural_Style_Transfer/app/res/fonts.py
diff --git a/Netural Style Transfer/app/res/images/001.png b/Netural_Style_Transfer/app/res/images/001.png
similarity index 100%
rename from Netural Style Transfer/app/res/images/001.png
rename to Netural_Style_Transfer/app/res/images/001.png
diff --git a/Netural Style Transfer/app/res/images/Money.ico b/Netural_Style_Transfer/app/res/images/Money.ico
similarity index 100%
rename from Netural Style Transfer/app/res/images/Money.ico
rename to Netural_Style_Transfer/app/res/images/Money.ico
diff --git a/Netural Style Transfer/app/res/images/bg1.PNG b/Netural_Style_Transfer/app/res/images/bg1.PNG
similarity index 100%
rename from Netural Style Transfer/app/res/images/bg1.PNG
rename to Netural_Style_Transfer/app/res/images/bg1.PNG
diff --git a/Netural Style Transfer/app/res/images/bg2.PNG b/Netural_Style_Transfer/app/res/images/bg2.PNG
similarity index 100%
rename from Netural Style Transfer/app/res/images/bg2.PNG
rename to Netural_Style_Transfer/app/res/images/bg2.PNG
diff --git a/Netural Style Transfer/app/res/images/close.PNG b/Netural_Style_Transfer/app/res/images/close.PNG
similarity index 100%
rename from Netural Style Transfer/app/res/images/close.PNG
rename to Netural_Style_Transfer/app/res/images/close.PNG
diff --git a/Netural Style Transfer/app/res/images/flower.jpg b/Netural_Style_Transfer/app/res/images/flower.jpg
similarity index 100%
rename from Netural Style Transfer/app/res/images/flower.jpg
rename to Netural_Style_Transfer/app/res/images/flower.jpg
diff --git a/Netural Style Transfer/app/res/images/img_title.PNG b/Netural_Style_Transfer/app/res/images/img_title.PNG
similarity index 100%
rename from Netural Style Transfer/app/res/images/img_title.PNG
rename to Netural_Style_Transfer/app/res/images/img_title.PNG
diff --git a/Netural Style Transfer/app/res/images/python.PNG b/Netural_Style_Transfer/app/res/images/python.PNG
similarity index 100%
rename from Netural Style Transfer/app/res/images/python.PNG
rename to Netural_Style_Transfer/app/res/images/python.PNG
diff --git a/Netural Style Transfer/app/res/images/style.JPG b/Netural_Style_Transfer/app/res/images/style.JPG
similarity index 100%
rename from Netural Style Transfer/app/res/images/style.JPG
rename to Netural_Style_Transfer/app/res/images/style.JPG
diff --git a/Netural Style Transfer/app/res/images/style_flower.png b/Netural_Style_Transfer/app/res/images/style_flower.png
similarity index 100%
rename from Netural Style Transfer/app/res/images/style_flower.png
rename to Netural_Style_Transfer/app/res/images/style_flower.png
diff --git a/Netural Style Transfer/app/res/images/user.PNG b/Netural_Style_Transfer/app/res/images/user.PNG
similarity index 100%
rename from Netural Style Transfer/app/res/images/user.PNG
rename to Netural_Style_Transfer/app/res/images/user.PNG
diff --git a/Netural Style Transfer/app/res/strings.py b/Netural_Style_Transfer/app/res/strings.py
similarity index 100%
rename from Netural Style Transfer/app/res/strings.py
rename to Netural_Style_Transfer/app/res/strings.py
diff --git a/Netural Style Transfer/app/settings.py b/Netural_Style_Transfer/app/settings.py
similarity index 100%
rename from Netural Style Transfer/app/settings.py
rename to Netural_Style_Transfer/app/settings.py
diff --git a/Netural Style Transfer/app/views/win_main.py b/Netural_Style_Transfer/app/views/win_main.py
similarity index 98%
rename from Netural Style Transfer/app/views/win_main.py
rename to Netural_Style_Transfer/app/views/win_main.py
index 06bd4e3..7f6b6e2 100644
--- a/Netural Style Transfer/app/views/win_main.py	
+++ b/Netural_Style_Transfer/app/views/win_main.py
@@ -26,7 +26,6 @@
 from framework import tk_utils as tku
 from framework import utils
 from app import my
-
 from app.my import session
 from app.my import img
 from app.my import Color
@@ -45,6 +44,7 @@
 style_weight = 1.
 content_weight = 0.025
 
+
 def preprocess_image(image_path, img_height, img_width):
     img = load_img(image_path, target_size=(img_height, img_width))
     img = img_to_array(img)
@@ -91,10 +91,9 @@ def total_variation_loss(x, img_height, img_width):
 
 
 class Evaluator(object):
-
     def __init__(self, img_height, img_width, fetch_loss_and_grads):
         self.loss_value = None
-        self.grads_values = None
+        self.grad_values = None
         self.img_height = img_height
         self.img_width = img_width
         self.fetch_loss_and_grads = fetch_loss_and_grads
@@ -139,9 +138,9 @@ def lay_body(self):
 
         self.lay_bottom(self.win).pack(fill=tk.X)
 
-        self.txtIterations.insert('end', iterations)
-        self.txtContent.insert('end', content_weight)
-        self.txtStyle.insert('end', style_weight)
+        self.txtIterations.insert('end', str(iterations))
+        self.txtContent.insert('end', str(content_weight))
+        self.txtStyle.insert('end', str(style_weight))
         return self.win
 
     def lay_title(self, parent):
@@ -202,7 +201,7 @@ def lay_org_image(self, parent):
             .pack(side=tk.RIGHT, fill=tk.X, padx=20)
 
         frame.propagate(True)
-        frame.pack_propagate(0)
+        frame.pack_propagate(False)
         return frame
 
     def lay_result_image(self, parent):
diff --git a/Boxman/__init__.py b/Netural_Style_Transfer/framework/__init__.py
similarity index 100%
rename from Boxman/__init__.py
rename to Netural_Style_Transfer/framework/__init__.py
diff --git a/Netural Style Transfer/framework/python.PNG b/Netural_Style_Transfer/framework/python.PNG
similarity index 100%
rename from Netural Style Transfer/framework/python.PNG
rename to Netural_Style_Transfer/framework/python.PNG
diff --git a/Netural Style Transfer/framework/tk_utils.py b/Netural_Style_Transfer/framework/tk_utils.py
similarity index 100%
rename from Netural Style Transfer/framework/tk_utils.py
rename to Netural_Style_Transfer/framework/tk_utils.py
diff --git a/Netural Style Transfer/framework/utils.py b/Netural_Style_Transfer/framework/utils.py
similarity index 98%
rename from Netural Style Transfer/framework/utils.py
rename to Netural_Style_Transfer/framework/utils.py
index 71054c5..ac077e5 100644
--- a/Netural Style Transfer/framework/utils.py	
+++ b/Netural_Style_Transfer/framework/utils.py
@@ -140,6 +140,7 @@ def get_cfd(__f):
     """
     return os.path.dirname(os.path.abspath(__f))
 
+
 def get_all_files(folder_name, exts=None):
     """
     获得某目录下，指定扩展名的所有文件列表
@@ -199,19 +200,9 @@ def file_extension(filename):
     return os.path.splitext(filename)[1]
 
 
-def to_md5(source):
-    """ 将字符串加密为 md5
-        text： string
-    """
-    from Crypto.Hash import MD5
-    md5 = MD5.new()
-    md5.update(bytes(source, encoding="utf8"))
-    return md5.hexdigest()
-
-
 def reverse_rgb_bgr(img):
     """ 改变一个图像的通道类型：rgb <--> bgr
-    :param img (ndarray) : [width, height, channel=3]
+    :params img (ndarray) : [width, height, channel=3]
     :return: rgb-->bgr,  bgr-->rgb
     """
     return img[:, :, ::-1]
diff --git a/Netural Style Transfer/main.py b/Netural_Style_Transfer/main.py
similarity index 100%
rename from Netural Style Transfer/main.py
rename to Netural_Style_Transfer/main.py
diff --git a/Netural_Style_Transfer/run.bat b/Netural_Style_Transfer/run.bat
new file mode 100644
index 0000000..8d211a2
--- /dev/null
+++ b/Netural_Style_Transfer/run.bat
@@ -0,0 +1 @@
+..\.venv\scripts\python.exe main.py
\ No newline at end of file
diff --git a/Netural Style Transfer/workspace/bijiasuo.JPG b/Netural_Style_Transfer/workspace/bijiasuo.JPG
similarity index 100%
rename from Netural Style Transfer/workspace/bijiasuo.JPG
rename to Netural_Style_Transfer/workspace/bijiasuo.JPG
diff --git a/Netural Style Transfer/workspace/bijiasuo2.JPG b/Netural_Style_Transfer/workspace/bijiasuo2.JPG
similarity index 100%
rename from Netural Style Transfer/workspace/bijiasuo2.JPG
rename to Netural_Style_Transfer/workspace/bijiasuo2.JPG
diff --git a/Netural Style Transfer/workspace/dafenqi.JPG b/Netural_Style_Transfer/workspace/dafenqi.JPG
similarity index 100%
rename from Netural Style Transfer/workspace/dafenqi.JPG
rename to Netural_Style_Transfer/workspace/dafenqi.JPG
diff --git a/Netural Style Transfer/workspace/dafenqi2.JPG b/Netural_Style_Transfer/workspace/dafenqi2.JPG
similarity index 100%
rename from Netural Style Transfer/workspace/dafenqi2.JPG
rename to Netural_Style_Transfer/workspace/dafenqi2.JPG
diff --git a/Netural Style Transfer/workspace/dafenqi3.JPG b/Netural_Style_Transfer/workspace/dafenqi3.JPG
similarity index 100%
rename from Netural Style Transfer/workspace/dafenqi3.JPG
rename to Netural_Style_Transfer/workspace/dafenqi3.JPG
diff --git a/Netural Style Transfer/workspace/fangao.JPG b/Netural_Style_Transfer/workspace/fangao.JPG
similarity index 100%
rename from Netural Style Transfer/workspace/fangao.JPG
rename to Netural_Style_Transfer/workspace/fangao.JPG
diff --git a/Netural Style Transfer/workspace/fangao2.JPG b/Netural_Style_Transfer/workspace/fangao2.JPG
similarity index 100%
rename from Netural Style Transfer/workspace/fangao2.JPG
rename to Netural_Style_Transfer/workspace/fangao2.JPG
diff --git a/Netural Style Transfer/workspace/flower.jpg b/Netural_Style_Transfer/workspace/flower.jpg
similarity index 100%
rename from Netural Style Transfer/workspace/flower.jpg
rename to Netural_Style_Transfer/workspace/flower.jpg
diff --git a/Netural Style Transfer/workspace/style_transfer_20190515150337.png b/Netural_Style_Transfer/workspace/style_transfer_20190515150337.png
similarity index 100%
rename from Netural Style Transfer/workspace/style_transfer_20190515150337.png
rename to Netural_Style_Transfer/workspace/style_transfer_20190515150337.png
diff --git a/Netural Style Transfer/workspace/style_transfer_20190515153532.png b/Netural_Style_Transfer/workspace/style_transfer_20190515153532.png
similarity index 100%
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diff --git a/README.md b/README.md
index 21c7910..0109ffe 100644
--- a/README.md
+++ b/README.md
@@ -1,18 +1,56 @@
-# Python
-Source code about Python Development. 
+# 一. 项目说明
+该项目是一些Python程序的源代码，用于学习
 
-
-## California Housing Prices
+## 1. California Housing Prices
 是一个机器学习的项目级演示代码，实现机器学习的全自动化处理。 详细描述，可参考CSDN博客相关文章
 https://blog.csdn.net/superfanstoprogram/article/details/80413639
 
-## tkinter-pack Demo
+## 2. tkinter-pack Demo
 用TKInter编写的演示程序，主要演示pack()定位的参数设置。 详细描述，可参考本CSDN博客相关文章
 https://blog.csdn.net/superfanstoprogram/article/details/83713196
 
-## Netural Style Transfer
+## 3. Neural Style Transfer
 是一个用Keras实现的，利用神经网络进行图像风格迁移的工具， GUI用tkinter完成。可参考CSDN博客相关文章
 https://blog.csdn.net/superfanstoprogram/article/details/90239343
 
-## Boxman
+
+## 4. Boxman
 利用 tkinter.Canvas 实现的推箱子游戏, 核心代码 play.py 精简为200多行，可以参考game_maps.py中的地图设置方式，自己设计新的游戏关卡。
+
+
+
+# 二. 安装说明
+该项目用的Python版本是 3.6.7; 根据以下安装说明创建虚拟环境后，可直接运行
+
+1. 下载并安装 64位的 [Python 3.6.7](https://www.python.org/downloads/windows)。（一定是 64位的安装文件，文件名为：python-3.6.7-amd64.exe， .resource 目录中准备了一份）
+
+2. 复制所有源代码到本地目录
+
+- 手工编辑 setup.bat 文件，设置PYTHON变量为本地 python 3.6.7 安装目录下的 python.exe 的全称文件名。 
+    ```
+    if not defined PYTHON (set PYTHON="C:\Program Files\Python36\python.exe")
+    ```
+
+- 打开命令行窗口，并定位以上源代码目录
+
+  **小技巧：** 用资源管理器定位以上目录，然后清空地址栏，输入 cmd , 按回车，可打开命令行窗口，并定位当前目录
+
+  
+
+- 在命令行窗口中，运行 setup.bat, 完成虚拟环境的搭建和依赖模块的安装
+  **注意：安装时，若本机没有安装Rust, 可能出现一个安装报错，不用理会**
+
+  
+
+- 运行相关子目录下的 run.bat，可启动相应程序
+
+    
+
+
+# 三. keras 预训练模型的权重系数下载：
+[Neural Style Transfer] 需用到 keras的预训练模型，可通过以下链接下载
+https://pan.baidu.com/s/1pYEKpQ48TabncoMy2btBLQ
+提取码: rao4
+
+下载后的模型参数文件，请复制到用户目录下的 .keras\models 中，以便keras进行读取
+如： C:\Users\Edwin\\.keras\models
diff --git a/California Housing Prices/__init__.py b/boxman/__init__.py
similarity index 100%
rename from California Housing Prices/__init__.py
rename to boxman/__init__.py
diff --git a/Boxman/game_maps.py b/boxman/game_maps.py
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rename from Boxman/game_maps.py
rename to boxman/game_maps.py
diff --git a/Boxman/images/Destination.jpg b/boxman/images/Destination.jpg
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rename from Boxman/images/Destination.jpg
rename to boxman/images/Destination.jpg
diff --git a/Boxman/images/W_down.jpg b/boxman/images/W_down.jpg
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rename from Boxman/images/W_down.jpg
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diff --git a/Boxman/images/WorkerInDest.jpg b/boxman/images/WorkerInDest.jpg
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rename from Boxman/images/WorkerInDest.jpg
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diff --git a/Boxman/images/batch_resize.py b/boxman/images/batch_resize.py
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rename from Boxman/images/batch_resize.py
rename to boxman/images/batch_resize.py
diff --git a/Boxman/images/box.jpg b/boxman/images/box.jpg
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rename from Boxman/images/box.jpg
rename to boxman/images/box.jpg
diff --git a/Boxman/images/passageway.jpg b/boxman/images/passageway.jpg
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rename to boxman/images/passageway.jpg
diff --git a/Boxman/images/redbox.jpg b/boxman/images/redbox.jpg
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rename from Boxman/images/redbox.jpg
rename to boxman/images/redbox.jpg
diff --git a/Boxman/images/restart.png b/boxman/images/restart.png
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diff --git a/Boxman/images/restart2.png b/boxman/images/restart2.png
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rename to boxman/images/restart2.png
diff --git a/Boxman/images/w_down_in.jpg b/boxman/images/w_down_in.jpg
similarity index 100%
rename from Boxman/images/w_down_in.jpg
rename to boxman/images/w_down_in.jpg
diff --git a/Boxman/images/w_left.jpg b/boxman/images/w_left.jpg
similarity index 100%
rename from Boxman/images/w_left.jpg
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diff --git a/Boxman/images/w_left_in.jpg b/boxman/images/w_left_in.jpg
similarity index 100%
rename from Boxman/images/w_left_in.jpg
rename to boxman/images/w_left_in.jpg
diff --git a/Boxman/images/w_right.jpg b/boxman/images/w_right.jpg
similarity index 100%
rename from Boxman/images/w_right.jpg
rename to boxman/images/w_right.jpg
diff --git a/Boxman/images/w_right_in.jpg b/boxman/images/w_right_in.jpg
similarity index 100%
rename from Boxman/images/w_right_in.jpg
rename to boxman/images/w_right_in.jpg
diff --git a/Boxman/images/w_up.jpg b/boxman/images/w_up.jpg
similarity index 100%
rename from Boxman/images/w_up.jpg
rename to boxman/images/w_up.jpg
diff --git a/Boxman/images/w_up_in.jpg b/boxman/images/w_up_in.jpg
similarity index 100%
rename from Boxman/images/w_up_in.jpg
rename to boxman/images/w_up_in.jpg
diff --git a/Boxman/images/wall.jpg b/boxman/images/wall.jpg
similarity index 100%
rename from Boxman/images/wall.jpg
rename to boxman/images/wall.jpg
diff --git a/Boxman/images/worker.jpg b/boxman/images/worker.jpg
similarity index 100%
rename from Boxman/images/worker.jpg
rename to boxman/images/worker.jpg
diff --git a/Boxman/play.py b/boxman/main.py
similarity index 100%
rename from Boxman/play.py
rename to boxman/main.py
diff --git a/boxman/run.bat b/boxman/run.bat
new file mode 100644
index 0000000..ce5f798
--- /dev/null
+++ b/boxman/run.bat
@@ -0,0 +1 @@
+..\.venv\scripts\python.exe main.py
diff --git a/california_housing_prices/.ipynb_checkpoints/california housing prices-checkpoint.ipynb b/california_housing_prices/.ipynb_checkpoints/california housing prices-checkpoint.ipynb
new file mode 100644
index 0000000..fdfc9c1
--- /dev/null
+++ b/california_housing_prices/.ipynb_checkpoints/california housing prices-checkpoint.ipynb	
@@ -0,0 +1,1318 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "项目名称： 加利福尼亚房价预测"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## 分析数据特征"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### 将记录集装载到内存\n",
+    "\n",
+    "为了方便，建议将训练集的数据文件放在同一目录"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import pandas as pd\n",
+    "import numpy as np\n",
+    "import matplotlib.pyplot as plt\n",
+    "%matplotlib inline"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "datafilename = \"datasets\\\\train_set.csv\"\n",
+    "train_set_original = pd.read_csv(datafilename)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### 创建一个数据集的副本"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "train_set = train_set_original.copy()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### 检查数据集的大小"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(16512, 10)"
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "train_set.shape"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### 获得数据集的所有特征名称及数据类型\n",
+    "\n",
+    "其中:标签列为 : media_house_value"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Index(['longitude', 'latitude', 'housing_median_age', 'total_rooms',\n",
+       "       'total_bedrooms', 'population', 'households', 'median_income',\n",
+       "       'median_house_value', 'ocean_proximity'],\n",
+       "      dtype='object')"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "train_set.columns"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "longitude             float64\n",
+       "latitude              float64\n",
+       "housing_median_age    float64\n",
+       "total_rooms           float64\n",
+       "total_bedrooms        float64\n",
+       "population            float64\n",
+       "households            float64\n",
+       "median_income         float64\n",
+       "median_house_value    float64\n",
+       "ocean_proximity        object\n",
+       "dtype: object"
+      ]
+     },
+     "execution_count": 11,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "train_set.dtypes"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### 数据集的样本内容查看"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [
+    {
+     "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>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",
+       "      <th>ocean_proximity</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>-117.03</td>\n",
+       "      <td>32.71</td>\n",
+       "      <td>33.0</td>\n",
+       "      <td>3126.0</td>\n",
+       "      <td>627.0</td>\n",
+       "      <td>2300.0</td>\n",
+       "      <td>623.0</td>\n",
+       "      <td>3.2596</td>\n",
+       "      <td>103000.0</td>\n",
+       "      <td>NEAR OCEAN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>-118.16</td>\n",
+       "      <td>33.77</td>\n",
+       "      <td>49.0</td>\n",
+       "      <td>3382.0</td>\n",
+       "      <td>787.0</td>\n",
+       "      <td>1314.0</td>\n",
+       "      <td>756.0</td>\n",
+       "      <td>3.8125</td>\n",
+       "      <td>382100.0</td>\n",
+       "      <td>NEAR OCEAN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>-120.48</td>\n",
+       "      <td>34.66</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>1897.0</td>\n",
+       "      <td>331.0</td>\n",
+       "      <td>915.0</td>\n",
+       "      <td>336.0</td>\n",
+       "      <td>4.1563</td>\n",
+       "      <td>172600.0</td>\n",
+       "      <td>NEAR OCEAN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>-117.11</td>\n",
+       "      <td>32.69</td>\n",
+       "      <td>36.0</td>\n",
+       "      <td>1421.0</td>\n",
+       "      <td>367.0</td>\n",
+       "      <td>1418.0</td>\n",
+       "      <td>355.0</td>\n",
+       "      <td>1.9425</td>\n",
+       "      <td>93400.0</td>\n",
+       "      <td>NEAR OCEAN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>-119.80</td>\n",
+       "      <td>36.78</td>\n",
+       "      <td>43.0</td>\n",
+       "      <td>2382.0</td>\n",
+       "      <td>431.0</td>\n",
+       "      <td>874.0</td>\n",
+       "      <td>380.0</td>\n",
+       "      <td>3.5542</td>\n",
+       "      <td>96500.0</td>\n",
+       "      <td>INLAND</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   longitude  latitude  housing_median_age  total_rooms  total_bedrooms  \\\n",
+       "0    -117.03     32.71                33.0       3126.0           627.0   \n",
+       "1    -118.16     33.77                49.0       3382.0           787.0   \n",
+       "2    -120.48     34.66                 4.0       1897.0           331.0   \n",
+       "3    -117.11     32.69                36.0       1421.0           367.0   \n",
+       "4    -119.80     36.78                43.0       2382.0           431.0   \n",
+       "\n",
+       "   population  households  median_income  median_house_value ocean_proximity  \n",
+       "0      2300.0       623.0         3.2596            103000.0      NEAR OCEAN  \n",
+       "1      1314.0       756.0         3.8125            382100.0      NEAR OCEAN  \n",
+       "2       915.0       336.0         4.1563            172600.0      NEAR OCEAN  \n",
+       "3      1418.0       355.0         1.9425             93400.0      NEAR OCEAN  \n",
+       "4       874.0       380.0         3.5542             96500.0          INLAND  "
+      ]
+     },
+     "execution_count": 12,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "train_set.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [
+    {
+     "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>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",
+       "      <th>ocean_proximity</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>16507</th>\n",
+       "      <td>-117.96</td>\n",
+       "      <td>33.78</td>\n",
+       "      <td>35.0</td>\n",
+       "      <td>1330.0</td>\n",
+       "      <td>201.0</td>\n",
+       "      <td>658.0</td>\n",
+       "      <td>217.0</td>\n",
+       "      <td>6.3700</td>\n",
+       "      <td>229200.0</td>\n",
+       "      <td>&lt;1H OCEAN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>16508</th>\n",
+       "      <td>-117.43</td>\n",
+       "      <td>34.02</td>\n",
+       "      <td>33.0</td>\n",
+       "      <td>3084.0</td>\n",
+       "      <td>570.0</td>\n",
+       "      <td>1753.0</td>\n",
+       "      <td>449.0</td>\n",
+       "      <td>3.0500</td>\n",
+       "      <td>97800.0</td>\n",
+       "      <td>INLAND</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>16509</th>\n",
+       "      <td>-118.38</td>\n",
+       "      <td>34.03</td>\n",
+       "      <td>36.0</td>\n",
+       "      <td>2101.0</td>\n",
+       "      <td>569.0</td>\n",
+       "      <td>1756.0</td>\n",
+       "      <td>527.0</td>\n",
+       "      <td>2.9344</td>\n",
+       "      <td>222100.0</td>\n",
+       "      <td>&lt;1H OCEAN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>16510</th>\n",
+       "      <td>-121.96</td>\n",
+       "      <td>37.58</td>\n",
+       "      <td>15.0</td>\n",
+       "      <td>3575.0</td>\n",
+       "      <td>597.0</td>\n",
+       "      <td>1777.0</td>\n",
+       "      <td>559.0</td>\n",
+       "      <td>5.7192</td>\n",
+       "      <td>283500.0</td>\n",
+       "      <td>&lt;1H OCEAN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>16511</th>\n",
+       "      <td>-122.42</td>\n",
+       "      <td>37.77</td>\n",
+       "      <td>52.0</td>\n",
+       "      <td>4226.0</td>\n",
+       "      <td>1315.0</td>\n",
+       "      <td>2619.0</td>\n",
+       "      <td>1242.0</td>\n",
+       "      <td>2.5755</td>\n",
+       "      <td>325000.0</td>\n",
+       "      <td>NEAR BAY</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "       longitude  latitude  housing_median_age  total_rooms  total_bedrooms  \\\n",
+       "16507    -117.96     33.78                35.0       1330.0           201.0   \n",
+       "16508    -117.43     34.02                33.0       3084.0           570.0   \n",
+       "16509    -118.38     34.03                36.0       2101.0           569.0   \n",
+       "16510    -121.96     37.58                15.0       3575.0           597.0   \n",
+       "16511    -122.42     37.77                52.0       4226.0          1315.0   \n",
+       "\n",
+       "       population  households  median_income  median_house_value  \\\n",
+       "16507       658.0       217.0         6.3700            229200.0   \n",
+       "16508      1753.0       449.0         3.0500             97800.0   \n",
+       "16509      1756.0       527.0         2.9344            222100.0   \n",
+       "16510      1777.0       559.0         5.7192            283500.0   \n",
+       "16511      2619.0      1242.0         2.5755            325000.0   \n",
+       "\n",
+       "      ocean_proximity  \n",
+       "16507       <1H OCEAN  \n",
+       "16508          INLAND  \n",
+       "16509       <1H OCEAN  \n",
+       "16510       <1H OCEAN  \n",
+       "16511        NEAR BAY  "
+      ]
+     },
+     "execution_count": 13,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "train_set.tail()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### 特征数据的分布情况"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<1H OCEAN     7341\n",
+       "INLAND        5227\n",
+       "NEAR OCEAN    2086\n",
+       "NEAR BAY      1854\n",
+       "ISLAND           4\n",
+       "Name: ocean_proximity, dtype: int64"
+      ]
+     },
+     "execution_count": 14,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "train_set[\"ocean_proximity\"].value_counts()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### 数据集的快速统计分析"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "<class 'pandas.core.frame.DataFrame'>\n",
+      "RangeIndex: 16512 entries, 0 to 16511\n",
+      "Data columns (total 10 columns):\n",
+      "longitude             16512 non-null float64\n",
+      "latitude              16512 non-null float64\n",
+      "housing_median_age    16512 non-null float64\n",
+      "total_rooms           16512 non-null float64\n",
+      "total_bedrooms        16512 non-null float64\n",
+      "population            16512 non-null float64\n",
+      "households            16512 non-null float64\n",
+      "median_income         16512 non-null float64\n",
+      "median_house_value    16512 non-null float64\n",
+      "ocean_proximity       16512 non-null object\n",
+      "dtypes: float64(9), object(1)\n",
+      "memory usage: 1.3+ MB\n"
+     ]
+    }
+   ],
+   "source": [
+    "train_set.info()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {},
+   "outputs": [
+    {
+     "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>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>count</th>\n",
+       "      <td>16512.000000</td>\n",
+       "      <td>16512.000000</td>\n",
+       "      <td>16512.000000</td>\n",
+       "      <td>16512.000000</td>\n",
+       "      <td>16512.000000</td>\n",
+       "      <td>16512.000000</td>\n",
+       "      <td>16512.000000</td>\n",
+       "      <td>16512.000000</td>\n",
+       "      <td>16512.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>mean</th>\n",
+       "      <td>-119.582290</td>\n",
+       "      <td>35.643149</td>\n",
+       "      <td>28.608285</td>\n",
+       "      <td>2642.004784</td>\n",
+       "      <td>538.496851</td>\n",
+       "      <td>1426.453004</td>\n",
+       "      <td>499.986919</td>\n",
+       "      <td>3.880754</td>\n",
+       "      <td>207194.693738</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>std</th>\n",
+       "      <td>2.005654</td>\n",
+       "      <td>2.136665</td>\n",
+       "      <td>12.602499</td>\n",
+       "      <td>2174.646744</td>\n",
+       "      <td>419.007096</td>\n",
+       "      <td>1137.056380</td>\n",
+       "      <td>380.967964</td>\n",
+       "      <td>1.904294</td>\n",
+       "      <td>115622.626448</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>min</th>\n",
+       "      <td>-124.350000</td>\n",
+       "      <td>32.550000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>2.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>3.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.499900</td>\n",
+       "      <td>14999.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>25%</th>\n",
+       "      <td>-121.810000</td>\n",
+       "      <td>33.930000</td>\n",
+       "      <td>18.000000</td>\n",
+       "      <td>1454.000000</td>\n",
+       "      <td>296.750000</td>\n",
+       "      <td>789.000000</td>\n",
+       "      <td>280.000000</td>\n",
+       "      <td>2.566700</td>\n",
+       "      <td>119800.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>50%</th>\n",
+       "      <td>-118.510000</td>\n",
+       "      <td>34.260000</td>\n",
+       "      <td>29.000000</td>\n",
+       "      <td>2129.000000</td>\n",
+       "      <td>437.000000</td>\n",
+       "      <td>1167.000000</td>\n",
+       "      <td>410.000000</td>\n",
+       "      <td>3.545800</td>\n",
+       "      <td>179850.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>75%</th>\n",
+       "      <td>-118.010000</td>\n",
+       "      <td>37.720000</td>\n",
+       "      <td>37.000000</td>\n",
+       "      <td>3160.000000</td>\n",
+       "      <td>647.000000</td>\n",
+       "      <td>1726.000000</td>\n",
+       "      <td>606.000000</td>\n",
+       "      <td>4.773175</td>\n",
+       "      <td>265125.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>max</th>\n",
+       "      <td>-114.310000</td>\n",
+       "      <td>41.950000</td>\n",
+       "      <td>52.000000</td>\n",
+       "      <td>39320.000000</td>\n",
+       "      <td>6445.000000</td>\n",
+       "      <td>35682.000000</td>\n",
+       "      <td>6082.000000</td>\n",
+       "      <td>15.000100</td>\n",
+       "      <td>500001.000000</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "          longitude      latitude  housing_median_age   total_rooms  \\\n",
+       "count  16512.000000  16512.000000        16512.000000  16512.000000   \n",
+       "mean    -119.582290     35.643149           28.608285   2642.004784   \n",
+       "std        2.005654      2.136665           12.602499   2174.646744   \n",
+       "min     -124.350000     32.550000            1.000000      2.000000   \n",
+       "25%     -121.810000     33.930000           18.000000   1454.000000   \n",
+       "50%     -118.510000     34.260000           29.000000   2129.000000   \n",
+       "75%     -118.010000     37.720000           37.000000   3160.000000   \n",
+       "max     -114.310000     41.950000           52.000000  39320.000000   \n",
+       "\n",
+       "       total_bedrooms    population    households  median_income  \\\n",
+       "count    16512.000000  16512.000000  16512.000000   16512.000000   \n",
+       "mean       538.496851   1426.453004    499.986919       3.880754   \n",
+       "std        419.007096   1137.056380    380.967964       1.904294   \n",
+       "min          1.000000      3.000000      1.000000       0.499900   \n",
+       "25%        296.750000    789.000000    280.000000       2.566700   \n",
+       "50%        437.000000   1167.000000    410.000000       3.545800   \n",
+       "75%        647.000000   1726.000000    606.000000       4.773175   \n",
+       "max       6445.000000  35682.000000   6082.000000      15.000100   \n",
+       "\n",
+       "       median_house_value  \n",
+       "count        16512.000000  \n",
+       "mean        207194.693738  \n",
+       "std         115622.626448  \n",
+       "min          14999.000000  \n",
+       "25%         119800.000000  \n",
+       "50%         179850.000000  \n",
+       "75%         265125.000000  \n",
+       "max         500001.000000  "
+      ]
+     },
+     "execution_count": 16,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "train_set.describe()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "longitude             0\n",
+       "latitude              0\n",
+       "housing_median_age    0\n",
+       "total_rooms           0\n",
+       "total_bedrooms        0\n",
+       "population            0\n",
+       "households            0\n",
+       "median_income         0\n",
+       "median_house_value    0\n",
+       "ocean_proximity       0\n",
+       "dtype: int64"
+      ]
+     },
+     "execution_count": 17,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "train_set.isnull().sum()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "metadata": {},
+   "outputs": [
+    {
+     "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>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",
+       "    <tr>\n",
+       "      <th>ocean_proximity</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>&lt;1H OCEAN</th>\n",
+       "      <td>7341</td>\n",
+       "      <td>7341</td>\n",
+       "      <td>7341</td>\n",
+       "      <td>7341</td>\n",
+       "      <td>7341</td>\n",
+       "      <td>7341</td>\n",
+       "      <td>7341</td>\n",
+       "      <td>7341</td>\n",
+       "      <td>7341</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>INLAND</th>\n",
+       "      <td>5227</td>\n",
+       "      <td>5227</td>\n",
+       "      <td>5227</td>\n",
+       "      <td>5227</td>\n",
+       "      <td>5227</td>\n",
+       "      <td>5227</td>\n",
+       "      <td>5227</td>\n",
+       "      <td>5227</td>\n",
+       "      <td>5227</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>ISLAND</th>\n",
+       "      <td>4</td>\n",
+       "      <td>4</td>\n",
+       "      <td>4</td>\n",
+       "      <td>4</td>\n",
+       "      <td>4</td>\n",
+       "      <td>4</td>\n",
+       "      <td>4</td>\n",
+       "      <td>4</td>\n",
+       "      <td>4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>NEAR BAY</th>\n",
+       "      <td>1854</td>\n",
+       "      <td>1854</td>\n",
+       "      <td>1854</td>\n",
+       "      <td>1854</td>\n",
+       "      <td>1854</td>\n",
+       "      <td>1854</td>\n",
+       "      <td>1854</td>\n",
+       "      <td>1854</td>\n",
+       "      <td>1854</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>NEAR OCEAN</th>\n",
+       "      <td>2086</td>\n",
+       "      <td>2086</td>\n",
+       "      <td>2086</td>\n",
+       "      <td>2086</td>\n",
+       "      <td>2086</td>\n",
+       "      <td>2086</td>\n",
+       "      <td>2086</td>\n",
+       "      <td>2086</td>\n",
+       "      <td>2086</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                 longitude  latitude  housing_median_age  total_rooms  \\\n",
+       "ocean_proximity                                                         \n",
+       "<1H OCEAN             7341      7341                7341         7341   \n",
+       "INLAND                5227      5227                5227         5227   \n",
+       "ISLAND                   4         4                   4            4   \n",
+       "NEAR BAY              1854      1854                1854         1854   \n",
+       "NEAR OCEAN            2086      2086                2086         2086   \n",
+       "\n",
+       "                 total_bedrooms  population  households  median_income  \\\n",
+       "ocean_proximity                                                          \n",
+       "<1H OCEAN                  7341        7341        7341           7341   \n",
+       "INLAND                     5227        5227        5227           5227   \n",
+       "ISLAND                        4           4           4              4   \n",
+       "NEAR BAY                   1854        1854        1854           1854   \n",
+       "NEAR OCEAN                 2086        2086        2086           2086   \n",
+       "\n",
+       "                 median_house_value  \n",
+       "ocean_proximity                      \n",
+       "<1H OCEAN                      7341  \n",
+       "INLAND                         5227  \n",
+       "ISLAND                            4  \n",
+       "NEAR BAY                       1854  \n",
+       "NEAR OCEAN                     2086  "
+      ]
+     },
+     "execution_count": 18,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "train_set.groupby('ocean_proximity').count()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### 可视化数据进行分析"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "每个列的数据直方图"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([[<matplotlib.axes._subplots.AxesSubplot object at 0x000002268D89B3C8>,\n",
+       "        <matplotlib.axes._subplots.AxesSubplot object at 0x000002268DA43128>,\n",
+       "        <matplotlib.axes._subplots.AxesSubplot object at 0x000002268DA69550>],\n",
+       "       [<matplotlib.axes._subplots.AxesSubplot object at 0x000002268DA8CA58>,\n",
+       "        <matplotlib.axes._subplots.AxesSubplot object at 0x000002268DAB1CC0>,\n",
+       "        <matplotlib.axes._subplots.AxesSubplot object at 0x000002268DAE3208>],\n",
+       "       [<matplotlib.axes._subplots.AxesSubplot object at 0x000002268DB09710>,\n",
+       "        <matplotlib.axes._subplots.AxesSubplot object at 0x000002268DB30C50>,\n",
+       "        <matplotlib.axes._subplots.AxesSubplot object at 0x000002268DB30C88>]],\n",
+       "      dtype=object)"
+      ]
+     },
+     "execution_count": 19,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1440x1080 with 9 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "train_set.hist(bins=50,figsize=(20,15))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "按地理位置的人口分布散点图"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.legend.Legend at 0x2268df80c50>"
+      ]
+     },
+     "execution_count": 20,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 2 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "train_set.plot(kind='scatter',x='longitude', y='latitude', alpha=0.4, s=train_set['population']/100,label='population', c='median_house_value',cmap=plt.get_cmap(\"jet\"),colorbar=True)\n",
+    "plt.legend()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### 研究样本属性之间的关系"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "metadata": {},
+   "outputs": [
+    {
+     "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>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>longitude</th>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>-0.924485</td>\n",
+       "      <td>-0.101818</td>\n",
+       "      <td>0.038676</td>\n",
+       "      <td>0.063064</td>\n",
+       "      <td>0.094276</td>\n",
+       "      <td>0.049306</td>\n",
+       "      <td>-0.017040</td>\n",
+       "      <td>-0.046349</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>latitude</th>\n",
+       "      <td>-0.924485</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.005296</td>\n",
+       "      <td>-0.029224</td>\n",
+       "      <td>-0.059998</td>\n",
+       "      <td>-0.102499</td>\n",
+       "      <td>-0.064061</td>\n",
+       "      <td>-0.076571</td>\n",
+       "      <td>-0.142983</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>housing_median_age</th>\n",
+       "      <td>-0.101818</td>\n",
+       "      <td>0.005296</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>-0.360922</td>\n",
+       "      <td>-0.320624</td>\n",
+       "      <td>-0.292283</td>\n",
+       "      <td>-0.302796</td>\n",
+       "      <td>-0.121711</td>\n",
+       "      <td>0.103706</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>total_rooms</th>\n",
+       "      <td>0.038676</td>\n",
+       "      <td>-0.029224</td>\n",
+       "      <td>-0.360922</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.930489</td>\n",
+       "      <td>0.857936</td>\n",
+       "      <td>0.920482</td>\n",
+       "      <td>0.198268</td>\n",
+       "      <td>0.133989</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>total_bedrooms</th>\n",
+       "      <td>0.063064</td>\n",
+       "      <td>-0.059998</td>\n",
+       "      <td>-0.320624</td>\n",
+       "      <td>0.930489</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.878932</td>\n",
+       "      <td>0.980255</td>\n",
+       "      <td>-0.009141</td>\n",
+       "      <td>0.047980</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>population</th>\n",
+       "      <td>0.094276</td>\n",
+       "      <td>-0.102499</td>\n",
+       "      <td>-0.292283</td>\n",
+       "      <td>0.857936</td>\n",
+       "      <td>0.878932</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.907452</td>\n",
+       "      <td>0.004122</td>\n",
+       "      <td>-0.026032</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>households</th>\n",
+       "      <td>0.049306</td>\n",
+       "      <td>-0.064061</td>\n",
+       "      <td>-0.302796</td>\n",
+       "      <td>0.920482</td>\n",
+       "      <td>0.980255</td>\n",
+       "      <td>0.907452</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.012776</td>\n",
+       "      <td>0.063714</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>median_income</th>\n",
+       "      <td>-0.017040</td>\n",
+       "      <td>-0.076571</td>\n",
+       "      <td>-0.121711</td>\n",
+       "      <td>0.198268</td>\n",
+       "      <td>-0.009141</td>\n",
+       "      <td>0.004122</td>\n",
+       "      <td>0.012776</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.690647</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>median_house_value</th>\n",
+       "      <td>-0.046349</td>\n",
+       "      <td>-0.142983</td>\n",
+       "      <td>0.103706</td>\n",
+       "      <td>0.133989</td>\n",
+       "      <td>0.047980</td>\n",
+       "      <td>-0.026032</td>\n",
+       "      <td>0.063714</td>\n",
+       "      <td>0.690647</td>\n",
+       "      <td>1.000000</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                    longitude  latitude  housing_median_age  total_rooms  \\\n",
+       "longitude            1.000000 -0.924485           -0.101818     0.038676   \n",
+       "latitude            -0.924485  1.000000            0.005296    -0.029224   \n",
+       "housing_median_age  -0.101818  0.005296            1.000000    -0.360922   \n",
+       "total_rooms          0.038676 -0.029224           -0.360922     1.000000   \n",
+       "total_bedrooms       0.063064 -0.059998           -0.320624     0.930489   \n",
+       "population           0.094276 -0.102499           -0.292283     0.857936   \n",
+       "households           0.049306 -0.064061           -0.302796     0.920482   \n",
+       "median_income       -0.017040 -0.076571           -0.121711     0.198268   \n",
+       "median_house_value  -0.046349 -0.142983            0.103706     0.133989   \n",
+       "\n",
+       "                    total_bedrooms  population  households  median_income  \\\n",
+       "longitude                 0.063064    0.094276    0.049306      -0.017040   \n",
+       "latitude                 -0.059998   -0.102499   -0.064061      -0.076571   \n",
+       "housing_median_age       -0.320624   -0.292283   -0.302796      -0.121711   \n",
+       "total_rooms               0.930489    0.857936    0.920482       0.198268   \n",
+       "total_bedrooms            1.000000    0.878932    0.980255      -0.009141   \n",
+       "population                0.878932    1.000000    0.907452       0.004122   \n",
+       "households                0.980255    0.907452    1.000000       0.012776   \n",
+       "median_income            -0.009141    0.004122    0.012776       1.000000   \n",
+       "median_house_value        0.047980   -0.026032    0.063714       0.690647   \n",
+       "\n",
+       "                    median_house_value  \n",
+       "longitude                    -0.046349  \n",
+       "latitude                     -0.142983  \n",
+       "housing_median_age            0.103706  \n",
+       "total_rooms                   0.133989  \n",
+       "total_bedrooms                0.047980  \n",
+       "population                   -0.026032  \n",
+       "households                    0.063714  \n",
+       "median_income                 0.690647  \n",
+       "median_house_value            1.000000  "
+      ]
+     },
+     "execution_count": 21,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "corr_matrix = train_set.corr()\n",
+    "corr_matrix"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "median_house_value    1.000000\n",
+       "median_income         0.690647\n",
+       "total_rooms           0.133989\n",
+       "housing_median_age    0.103706\n",
+       "households            0.063714\n",
+       "total_bedrooms        0.047980\n",
+       "population           -0.026032\n",
+       "longitude            -0.046349\n",
+       "latitude             -0.142983\n",
+       "Name: median_house_value, dtype: float64"
+      ]
+     },
+     "execution_count": 22,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "corr_matrix[\"median_house_value\"].sort_values(ascending=False)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "d:\\edwin_git\\我的博客\\mygithub\\test_python\\.venv\\lib\\site-packages\\ipykernel_launcher.py:3: FutureWarning: 'pandas.tools.plotting.scatter_matrix' is deprecated, import 'pandas.plotting.scatter_matrix' instead.\n",
+      "  This is separate from the ipykernel package so we can avoid doing imports until\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "array([[<matplotlib.axes._subplots.AxesSubplot object at 0x000002268E318E80>,\n",
+       "        <matplotlib.axes._subplots.AxesSubplot object at 0x000002268E4942B0>,\n",
+       "        <matplotlib.axes._subplots.AxesSubplot object at 0x000002268E33B780>,\n",
+       "        <matplotlib.axes._subplots.AxesSubplot object at 0x000002268E360C88>],\n",
+       "       [<matplotlib.axes._subplots.AxesSubplot object at 0x000002268E3901D0>,\n",
+       "        <matplotlib.axes._subplots.AxesSubplot object at 0x000002268E3B86D8>,\n",
+       "        <matplotlib.axes._subplots.AxesSubplot object at 0x000002268E3DFBE0>,\n",
+       "        <matplotlib.axes._subplots.AxesSubplot object at 0x000002268E40F160>],\n",
+       "       [<matplotlib.axes._subplots.AxesSubplot object at 0x000002268E40F198>,\n",
+       "        <matplotlib.axes._subplots.AxesSubplot object at 0x000002268E45FB38>,\n",
+       "        <matplotlib.axes._subplots.AxesSubplot object at 0x000002268E610080>,\n",
+       "        <matplotlib.axes._subplots.AxesSubplot object at 0x000002268E637588>],\n",
+       "       [<matplotlib.axes._subplots.AxesSubplot object at 0x000002268E660A90>,\n",
+       "        <matplotlib.axes._subplots.AxesSubplot object at 0x000002268FC2BF98>,\n",
+       "        <matplotlib.axes._subplots.AxesSubplot object at 0x000002268FC5A4E0>,\n",
+       "        <matplotlib.axes._subplots.AxesSubplot object at 0x000002268FC819E8>]],\n",
+       "      dtype=object)"
+      ]
+     },
+     "execution_count": 23,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 864x576 with 16 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "from pandas.tools.plotting import scatter_matrix\n",
+    "attributes = [\"median_house_value\",\"median_income\",\"total_rooms\",\"housing_median_age\"]\n",
+    "scatter_matrix(train_set[attributes],figsize=(12,8))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "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": "3.6.7"
+  },
+  "toc": {
+   "base_numbering": 1,
+   "nav_menu": {},
+   "number_sections": true,
+   "sideBar": true,
+   "skip_h1_title": false,
+   "title_cell": "Table of Contents",
+   "title_sidebar": "Contents",
+   "toc_cell": false,
+   "toc_position": {},
+   "toc_section_display": true,
+   "toc_window_display": true
+  },
+  "varInspector": {
+   "cols": {
+    "lenName": 16,
+    "lenType": 16,
+    "lenVar": 40
+   },
+   "kernels_config": {
+    "python": {
+     "delete_cmd_postfix": "",
+     "delete_cmd_prefix": "del ",
+     "library": "var_list.py",
+     "varRefreshCmd": "print(var_dic_list())"
+    },
+    "r": {
+     "delete_cmd_postfix": ") ",
+     "delete_cmd_prefix": "rm(",
+     "library": "var_list.r",
+     "varRefreshCmd": "cat(var_dic_list()) "
+    }
+   },
+   "types_to_exclude": [
+    "module",
+    "function",
+    "builtin_function_or_method",
+    "instance",
+    "_Feature"
+   ],
+   "window_display": false
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/california_housing_prices/.ipynb_checkpoints/california_data_prepare-checkpoint.ipynb b/california_housing_prices/.ipynb_checkpoints/california_data_prepare-checkpoint.ipynb
new file mode 100644
index 0000000..db20484
--- /dev/null
+++ b/california_housing_prices/.ipynb_checkpoints/california_data_prepare-checkpoint.ipynb
@@ -0,0 +1,1318 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "项目名称： 加利福尼亚房价预测"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## 分析数据特征"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### 将记录集装载到内存\n",
+    "\n",
+    "为了方便，建议将训练集的数据文件放在同一目录"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import pandas as pd\n",
+    "import numpy as np\n",
+    "import matplotlib.pyplot as plt\n",
+    "%matplotlib inline"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "datafilename = \"datasets\\\\train_set.csv\"\n",
+    "train_set_original = pd.read_csv(datafilename)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### 创建一个数据集的副本"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "train_set = train_set_original.copy()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### 检查数据集的大小"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(16512, 10)"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "train_set.shape"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### 获得数据集的所有特征名称及数据类型\n",
+    "\n",
+    "其中:标签列为 : media_house_value"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Index(['longitude', 'latitude', 'housing_median_age', 'total_rooms',\n",
+       "       'total_bedrooms', 'population', 'households', 'median_income',\n",
+       "       'median_house_value', 'ocean_proximity'],\n",
+       "      dtype='object')"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "train_set.columns"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "longitude             float64\n",
+       "latitude              float64\n",
+       "housing_median_age    float64\n",
+       "total_rooms           float64\n",
+       "total_bedrooms        float64\n",
+       "population            float64\n",
+       "households            float64\n",
+       "median_income         float64\n",
+       "median_house_value    float64\n",
+       "ocean_proximity        object\n",
+       "dtype: object"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "train_set.dtypes"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### 数据集的样本内容查看"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [
+    {
+     "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>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",
+       "      <th>ocean_proximity</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>-117.03</td>\n",
+       "      <td>32.71</td>\n",
+       "      <td>33.0</td>\n",
+       "      <td>3126.0</td>\n",
+       "      <td>627.0</td>\n",
+       "      <td>2300.0</td>\n",
+       "      <td>623.0</td>\n",
+       "      <td>3.2596</td>\n",
+       "      <td>103000.0</td>\n",
+       "      <td>NEAR OCEAN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>-118.16</td>\n",
+       "      <td>33.77</td>\n",
+       "      <td>49.0</td>\n",
+       "      <td>3382.0</td>\n",
+       "      <td>787.0</td>\n",
+       "      <td>1314.0</td>\n",
+       "      <td>756.0</td>\n",
+       "      <td>3.8125</td>\n",
+       "      <td>382100.0</td>\n",
+       "      <td>NEAR OCEAN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>-120.48</td>\n",
+       "      <td>34.66</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>1897.0</td>\n",
+       "      <td>331.0</td>\n",
+       "      <td>915.0</td>\n",
+       "      <td>336.0</td>\n",
+       "      <td>4.1563</td>\n",
+       "      <td>172600.0</td>\n",
+       "      <td>NEAR OCEAN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>-117.11</td>\n",
+       "      <td>32.69</td>\n",
+       "      <td>36.0</td>\n",
+       "      <td>1421.0</td>\n",
+       "      <td>367.0</td>\n",
+       "      <td>1418.0</td>\n",
+       "      <td>355.0</td>\n",
+       "      <td>1.9425</td>\n",
+       "      <td>93400.0</td>\n",
+       "      <td>NEAR OCEAN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>-119.80</td>\n",
+       "      <td>36.78</td>\n",
+       "      <td>43.0</td>\n",
+       "      <td>2382.0</td>\n",
+       "      <td>431.0</td>\n",
+       "      <td>874.0</td>\n",
+       "      <td>380.0</td>\n",
+       "      <td>3.5542</td>\n",
+       "      <td>96500.0</td>\n",
+       "      <td>INLAND</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   longitude  latitude  housing_median_age  total_rooms  total_bedrooms  \\\n",
+       "0    -117.03     32.71                33.0       3126.0           627.0   \n",
+       "1    -118.16     33.77                49.0       3382.0           787.0   \n",
+       "2    -120.48     34.66                 4.0       1897.0           331.0   \n",
+       "3    -117.11     32.69                36.0       1421.0           367.0   \n",
+       "4    -119.80     36.78                43.0       2382.0           431.0   \n",
+       "\n",
+       "   population  households  median_income  median_house_value ocean_proximity  \n",
+       "0      2300.0       623.0         3.2596            103000.0      NEAR OCEAN  \n",
+       "1      1314.0       756.0         3.8125            382100.0      NEAR OCEAN  \n",
+       "2       915.0       336.0         4.1563            172600.0      NEAR OCEAN  \n",
+       "3      1418.0       355.0         1.9425             93400.0      NEAR OCEAN  \n",
+       "4       874.0       380.0         3.5542             96500.0          INLAND  "
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "train_set.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [
+    {
+     "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>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",
+       "      <th>ocean_proximity</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>16507</th>\n",
+       "      <td>-117.96</td>\n",
+       "      <td>33.78</td>\n",
+       "      <td>35.0</td>\n",
+       "      <td>1330.0</td>\n",
+       "      <td>201.0</td>\n",
+       "      <td>658.0</td>\n",
+       "      <td>217.0</td>\n",
+       "      <td>6.3700</td>\n",
+       "      <td>229200.0</td>\n",
+       "      <td>&lt;1H OCEAN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>16508</th>\n",
+       "      <td>-117.43</td>\n",
+       "      <td>34.02</td>\n",
+       "      <td>33.0</td>\n",
+       "      <td>3084.0</td>\n",
+       "      <td>570.0</td>\n",
+       "      <td>1753.0</td>\n",
+       "      <td>449.0</td>\n",
+       "      <td>3.0500</td>\n",
+       "      <td>97800.0</td>\n",
+       "      <td>INLAND</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>16509</th>\n",
+       "      <td>-118.38</td>\n",
+       "      <td>34.03</td>\n",
+       "      <td>36.0</td>\n",
+       "      <td>2101.0</td>\n",
+       "      <td>569.0</td>\n",
+       "      <td>1756.0</td>\n",
+       "      <td>527.0</td>\n",
+       "      <td>2.9344</td>\n",
+       "      <td>222100.0</td>\n",
+       "      <td>&lt;1H OCEAN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>16510</th>\n",
+       "      <td>-121.96</td>\n",
+       "      <td>37.58</td>\n",
+       "      <td>15.0</td>\n",
+       "      <td>3575.0</td>\n",
+       "      <td>597.0</td>\n",
+       "      <td>1777.0</td>\n",
+       "      <td>559.0</td>\n",
+       "      <td>5.7192</td>\n",
+       "      <td>283500.0</td>\n",
+       "      <td>&lt;1H OCEAN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>16511</th>\n",
+       "      <td>-122.42</td>\n",
+       "      <td>37.77</td>\n",
+       "      <td>52.0</td>\n",
+       "      <td>4226.0</td>\n",
+       "      <td>1315.0</td>\n",
+       "      <td>2619.0</td>\n",
+       "      <td>1242.0</td>\n",
+       "      <td>2.5755</td>\n",
+       "      <td>325000.0</td>\n",
+       "      <td>NEAR BAY</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "       longitude  latitude  housing_median_age  total_rooms  total_bedrooms  \\\n",
+       "16507    -117.96     33.78                35.0       1330.0           201.0   \n",
+       "16508    -117.43     34.02                33.0       3084.0           570.0   \n",
+       "16509    -118.38     34.03                36.0       2101.0           569.0   \n",
+       "16510    -121.96     37.58                15.0       3575.0           597.0   \n",
+       "16511    -122.42     37.77                52.0       4226.0          1315.0   \n",
+       "\n",
+       "       population  households  median_income  median_house_value  \\\n",
+       "16507       658.0       217.0         6.3700            229200.0   \n",
+       "16508      1753.0       449.0         3.0500             97800.0   \n",
+       "16509      1756.0       527.0         2.9344            222100.0   \n",
+       "16510      1777.0       559.0         5.7192            283500.0   \n",
+       "16511      2619.0      1242.0         2.5755            325000.0   \n",
+       "\n",
+       "      ocean_proximity  \n",
+       "16507       <1H OCEAN  \n",
+       "16508          INLAND  \n",
+       "16509       <1H OCEAN  \n",
+       "16510       <1H OCEAN  \n",
+       "16511        NEAR BAY  "
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "train_set.tail()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### 特征数据的分布情况"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<1H OCEAN     7341\n",
+       "INLAND        5227\n",
+       "NEAR OCEAN    2086\n",
+       "NEAR BAY      1854\n",
+       "ISLAND           4\n",
+       "Name: ocean_proximity, dtype: int64"
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "train_set[\"ocean_proximity\"].value_counts()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### 数据集的快速统计分析"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "<class 'pandas.core.frame.DataFrame'>\n",
+      "RangeIndex: 16512 entries, 0 to 16511\n",
+      "Data columns (total 10 columns):\n",
+      "longitude             16512 non-null float64\n",
+      "latitude              16512 non-null float64\n",
+      "housing_median_age    16512 non-null float64\n",
+      "total_rooms           16512 non-null float64\n",
+      "total_bedrooms        16512 non-null float64\n",
+      "population            16512 non-null float64\n",
+      "households            16512 non-null float64\n",
+      "median_income         16512 non-null float64\n",
+      "median_house_value    16512 non-null float64\n",
+      "ocean_proximity       16512 non-null object\n",
+      "dtypes: float64(9), object(1)\n",
+      "memory usage: 1.3+ MB\n"
+     ]
+    }
+   ],
+   "source": [
+    "train_set.info()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [
+    {
+     "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>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>count</th>\n",
+       "      <td>16512.000000</td>\n",
+       "      <td>16512.000000</td>\n",
+       "      <td>16512.000000</td>\n",
+       "      <td>16512.000000</td>\n",
+       "      <td>16512.000000</td>\n",
+       "      <td>16512.000000</td>\n",
+       "      <td>16512.000000</td>\n",
+       "      <td>16512.000000</td>\n",
+       "      <td>16512.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>mean</th>\n",
+       "      <td>-119.582290</td>\n",
+       "      <td>35.643149</td>\n",
+       "      <td>28.608285</td>\n",
+       "      <td>2642.004784</td>\n",
+       "      <td>538.496851</td>\n",
+       "      <td>1426.453004</td>\n",
+       "      <td>499.986919</td>\n",
+       "      <td>3.880754</td>\n",
+       "      <td>207194.693738</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>std</th>\n",
+       "      <td>2.005654</td>\n",
+       "      <td>2.136665</td>\n",
+       "      <td>12.602499</td>\n",
+       "      <td>2174.646744</td>\n",
+       "      <td>419.007096</td>\n",
+       "      <td>1137.056380</td>\n",
+       "      <td>380.967964</td>\n",
+       "      <td>1.904294</td>\n",
+       "      <td>115622.626448</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>min</th>\n",
+       "      <td>-124.350000</td>\n",
+       "      <td>32.550000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>2.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>3.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.499900</td>\n",
+       "      <td>14999.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>25%</th>\n",
+       "      <td>-121.810000</td>\n",
+       "      <td>33.930000</td>\n",
+       "      <td>18.000000</td>\n",
+       "      <td>1454.000000</td>\n",
+       "      <td>296.750000</td>\n",
+       "      <td>789.000000</td>\n",
+       "      <td>280.000000</td>\n",
+       "      <td>2.566700</td>\n",
+       "      <td>119800.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>50%</th>\n",
+       "      <td>-118.510000</td>\n",
+       "      <td>34.260000</td>\n",
+       "      <td>29.000000</td>\n",
+       "      <td>2129.000000</td>\n",
+       "      <td>437.000000</td>\n",
+       "      <td>1167.000000</td>\n",
+       "      <td>410.000000</td>\n",
+       "      <td>3.545800</td>\n",
+       "      <td>179850.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>75%</th>\n",
+       "      <td>-118.010000</td>\n",
+       "      <td>37.720000</td>\n",
+       "      <td>37.000000</td>\n",
+       "      <td>3160.000000</td>\n",
+       "      <td>647.000000</td>\n",
+       "      <td>1726.000000</td>\n",
+       "      <td>606.000000</td>\n",
+       "      <td>4.773175</td>\n",
+       "      <td>265125.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>max</th>\n",
+       "      <td>-114.310000</td>\n",
+       "      <td>41.950000</td>\n",
+       "      <td>52.000000</td>\n",
+       "      <td>39320.000000</td>\n",
+       "      <td>6445.000000</td>\n",
+       "      <td>35682.000000</td>\n",
+       "      <td>6082.000000</td>\n",
+       "      <td>15.000100</td>\n",
+       "      <td>500001.000000</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "          longitude      latitude  housing_median_age   total_rooms  \\\n",
+       "count  16512.000000  16512.000000        16512.000000  16512.000000   \n",
+       "mean    -119.582290     35.643149           28.608285   2642.004784   \n",
+       "std        2.005654      2.136665           12.602499   2174.646744   \n",
+       "min     -124.350000     32.550000            1.000000      2.000000   \n",
+       "25%     -121.810000     33.930000           18.000000   1454.000000   \n",
+       "50%     -118.510000     34.260000           29.000000   2129.000000   \n",
+       "75%     -118.010000     37.720000           37.000000   3160.000000   \n",
+       "max     -114.310000     41.950000           52.000000  39320.000000   \n",
+       "\n",
+       "       total_bedrooms    population    households  median_income  \\\n",
+       "count    16512.000000  16512.000000  16512.000000   16512.000000   \n",
+       "mean       538.496851   1426.453004    499.986919       3.880754   \n",
+       "std        419.007096   1137.056380    380.967964       1.904294   \n",
+       "min          1.000000      3.000000      1.000000       0.499900   \n",
+       "25%        296.750000    789.000000    280.000000       2.566700   \n",
+       "50%        437.000000   1167.000000    410.000000       3.545800   \n",
+       "75%        647.000000   1726.000000    606.000000       4.773175   \n",
+       "max       6445.000000  35682.000000   6082.000000      15.000100   \n",
+       "\n",
+       "       median_house_value  \n",
+       "count        16512.000000  \n",
+       "mean        207194.693738  \n",
+       "std         115622.626448  \n",
+       "min          14999.000000  \n",
+       "25%         119800.000000  \n",
+       "50%         179850.000000  \n",
+       "75%         265125.000000  \n",
+       "max         500001.000000  "
+      ]
+     },
+     "execution_count": 11,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "train_set.describe()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "longitude             0\n",
+       "latitude              0\n",
+       "housing_median_age    0\n",
+       "total_rooms           0\n",
+       "total_bedrooms        0\n",
+       "population            0\n",
+       "households            0\n",
+       "median_income         0\n",
+       "median_house_value    0\n",
+       "ocean_proximity       0\n",
+       "dtype: int64"
+      ]
+     },
+     "execution_count": 12,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "train_set.isnull().sum()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [
+    {
+     "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>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",
+       "    <tr>\n",
+       "      <th>ocean_proximity</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>&lt;1H OCEAN</th>\n",
+       "      <td>7341</td>\n",
+       "      <td>7341</td>\n",
+       "      <td>7341</td>\n",
+       "      <td>7341</td>\n",
+       "      <td>7341</td>\n",
+       "      <td>7341</td>\n",
+       "      <td>7341</td>\n",
+       "      <td>7341</td>\n",
+       "      <td>7341</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>INLAND</th>\n",
+       "      <td>5227</td>\n",
+       "      <td>5227</td>\n",
+       "      <td>5227</td>\n",
+       "      <td>5227</td>\n",
+       "      <td>5227</td>\n",
+       "      <td>5227</td>\n",
+       "      <td>5227</td>\n",
+       "      <td>5227</td>\n",
+       "      <td>5227</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>ISLAND</th>\n",
+       "      <td>4</td>\n",
+       "      <td>4</td>\n",
+       "      <td>4</td>\n",
+       "      <td>4</td>\n",
+       "      <td>4</td>\n",
+       "      <td>4</td>\n",
+       "      <td>4</td>\n",
+       "      <td>4</td>\n",
+       "      <td>4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>NEAR BAY</th>\n",
+       "      <td>1854</td>\n",
+       "      <td>1854</td>\n",
+       "      <td>1854</td>\n",
+       "      <td>1854</td>\n",
+       "      <td>1854</td>\n",
+       "      <td>1854</td>\n",
+       "      <td>1854</td>\n",
+       "      <td>1854</td>\n",
+       "      <td>1854</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>NEAR OCEAN</th>\n",
+       "      <td>2086</td>\n",
+       "      <td>2086</td>\n",
+       "      <td>2086</td>\n",
+       "      <td>2086</td>\n",
+       "      <td>2086</td>\n",
+       "      <td>2086</td>\n",
+       "      <td>2086</td>\n",
+       "      <td>2086</td>\n",
+       "      <td>2086</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                 longitude  latitude  housing_median_age  total_rooms  \\\n",
+       "ocean_proximity                                                         \n",
+       "<1H OCEAN             7341      7341                7341         7341   \n",
+       "INLAND                5227      5227                5227         5227   \n",
+       "ISLAND                   4         4                   4            4   \n",
+       "NEAR BAY              1854      1854                1854         1854   \n",
+       "NEAR OCEAN            2086      2086                2086         2086   \n",
+       "\n",
+       "                 total_bedrooms  population  households  median_income  \\\n",
+       "ocean_proximity                                                          \n",
+       "<1H OCEAN                  7341        7341        7341           7341   \n",
+       "INLAND                     5227        5227        5227           5227   \n",
+       "ISLAND                        4           4           4              4   \n",
+       "NEAR BAY                   1854        1854        1854           1854   \n",
+       "NEAR OCEAN                 2086        2086        2086           2086   \n",
+       "\n",
+       "                 median_house_value  \n",
+       "ocean_proximity                      \n",
+       "<1H OCEAN                      7341  \n",
+       "INLAND                         5227  \n",
+       "ISLAND                            4  \n",
+       "NEAR BAY                       1854  \n",
+       "NEAR OCEAN                     2086  "
+      ]
+     },
+     "execution_count": 13,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "train_set.groupby('ocean_proximity').count()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### 可视化数据进行分析"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "每个列的数据直方图"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([[<matplotlib.axes._subplots.AxesSubplot object at 0x000001688C4F07F0>,\n",
+       "        <matplotlib.axes._subplots.AxesSubplot object at 0x000001688C558A20>,\n",
+       "        <matplotlib.axes._subplots.AxesSubplot object at 0x000001688C580EF0>],\n",
+       "       [<matplotlib.axes._subplots.AxesSubplot object at 0x000001688C5AD438>,\n",
+       "        <matplotlib.axes._subplots.AxesSubplot object at 0x000001688C5D38D0>,\n",
+       "        <matplotlib.axes._subplots.AxesSubplot object at 0x000001688C5FCDD8>],\n",
+       "       [<matplotlib.axes._subplots.AxesSubplot object at 0x000001688C62D320>,\n",
+       "        <matplotlib.axes._subplots.AxesSubplot object at 0x000001688C651860>,\n",
+       "        <matplotlib.axes._subplots.AxesSubplot object at 0x000001688C651898>]],\n",
+       "      dtype=object)"
+      ]
+     },
+     "execution_count": 14,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1440x1080 with 9 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "train_set.hist(bins=50,figsize=(20,15))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "按地理位置的人口分布散点图"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.legend.Legend at 0x1688c96a240>"
+      ]
+     },
+     "execution_count": 15,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 2 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "train_set.plot(kind='scatter',x='longitude', y='latitude', alpha=0.4, s=train_set['population']/100,label='population', c='median_house_value',cmap=plt.get_cmap(\"jet\"),colorbar=True)\n",
+    "plt.legend()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### 研究样本属性之间的关系"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {},
+   "outputs": [
+    {
+     "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>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>longitude</th>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>-0.924485</td>\n",
+       "      <td>-0.101818</td>\n",
+       "      <td>0.038676</td>\n",
+       "      <td>0.063064</td>\n",
+       "      <td>0.094276</td>\n",
+       "      <td>0.049306</td>\n",
+       "      <td>-0.017040</td>\n",
+       "      <td>-0.046349</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>latitude</th>\n",
+       "      <td>-0.924485</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.005296</td>\n",
+       "      <td>-0.029224</td>\n",
+       "      <td>-0.059998</td>\n",
+       "      <td>-0.102499</td>\n",
+       "      <td>-0.064061</td>\n",
+       "      <td>-0.076571</td>\n",
+       "      <td>-0.142983</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>housing_median_age</th>\n",
+       "      <td>-0.101818</td>\n",
+       "      <td>0.005296</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>-0.360922</td>\n",
+       "      <td>-0.320624</td>\n",
+       "      <td>-0.292283</td>\n",
+       "      <td>-0.302796</td>\n",
+       "      <td>-0.121711</td>\n",
+       "      <td>0.103706</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>total_rooms</th>\n",
+       "      <td>0.038676</td>\n",
+       "      <td>-0.029224</td>\n",
+       "      <td>-0.360922</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.930489</td>\n",
+       "      <td>0.857936</td>\n",
+       "      <td>0.920482</td>\n",
+       "      <td>0.198268</td>\n",
+       "      <td>0.133989</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>total_bedrooms</th>\n",
+       "      <td>0.063064</td>\n",
+       "      <td>-0.059998</td>\n",
+       "      <td>-0.320624</td>\n",
+       "      <td>0.930489</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.878932</td>\n",
+       "      <td>0.980255</td>\n",
+       "      <td>-0.009141</td>\n",
+       "      <td>0.047980</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>population</th>\n",
+       "      <td>0.094276</td>\n",
+       "      <td>-0.102499</td>\n",
+       "      <td>-0.292283</td>\n",
+       "      <td>0.857936</td>\n",
+       "      <td>0.878932</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.907452</td>\n",
+       "      <td>0.004122</td>\n",
+       "      <td>-0.026032</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>households</th>\n",
+       "      <td>0.049306</td>\n",
+       "      <td>-0.064061</td>\n",
+       "      <td>-0.302796</td>\n",
+       "      <td>0.920482</td>\n",
+       "      <td>0.980255</td>\n",
+       "      <td>0.907452</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.012776</td>\n",
+       "      <td>0.063714</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>median_income</th>\n",
+       "      <td>-0.017040</td>\n",
+       "      <td>-0.076571</td>\n",
+       "      <td>-0.121711</td>\n",
+       "      <td>0.198268</td>\n",
+       "      <td>-0.009141</td>\n",
+       "      <td>0.004122</td>\n",
+       "      <td>0.012776</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.690647</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>median_house_value</th>\n",
+       "      <td>-0.046349</td>\n",
+       "      <td>-0.142983</td>\n",
+       "      <td>0.103706</td>\n",
+       "      <td>0.133989</td>\n",
+       "      <td>0.047980</td>\n",
+       "      <td>-0.026032</td>\n",
+       "      <td>0.063714</td>\n",
+       "      <td>0.690647</td>\n",
+       "      <td>1.000000</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                    longitude  latitude  housing_median_age  total_rooms  \\\n",
+       "longitude            1.000000 -0.924485           -0.101818     0.038676   \n",
+       "latitude            -0.924485  1.000000            0.005296    -0.029224   \n",
+       "housing_median_age  -0.101818  0.005296            1.000000    -0.360922   \n",
+       "total_rooms          0.038676 -0.029224           -0.360922     1.000000   \n",
+       "total_bedrooms       0.063064 -0.059998           -0.320624     0.930489   \n",
+       "population           0.094276 -0.102499           -0.292283     0.857936   \n",
+       "households           0.049306 -0.064061           -0.302796     0.920482   \n",
+       "median_income       -0.017040 -0.076571           -0.121711     0.198268   \n",
+       "median_house_value  -0.046349 -0.142983            0.103706     0.133989   \n",
+       "\n",
+       "                    total_bedrooms  population  households  median_income  \\\n",
+       "longitude                 0.063064    0.094276    0.049306      -0.017040   \n",
+       "latitude                 -0.059998   -0.102499   -0.064061      -0.076571   \n",
+       "housing_median_age       -0.320624   -0.292283   -0.302796      -0.121711   \n",
+       "total_rooms               0.930489    0.857936    0.920482       0.198268   \n",
+       "total_bedrooms            1.000000    0.878932    0.980255      -0.009141   \n",
+       "population                0.878932    1.000000    0.907452       0.004122   \n",
+       "households                0.980255    0.907452    1.000000       0.012776   \n",
+       "median_income            -0.009141    0.004122    0.012776       1.000000   \n",
+       "median_house_value        0.047980   -0.026032    0.063714       0.690647   \n",
+       "\n",
+       "                    median_house_value  \n",
+       "longitude                    -0.046349  \n",
+       "latitude                     -0.142983  \n",
+       "housing_median_age            0.103706  \n",
+       "total_rooms                   0.133989  \n",
+       "total_bedrooms                0.047980  \n",
+       "population                   -0.026032  \n",
+       "households                    0.063714  \n",
+       "median_income                 0.690647  \n",
+       "median_house_value            1.000000  "
+      ]
+     },
+     "execution_count": 16,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "corr_matrix = train_set.corr()\n",
+    "corr_matrix"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "median_house_value    1.000000\n",
+       "median_income         0.690647\n",
+       "total_rooms           0.133989\n",
+       "housing_median_age    0.103706\n",
+       "households            0.063714\n",
+       "total_bedrooms        0.047980\n",
+       "population           -0.026032\n",
+       "longitude            -0.046349\n",
+       "latitude             -0.142983\n",
+       "Name: median_house_value, dtype: float64"
+      ]
+     },
+     "execution_count": 17,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "corr_matrix[\"median_house_value\"].sort_values(ascending=False)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "D:\\Edwin_Git\\我的博客\\MyGitHub\\Python\\.venv\\lib\\site-packages\\ipykernel_launcher.py:3: FutureWarning: 'pandas.tools.plotting.scatter_matrix' is deprecated, import 'pandas.plotting.scatter_matrix' instead.\n",
+      "  This is separate from the ipykernel package so we can avoid doing imports until\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "array([[<matplotlib.axes._subplots.AxesSubplot object at 0x000001688CC27CF8>,\n",
+       "        <matplotlib.axes._subplots.AxesSubplot object at 0x000001688CC5DF98>,\n",
+       "        <matplotlib.axes._subplots.AxesSubplot object at 0x000001688CC8B2E8>,\n",
+       "        <matplotlib.axes._subplots.AxesSubplot object at 0x000001688CCAF7F0>],\n",
+       "       [<matplotlib.axes._subplots.AxesSubplot object at 0x000001688CCD5CC0>,\n",
+       "        <matplotlib.axes._subplots.AxesSubplot object at 0x000001688CFA7208>,\n",
+       "        <matplotlib.axes._subplots.AxesSubplot object at 0x000001688CFCB710>,\n",
+       "        <matplotlib.axes._subplots.AxesSubplot object at 0x000001688CFF4C50>],\n",
+       "       [<matplotlib.axes._subplots.AxesSubplot object at 0x000001688CFF4C88>,\n",
+       "        <matplotlib.axes._subplots.AxesSubplot object at 0x000001688D04E668>,\n",
+       "        <matplotlib.axes._subplots.AxesSubplot object at 0x000001688D074B70>,\n",
+       "        <matplotlib.axes._subplots.AxesSubplot object at 0x000001688D0A40B8>],\n",
+       "       [<matplotlib.axes._subplots.AxesSubplot object at 0x000001688D0CB5C0>,\n",
+       "        <matplotlib.axes._subplots.AxesSubplot object at 0x000001688D0F5AC8>,\n",
+       "        <matplotlib.axes._subplots.AxesSubplot object at 0x000001688D11CFD0>,\n",
+       "        <matplotlib.axes._subplots.AxesSubplot object at 0x000001688D14F518>]],\n",
+       "      dtype=object)"
+      ]
+     },
+     "execution_count": 18,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 864x576 with 16 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "from pandas.tools.plotting import scatter_matrix\n",
+    "attributes = [\"median_house_value\",\"median_income\",\"total_rooms\",\"housing_median_age\"]\n",
+    "scatter_matrix(train_set[attributes],figsize=(12,8))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "env_python367",
+   "language": "python",
+   "name": ".venv"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.6.7"
+  },
+  "toc": {
+   "base_numbering": 1,
+   "nav_menu": {},
+   "number_sections": true,
+   "sideBar": true,
+   "skip_h1_title": false,
+   "title_cell": "Table of Contents",
+   "title_sidebar": "Contents",
+   "toc_cell": false,
+   "toc_position": {},
+   "toc_section_display": true,
+   "toc_window_display": true
+  },
+  "varInspector": {
+   "cols": {
+    "lenName": 16,
+    "lenType": 16,
+    "lenVar": 40
+   },
+   "kernels_config": {
+    "python": {
+     "delete_cmd_postfix": "",
+     "delete_cmd_prefix": "del ",
+     "library": "var_list.py",
+     "varRefreshCmd": "print(var_dic_list())"
+    },
+    "r": {
+     "delete_cmd_postfix": ") ",
+     "delete_cmd_prefix": "rm(",
+     "library": "var_list.r",
+     "varRefreshCmd": "cat(var_dic_list()) "
+    }
+   },
+   "types_to_exclude": [
+    "module",
+    "function",
+    "builtin_function_or_method",
+    "instance",
+    "_Feature"
+   ],
+   "window_display": false
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/Netural Style Transfer/framework/__init__.py b/california_housing_prices/__init__.py
similarity index 100%
rename from Netural Style Transfer/framework/__init__.py
rename to california_housing_prices/__init__.py
diff --git a/california_housing_prices/california_data_prepare.ipynb b/california_housing_prices/california_data_prepare.ipynb
new file mode 100644
index 0000000..db20484
--- /dev/null
+++ b/california_housing_prices/california_data_prepare.ipynb
@@ -0,0 +1,1318 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "项目名称： 加利福尼亚房价预测"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## 分析数据特征"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### 将记录集装载到内存\n",
+    "\n",
+    "为了方便，建议将训练集的数据文件放在同一目录"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import pandas as pd\n",
+    "import numpy as np\n",
+    "import matplotlib.pyplot as plt\n",
+    "%matplotlib inline"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "datafilename = \"datasets\\\\train_set.csv\"\n",
+    "train_set_original = pd.read_csv(datafilename)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### 创建一个数据集的副本"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "train_set = train_set_original.copy()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### 检查数据集的大小"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(16512, 10)"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "train_set.shape"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### 获得数据集的所有特征名称及数据类型\n",
+    "\n",
+    "其中:标签列为 : media_house_value"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Index(['longitude', 'latitude', 'housing_median_age', 'total_rooms',\n",
+       "       'total_bedrooms', 'population', 'households', 'median_income',\n",
+       "       'median_house_value', 'ocean_proximity'],\n",
+       "      dtype='object')"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "train_set.columns"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "longitude             float64\n",
+       "latitude              float64\n",
+       "housing_median_age    float64\n",
+       "total_rooms           float64\n",
+       "total_bedrooms        float64\n",
+       "population            float64\n",
+       "households            float64\n",
+       "median_income         float64\n",
+       "median_house_value    float64\n",
+       "ocean_proximity        object\n",
+       "dtype: object"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "train_set.dtypes"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### 数据集的样本内容查看"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [
+    {
+     "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>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",
+       "      <th>ocean_proximity</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>-117.03</td>\n",
+       "      <td>32.71</td>\n",
+       "      <td>33.0</td>\n",
+       "      <td>3126.0</td>\n",
+       "      <td>627.0</td>\n",
+       "      <td>2300.0</td>\n",
+       "      <td>623.0</td>\n",
+       "      <td>3.2596</td>\n",
+       "      <td>103000.0</td>\n",
+       "      <td>NEAR OCEAN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>-118.16</td>\n",
+       "      <td>33.77</td>\n",
+       "      <td>49.0</td>\n",
+       "      <td>3382.0</td>\n",
+       "      <td>787.0</td>\n",
+       "      <td>1314.0</td>\n",
+       "      <td>756.0</td>\n",
+       "      <td>3.8125</td>\n",
+       "      <td>382100.0</td>\n",
+       "      <td>NEAR OCEAN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>-120.48</td>\n",
+       "      <td>34.66</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>1897.0</td>\n",
+       "      <td>331.0</td>\n",
+       "      <td>915.0</td>\n",
+       "      <td>336.0</td>\n",
+       "      <td>4.1563</td>\n",
+       "      <td>172600.0</td>\n",
+       "      <td>NEAR OCEAN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>-117.11</td>\n",
+       "      <td>32.69</td>\n",
+       "      <td>36.0</td>\n",
+       "      <td>1421.0</td>\n",
+       "      <td>367.0</td>\n",
+       "      <td>1418.0</td>\n",
+       "      <td>355.0</td>\n",
+       "      <td>1.9425</td>\n",
+       "      <td>93400.0</td>\n",
+       "      <td>NEAR OCEAN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>-119.80</td>\n",
+       "      <td>36.78</td>\n",
+       "      <td>43.0</td>\n",
+       "      <td>2382.0</td>\n",
+       "      <td>431.0</td>\n",
+       "      <td>874.0</td>\n",
+       "      <td>380.0</td>\n",
+       "      <td>3.5542</td>\n",
+       "      <td>96500.0</td>\n",
+       "      <td>INLAND</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   longitude  latitude  housing_median_age  total_rooms  total_bedrooms  \\\n",
+       "0    -117.03     32.71                33.0       3126.0           627.0   \n",
+       "1    -118.16     33.77                49.0       3382.0           787.0   \n",
+       "2    -120.48     34.66                 4.0       1897.0           331.0   \n",
+       "3    -117.11     32.69                36.0       1421.0           367.0   \n",
+       "4    -119.80     36.78                43.0       2382.0           431.0   \n",
+       "\n",
+       "   population  households  median_income  median_house_value ocean_proximity  \n",
+       "0      2300.0       623.0         3.2596            103000.0      NEAR OCEAN  \n",
+       "1      1314.0       756.0         3.8125            382100.0      NEAR OCEAN  \n",
+       "2       915.0       336.0         4.1563            172600.0      NEAR OCEAN  \n",
+       "3      1418.0       355.0         1.9425             93400.0      NEAR OCEAN  \n",
+       "4       874.0       380.0         3.5542             96500.0          INLAND  "
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "train_set.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [
+    {
+     "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>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",
+       "      <th>ocean_proximity</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>16507</th>\n",
+       "      <td>-117.96</td>\n",
+       "      <td>33.78</td>\n",
+       "      <td>35.0</td>\n",
+       "      <td>1330.0</td>\n",
+       "      <td>201.0</td>\n",
+       "      <td>658.0</td>\n",
+       "      <td>217.0</td>\n",
+       "      <td>6.3700</td>\n",
+       "      <td>229200.0</td>\n",
+       "      <td>&lt;1H OCEAN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>16508</th>\n",
+       "      <td>-117.43</td>\n",
+       "      <td>34.02</td>\n",
+       "      <td>33.0</td>\n",
+       "      <td>3084.0</td>\n",
+       "      <td>570.0</td>\n",
+       "      <td>1753.0</td>\n",
+       "      <td>449.0</td>\n",
+       "      <td>3.0500</td>\n",
+       "      <td>97800.0</td>\n",
+       "      <td>INLAND</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>16509</th>\n",
+       "      <td>-118.38</td>\n",
+       "      <td>34.03</td>\n",
+       "      <td>36.0</td>\n",
+       "      <td>2101.0</td>\n",
+       "      <td>569.0</td>\n",
+       "      <td>1756.0</td>\n",
+       "      <td>527.0</td>\n",
+       "      <td>2.9344</td>\n",
+       "      <td>222100.0</td>\n",
+       "      <td>&lt;1H OCEAN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>16510</th>\n",
+       "      <td>-121.96</td>\n",
+       "      <td>37.58</td>\n",
+       "      <td>15.0</td>\n",
+       "      <td>3575.0</td>\n",
+       "      <td>597.0</td>\n",
+       "      <td>1777.0</td>\n",
+       "      <td>559.0</td>\n",
+       "      <td>5.7192</td>\n",
+       "      <td>283500.0</td>\n",
+       "      <td>&lt;1H OCEAN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>16511</th>\n",
+       "      <td>-122.42</td>\n",
+       "      <td>37.77</td>\n",
+       "      <td>52.0</td>\n",
+       "      <td>4226.0</td>\n",
+       "      <td>1315.0</td>\n",
+       "      <td>2619.0</td>\n",
+       "      <td>1242.0</td>\n",
+       "      <td>2.5755</td>\n",
+       "      <td>325000.0</td>\n",
+       "      <td>NEAR BAY</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "       longitude  latitude  housing_median_age  total_rooms  total_bedrooms  \\\n",
+       "16507    -117.96     33.78                35.0       1330.0           201.0   \n",
+       "16508    -117.43     34.02                33.0       3084.0           570.0   \n",
+       "16509    -118.38     34.03                36.0       2101.0           569.0   \n",
+       "16510    -121.96     37.58                15.0       3575.0           597.0   \n",
+       "16511    -122.42     37.77                52.0       4226.0          1315.0   \n",
+       "\n",
+       "       population  households  median_income  median_house_value  \\\n",
+       "16507       658.0       217.0         6.3700            229200.0   \n",
+       "16508      1753.0       449.0         3.0500             97800.0   \n",
+       "16509      1756.0       527.0         2.9344            222100.0   \n",
+       "16510      1777.0       559.0         5.7192            283500.0   \n",
+       "16511      2619.0      1242.0         2.5755            325000.0   \n",
+       "\n",
+       "      ocean_proximity  \n",
+       "16507       <1H OCEAN  \n",
+       "16508          INLAND  \n",
+       "16509       <1H OCEAN  \n",
+       "16510       <1H OCEAN  \n",
+       "16511        NEAR BAY  "
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "train_set.tail()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### 特征数据的分布情况"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<1H OCEAN     7341\n",
+       "INLAND        5227\n",
+       "NEAR OCEAN    2086\n",
+       "NEAR BAY      1854\n",
+       "ISLAND           4\n",
+       "Name: ocean_proximity, dtype: int64"
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "train_set[\"ocean_proximity\"].value_counts()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### 数据集的快速统计分析"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "<class 'pandas.core.frame.DataFrame'>\n",
+      "RangeIndex: 16512 entries, 0 to 16511\n",
+      "Data columns (total 10 columns):\n",
+      "longitude             16512 non-null float64\n",
+      "latitude              16512 non-null float64\n",
+      "housing_median_age    16512 non-null float64\n",
+      "total_rooms           16512 non-null float64\n",
+      "total_bedrooms        16512 non-null float64\n",
+      "population            16512 non-null float64\n",
+      "households            16512 non-null float64\n",
+      "median_income         16512 non-null float64\n",
+      "median_house_value    16512 non-null float64\n",
+      "ocean_proximity       16512 non-null object\n",
+      "dtypes: float64(9), object(1)\n",
+      "memory usage: 1.3+ MB\n"
+     ]
+    }
+   ],
+   "source": [
+    "train_set.info()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [
+    {
+     "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>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>count</th>\n",
+       "      <td>16512.000000</td>\n",
+       "      <td>16512.000000</td>\n",
+       "      <td>16512.000000</td>\n",
+       "      <td>16512.000000</td>\n",
+       "      <td>16512.000000</td>\n",
+       "      <td>16512.000000</td>\n",
+       "      <td>16512.000000</td>\n",
+       "      <td>16512.000000</td>\n",
+       "      <td>16512.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>mean</th>\n",
+       "      <td>-119.582290</td>\n",
+       "      <td>35.643149</td>\n",
+       "      <td>28.608285</td>\n",
+       "      <td>2642.004784</td>\n",
+       "      <td>538.496851</td>\n",
+       "      <td>1426.453004</td>\n",
+       "      <td>499.986919</td>\n",
+       "      <td>3.880754</td>\n",
+       "      <td>207194.693738</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>std</th>\n",
+       "      <td>2.005654</td>\n",
+       "      <td>2.136665</td>\n",
+       "      <td>12.602499</td>\n",
+       "      <td>2174.646744</td>\n",
+       "      <td>419.007096</td>\n",
+       "      <td>1137.056380</td>\n",
+       "      <td>380.967964</td>\n",
+       "      <td>1.904294</td>\n",
+       "      <td>115622.626448</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>min</th>\n",
+       "      <td>-124.350000</td>\n",
+       "      <td>32.550000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>2.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>3.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.499900</td>\n",
+       "      <td>14999.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>25%</th>\n",
+       "      <td>-121.810000</td>\n",
+       "      <td>33.930000</td>\n",
+       "      <td>18.000000</td>\n",
+       "      <td>1454.000000</td>\n",
+       "      <td>296.750000</td>\n",
+       "      <td>789.000000</td>\n",
+       "      <td>280.000000</td>\n",
+       "      <td>2.566700</td>\n",
+       "      <td>119800.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>50%</th>\n",
+       "      <td>-118.510000</td>\n",
+       "      <td>34.260000</td>\n",
+       "      <td>29.000000</td>\n",
+       "      <td>2129.000000</td>\n",
+       "      <td>437.000000</td>\n",
+       "      <td>1167.000000</td>\n",
+       "      <td>410.000000</td>\n",
+       "      <td>3.545800</td>\n",
+       "      <td>179850.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>75%</th>\n",
+       "      <td>-118.010000</td>\n",
+       "      <td>37.720000</td>\n",
+       "      <td>37.000000</td>\n",
+       "      <td>3160.000000</td>\n",
+       "      <td>647.000000</td>\n",
+       "      <td>1726.000000</td>\n",
+       "      <td>606.000000</td>\n",
+       "      <td>4.773175</td>\n",
+       "      <td>265125.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>max</th>\n",
+       "      <td>-114.310000</td>\n",
+       "      <td>41.950000</td>\n",
+       "      <td>52.000000</td>\n",
+       "      <td>39320.000000</td>\n",
+       "      <td>6445.000000</td>\n",
+       "      <td>35682.000000</td>\n",
+       "      <td>6082.000000</td>\n",
+       "      <td>15.000100</td>\n",
+       "      <td>500001.000000</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "          longitude      latitude  housing_median_age   total_rooms  \\\n",
+       "count  16512.000000  16512.000000        16512.000000  16512.000000   \n",
+       "mean    -119.582290     35.643149           28.608285   2642.004784   \n",
+       "std        2.005654      2.136665           12.602499   2174.646744   \n",
+       "min     -124.350000     32.550000            1.000000      2.000000   \n",
+       "25%     -121.810000     33.930000           18.000000   1454.000000   \n",
+       "50%     -118.510000     34.260000           29.000000   2129.000000   \n",
+       "75%     -118.010000     37.720000           37.000000   3160.000000   \n",
+       "max     -114.310000     41.950000           52.000000  39320.000000   \n",
+       "\n",
+       "       total_bedrooms    population    households  median_income  \\\n",
+       "count    16512.000000  16512.000000  16512.000000   16512.000000   \n",
+       "mean       538.496851   1426.453004    499.986919       3.880754   \n",
+       "std        419.007096   1137.056380    380.967964       1.904294   \n",
+       "min          1.000000      3.000000      1.000000       0.499900   \n",
+       "25%        296.750000    789.000000    280.000000       2.566700   \n",
+       "50%        437.000000   1167.000000    410.000000       3.545800   \n",
+       "75%        647.000000   1726.000000    606.000000       4.773175   \n",
+       "max       6445.000000  35682.000000   6082.000000      15.000100   \n",
+       "\n",
+       "       median_house_value  \n",
+       "count        16512.000000  \n",
+       "mean        207194.693738  \n",
+       "std         115622.626448  \n",
+       "min          14999.000000  \n",
+       "25%         119800.000000  \n",
+       "50%         179850.000000  \n",
+       "75%         265125.000000  \n",
+       "max         500001.000000  "
+      ]
+     },
+     "execution_count": 11,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "train_set.describe()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "longitude             0\n",
+       "latitude              0\n",
+       "housing_median_age    0\n",
+       "total_rooms           0\n",
+       "total_bedrooms        0\n",
+       "population            0\n",
+       "households            0\n",
+       "median_income         0\n",
+       "median_house_value    0\n",
+       "ocean_proximity       0\n",
+       "dtype: int64"
+      ]
+     },
+     "execution_count": 12,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "train_set.isnull().sum()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [
+    {
+     "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>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",
+       "    <tr>\n",
+       "      <th>ocean_proximity</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>&lt;1H OCEAN</th>\n",
+       "      <td>7341</td>\n",
+       "      <td>7341</td>\n",
+       "      <td>7341</td>\n",
+       "      <td>7341</td>\n",
+       "      <td>7341</td>\n",
+       "      <td>7341</td>\n",
+       "      <td>7341</td>\n",
+       "      <td>7341</td>\n",
+       "      <td>7341</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>INLAND</th>\n",
+       "      <td>5227</td>\n",
+       "      <td>5227</td>\n",
+       "      <td>5227</td>\n",
+       "      <td>5227</td>\n",
+       "      <td>5227</td>\n",
+       "      <td>5227</td>\n",
+       "      <td>5227</td>\n",
+       "      <td>5227</td>\n",
+       "      <td>5227</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>ISLAND</th>\n",
+       "      <td>4</td>\n",
+       "      <td>4</td>\n",
+       "      <td>4</td>\n",
+       "      <td>4</td>\n",
+       "      <td>4</td>\n",
+       "      <td>4</td>\n",
+       "      <td>4</td>\n",
+       "      <td>4</td>\n",
+       "      <td>4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>NEAR BAY</th>\n",
+       "      <td>1854</td>\n",
+       "      <td>1854</td>\n",
+       "      <td>1854</td>\n",
+       "      <td>1854</td>\n",
+       "      <td>1854</td>\n",
+       "      <td>1854</td>\n",
+       "      <td>1854</td>\n",
+       "      <td>1854</td>\n",
+       "      <td>1854</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>NEAR OCEAN</th>\n",
+       "      <td>2086</td>\n",
+       "      <td>2086</td>\n",
+       "      <td>2086</td>\n",
+       "      <td>2086</td>\n",
+       "      <td>2086</td>\n",
+       "      <td>2086</td>\n",
+       "      <td>2086</td>\n",
+       "      <td>2086</td>\n",
+       "      <td>2086</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                 longitude  latitude  housing_median_age  total_rooms  \\\n",
+       "ocean_proximity                                                         \n",
+       "<1H OCEAN             7341      7341                7341         7341   \n",
+       "INLAND                5227      5227                5227         5227   \n",
+       "ISLAND                   4         4                   4            4   \n",
+       "NEAR BAY              1854      1854                1854         1854   \n",
+       "NEAR OCEAN            2086      2086                2086         2086   \n",
+       "\n",
+       "                 total_bedrooms  population  households  median_income  \\\n",
+       "ocean_proximity                                                          \n",
+       "<1H OCEAN                  7341        7341        7341           7341   \n",
+       "INLAND                     5227        5227        5227           5227   \n",
+       "ISLAND                        4           4           4              4   \n",
+       "NEAR BAY                   1854        1854        1854           1854   \n",
+       "NEAR OCEAN                 2086        2086        2086           2086   \n",
+       "\n",
+       "                 median_house_value  \n",
+       "ocean_proximity                      \n",
+       "<1H OCEAN                      7341  \n",
+       "INLAND                         5227  \n",
+       "ISLAND                            4  \n",
+       "NEAR BAY                       1854  \n",
+       "NEAR OCEAN                     2086  "
+      ]
+     },
+     "execution_count": 13,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "train_set.groupby('ocean_proximity').count()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### 可视化数据进行分析"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "每个列的数据直方图"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([[<matplotlib.axes._subplots.AxesSubplot object at 0x000001688C4F07F0>,\n",
+       "        <matplotlib.axes._subplots.AxesSubplot object at 0x000001688C558A20>,\n",
+       "        <matplotlib.axes._subplots.AxesSubplot object at 0x000001688C580EF0>],\n",
+       "       [<matplotlib.axes._subplots.AxesSubplot object at 0x000001688C5AD438>,\n",
+       "        <matplotlib.axes._subplots.AxesSubplot object at 0x000001688C5D38D0>,\n",
+       "        <matplotlib.axes._subplots.AxesSubplot object at 0x000001688C5FCDD8>],\n",
+       "       [<matplotlib.axes._subplots.AxesSubplot object at 0x000001688C62D320>,\n",
+       "        <matplotlib.axes._subplots.AxesSubplot object at 0x000001688C651860>,\n",
+       "        <matplotlib.axes._subplots.AxesSubplot object at 0x000001688C651898>]],\n",
+       "      dtype=object)"
+      ]
+     },
+     "execution_count": 14,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1440x1080 with 9 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "train_set.hist(bins=50,figsize=(20,15))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "按地理位置的人口分布散点图"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.legend.Legend at 0x1688c96a240>"
+      ]
+     },
+     "execution_count": 15,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 2 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "train_set.plot(kind='scatter',x='longitude', y='latitude', alpha=0.4, s=train_set['population']/100,label='population', c='median_house_value',cmap=plt.get_cmap(\"jet\"),colorbar=True)\n",
+    "plt.legend()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### 研究样本属性之间的关系"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {},
+   "outputs": [
+    {
+     "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>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>longitude</th>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>-0.924485</td>\n",
+       "      <td>-0.101818</td>\n",
+       "      <td>0.038676</td>\n",
+       "      <td>0.063064</td>\n",
+       "      <td>0.094276</td>\n",
+       "      <td>0.049306</td>\n",
+       "      <td>-0.017040</td>\n",
+       "      <td>-0.046349</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>latitude</th>\n",
+       "      <td>-0.924485</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.005296</td>\n",
+       "      <td>-0.029224</td>\n",
+       "      <td>-0.059998</td>\n",
+       "      <td>-0.102499</td>\n",
+       "      <td>-0.064061</td>\n",
+       "      <td>-0.076571</td>\n",
+       "      <td>-0.142983</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>housing_median_age</th>\n",
+       "      <td>-0.101818</td>\n",
+       "      <td>0.005296</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>-0.360922</td>\n",
+       "      <td>-0.320624</td>\n",
+       "      <td>-0.292283</td>\n",
+       "      <td>-0.302796</td>\n",
+       "      <td>-0.121711</td>\n",
+       "      <td>0.103706</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>total_rooms</th>\n",
+       "      <td>0.038676</td>\n",
+       "      <td>-0.029224</td>\n",
+       "      <td>-0.360922</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.930489</td>\n",
+       "      <td>0.857936</td>\n",
+       "      <td>0.920482</td>\n",
+       "      <td>0.198268</td>\n",
+       "      <td>0.133989</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>total_bedrooms</th>\n",
+       "      <td>0.063064</td>\n",
+       "      <td>-0.059998</td>\n",
+       "      <td>-0.320624</td>\n",
+       "      <td>0.930489</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.878932</td>\n",
+       "      <td>0.980255</td>\n",
+       "      <td>-0.009141</td>\n",
+       "      <td>0.047980</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>population</th>\n",
+       "      <td>0.094276</td>\n",
+       "      <td>-0.102499</td>\n",
+       "      <td>-0.292283</td>\n",
+       "      <td>0.857936</td>\n",
+       "      <td>0.878932</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.907452</td>\n",
+       "      <td>0.004122</td>\n",
+       "      <td>-0.026032</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>households</th>\n",
+       "      <td>0.049306</td>\n",
+       "      <td>-0.064061</td>\n",
+       "      <td>-0.302796</td>\n",
+       "      <td>0.920482</td>\n",
+       "      <td>0.980255</td>\n",
+       "      <td>0.907452</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.012776</td>\n",
+       "      <td>0.063714</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>median_income</th>\n",
+       "      <td>-0.017040</td>\n",
+       "      <td>-0.076571</td>\n",
+       "      <td>-0.121711</td>\n",
+       "      <td>0.198268</td>\n",
+       "      <td>-0.009141</td>\n",
+       "      <td>0.004122</td>\n",
+       "      <td>0.012776</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.690647</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>median_house_value</th>\n",
+       "      <td>-0.046349</td>\n",
+       "      <td>-0.142983</td>\n",
+       "      <td>0.103706</td>\n",
+       "      <td>0.133989</td>\n",
+       "      <td>0.047980</td>\n",
+       "      <td>-0.026032</td>\n",
+       "      <td>0.063714</td>\n",
+       "      <td>0.690647</td>\n",
+       "      <td>1.000000</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                    longitude  latitude  housing_median_age  total_rooms  \\\n",
+       "longitude            1.000000 -0.924485           -0.101818     0.038676   \n",
+       "latitude            -0.924485  1.000000            0.005296    -0.029224   \n",
+       "housing_median_age  -0.101818  0.005296            1.000000    -0.360922   \n",
+       "total_rooms          0.038676 -0.029224           -0.360922     1.000000   \n",
+       "total_bedrooms       0.063064 -0.059998           -0.320624     0.930489   \n",
+       "population           0.094276 -0.102499           -0.292283     0.857936   \n",
+       "households           0.049306 -0.064061           -0.302796     0.920482   \n",
+       "median_income       -0.017040 -0.076571           -0.121711     0.198268   \n",
+       "median_house_value  -0.046349 -0.142983            0.103706     0.133989   \n",
+       "\n",
+       "                    total_bedrooms  population  households  median_income  \\\n",
+       "longitude                 0.063064    0.094276    0.049306      -0.017040   \n",
+       "latitude                 -0.059998   -0.102499   -0.064061      -0.076571   \n",
+       "housing_median_age       -0.320624   -0.292283   -0.302796      -0.121711   \n",
+       "total_rooms               0.930489    0.857936    0.920482       0.198268   \n",
+       "total_bedrooms            1.000000    0.878932    0.980255      -0.009141   \n",
+       "population                0.878932    1.000000    0.907452       0.004122   \n",
+       "households                0.980255    0.907452    1.000000       0.012776   \n",
+       "median_income            -0.009141    0.004122    0.012776       1.000000   \n",
+       "median_house_value        0.047980   -0.026032    0.063714       0.690647   \n",
+       "\n",
+       "                    median_house_value  \n",
+       "longitude                    -0.046349  \n",
+       "latitude                     -0.142983  \n",
+       "housing_median_age            0.103706  \n",
+       "total_rooms                   0.133989  \n",
+       "total_bedrooms                0.047980  \n",
+       "population                   -0.026032  \n",
+       "households                    0.063714  \n",
+       "median_income                 0.690647  \n",
+       "median_house_value            1.000000  "
+      ]
+     },
+     "execution_count": 16,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "corr_matrix = train_set.corr()\n",
+    "corr_matrix"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "median_house_value    1.000000\n",
+       "median_income         0.690647\n",
+       "total_rooms           0.133989\n",
+       "housing_median_age    0.103706\n",
+       "households            0.063714\n",
+       "total_bedrooms        0.047980\n",
+       "population           -0.026032\n",
+       "longitude            -0.046349\n",
+       "latitude             -0.142983\n",
+       "Name: median_house_value, dtype: float64"
+      ]
+     },
+     "execution_count": 17,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "corr_matrix[\"median_house_value\"].sort_values(ascending=False)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "D:\\Edwin_Git\\我的博客\\MyGitHub\\Python\\.venv\\lib\\site-packages\\ipykernel_launcher.py:3: FutureWarning: 'pandas.tools.plotting.scatter_matrix' is deprecated, import 'pandas.plotting.scatter_matrix' instead.\n",
+      "  This is separate from the ipykernel package so we can avoid doing imports until\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "array([[<matplotlib.axes._subplots.AxesSubplot object at 0x000001688CC27CF8>,\n",
+       "        <matplotlib.axes._subplots.AxesSubplot object at 0x000001688CC5DF98>,\n",
+       "        <matplotlib.axes._subplots.AxesSubplot object at 0x000001688CC8B2E8>,\n",
+       "        <matplotlib.axes._subplots.AxesSubplot object at 0x000001688CCAF7F0>],\n",
+       "       [<matplotlib.axes._subplots.AxesSubplot object at 0x000001688CCD5CC0>,\n",
+       "        <matplotlib.axes._subplots.AxesSubplot object at 0x000001688CFA7208>,\n",
+       "        <matplotlib.axes._subplots.AxesSubplot object at 0x000001688CFCB710>,\n",
+       "        <matplotlib.axes._subplots.AxesSubplot object at 0x000001688CFF4C50>],\n",
+       "       [<matplotlib.axes._subplots.AxesSubplot object at 0x000001688CFF4C88>,\n",
+       "        <matplotlib.axes._subplots.AxesSubplot object at 0x000001688D04E668>,\n",
+       "        <matplotlib.axes._subplots.AxesSubplot object at 0x000001688D074B70>,\n",
+       "        <matplotlib.axes._subplots.AxesSubplot object at 0x000001688D0A40B8>],\n",
+       "       [<matplotlib.axes._subplots.AxesSubplot object at 0x000001688D0CB5C0>,\n",
+       "        <matplotlib.axes._subplots.AxesSubplot object at 0x000001688D0F5AC8>,\n",
+       "        <matplotlib.axes._subplots.AxesSubplot object at 0x000001688D11CFD0>,\n",
+       "        <matplotlib.axes._subplots.AxesSubplot object at 0x000001688D14F518>]],\n",
+       "      dtype=object)"
+      ]
+     },
+     "execution_count": 18,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 864x576 with 16 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "from pandas.tools.plotting import scatter_matrix\n",
+    "attributes = [\"median_house_value\",\"median_income\",\"total_rooms\",\"housing_median_age\"]\n",
+    "scatter_matrix(train_set[attributes],figsize=(12,8))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "env_python367",
+   "language": "python",
+   "name": ".venv"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.6.7"
+  },
+  "toc": {
+   "base_numbering": 1,
+   "nav_menu": {},
+   "number_sections": true,
+   "sideBar": true,
+   "skip_h1_title": false,
+   "title_cell": "Table of Contents",
+   "title_sidebar": "Contents",
+   "toc_cell": false,
+   "toc_position": {},
+   "toc_section_display": true,
+   "toc_window_display": true
+  },
+  "varInspector": {
+   "cols": {
+    "lenName": 16,
+    "lenType": 16,
+    "lenVar": 40
+   },
+   "kernels_config": {
+    "python": {
+     "delete_cmd_postfix": "",
+     "delete_cmd_prefix": "del ",
+     "library": "var_list.py",
+     "varRefreshCmd": "print(var_dic_list())"
+    },
+    "r": {
+     "delete_cmd_postfix": ") ",
+     "delete_cmd_prefix": "rm(",
+     "library": "var_list.r",
+     "varRefreshCmd": "cat(var_dic_list()) "
+    }
+   },
+   "types_to_exclude": [
+    "module",
+    "function",
+    "builtin_function_or_method",
+    "instance",
+    "_Feature"
+   ],
+   "window_display": false
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/California Housing Prices/datasets/housing.csv b/california_housing_prices/datasets/housing.csv
similarity index 100%
rename from California Housing Prices/datasets/housing.csv
rename to california_housing_prices/datasets/housing.csv
diff --git a/California Housing Prices/datasets/housing.tgz b/california_housing_prices/datasets/housing.tgz
similarity index 100%
rename from California Housing Prices/datasets/housing.tgz
rename to california_housing_prices/datasets/housing.tgz
diff --git a/California Housing Prices/datasets/test_set.csv b/california_housing_prices/datasets/test_set.csv
similarity index 100%
rename from California Housing Prices/datasets/test_set.csv
rename to california_housing_prices/datasets/test_set.csv
diff --git a/California Housing Prices/datasets/train_set.csv b/california_housing_prices/datasets/train_set.csv
similarity index 100%
rename from California Housing Prices/datasets/train_set.csv
rename to california_housing_prices/datasets/train_set.csv
diff --git a/california_housing_prices/datasource/housing/housing.tgz b/california_housing_prices/datasource/housing/housing.tgz
new file mode 100644
index 0000000..9f3a4a1
Binary files /dev/null and b/california_housing_prices/datasource/housing/housing.tgz differ
diff --git a/California Housing Prices/load_data.py b/california_housing_prices/load_data.py
similarity index 83%
rename from California Housing Prices/load_data.py
rename to california_housing_prices/load_data.py
index 8154c42..2c15ba5 100644
--- a/California Housing Prices/load_data.py	
+++ b/california_housing_prices/load_data.py
@@ -27,32 +27,32 @@ class FetchFileData:
     """
     说明: 用于下载指定url的具体文件内容
     """
-    def __init__(self, url, localpath=".", filename="", extractfile=True):
+    def __init__(self, url, local_path=".", filename="", extractfile=True):
         """
         输入值:
             url         : 完整的文件下载url, 含文件名, 本例只支持释放.tgz 文件，
                           根据项目需要，可调整代码，以便处理其他文件
-            localpath   : 文件下载以及释放后的文件存放的本地目录，可以是相对目录名,若为"" 或 ".", 则为当前目录
+            local_path   : 文件下载以及释放后的文件存放的本地目录，可以是相对目录名,若为"" 或 ".", 则为当前目录
             filename    : 本地保存的 .tgz 文件名，若为空，则为url中的文件名
-            extractfile : True : 执行释放文件的操作，目前只支持tgz ; False : 不执行释放文件的操作; 缺省为Fasle
+            extractfile : True : 执行释放文件的操作，目前只支持tgz ; False : 不执行释放文件的操作; 缺省为False
         """
         self.url = url
 
-        if localpath == "":
-            localpath = "."
-        self.localpath = localpath
+        if local_path == "":
+            local_path = "."
+        self.local_path = local_path
 
         if filename == "":
             filename = os.path.split(url)[1]
         self.filename = filename
 
-        self.extname = os.path.splitext(self.filename)[1]
+        self.ext_name = os.path.splitext(self.filename)[1]
 
         self.extractfile = extractfile
-        self.local_filename = os.path.join(self.localpath, self.filename)
+        self.local_filename = os.path.join(self.local_path, self.filename)
 
-    def schedule(self, blocknum, blocksize, totalsize):
-        per = 100.0 * blocknum * blocksize / totalsize
+    def schedule(self, block_num, block_size, total_size):
+        per = 100.0 * block_num * block_size / total_size
         if per > 100:
             per = 100
         myprint("Current download percentage : %.2f%%" % per)
@@ -61,8 +61,8 @@ def download_file_to_local(self):
         """
         单独使用，可实现下载指定文件内容
         """
-        if not os.path.exists(self.localpath):
-            os.makedirs(self.localpath)
+        if not os.path.exists(self.local_path):
+            os.makedirs(self.local_path)
         try:
             urllib.request.urlretrieve(self.url, self.local_filename, self.schedule)
             return True
@@ -75,9 +75,9 @@ def extract_tgz_file(self):
         单独使用，可实现释放指定的 .tgz 文件
         """
         if os.path.exists(self.local_filename):
-            tgzresult = tarfile.open(self.local_filename)
-            tgzresult.extractall(path=self.localpath)
-            tgzresult.close()
+            tgz_result = tarfile.open(self.local_filename)
+            tgz_result.extractall(path=self.local_path)
+            tgz_result.close()
         else:
             myprint(self.local_filename + " is not exists !")
 
@@ -90,7 +90,7 @@ def fetch_data(self):
             return None
 
         # 根据设置，释放 .tgz 文件
-        if self.extractfile and self.extname.lower() == ".tgz":
+        if self.extractfile and self.ext_name.lower() == ".tgz":
             self.extract_tgz_file()
 
         return self.local_filename
@@ -98,7 +98,7 @@ def fetch_data(self):
 
 class DataLoader:
     URL = "https://raw.githubusercontent.com/ageron/handson-ml/master/datasets/housing/housing.tgz"
-    LOCALPATH = "datasets"
+    DATASETS_DIR = "datasets"
     FILENAME_ALL_SET = "datasets\\housing.csv"
     FILENAME_TRAIN_SET = "datasets\\train_set.csv"
     FILENAME_TEST_SET = "datasets\\test_set.csv"
@@ -107,6 +107,11 @@ def __init__(self):
         self.train_set = None
         self.test_set = None
 
+    def download_training_data(self):
+        # 若训练数据不存在，则先下载训练数据
+        if not os.path.exists(self.FILENAME_ALL_SET):
+            FetchFileData(self.URL, self.DATASETS_DIR).fetch_data()
+
     def load_all_set(self):
         """
         说明:
@@ -115,8 +120,7 @@ def load_all_set(self):
         返回值:
             原始数据集: pandas.DataFrame
         """
-        if not os.path.exists(self.FILENAME_ALL_SET):
-            FetchFileData(self.URL, self.LOCALPATH).fetch_data()
+        self.download_training_data()
 
         # 有可能没有下载成功，因此打开文件前，仍需要再判断一次
         if os.path.exists(self.FILENAME_ALL_SET):
diff --git a/california_housing_prices/main.py b/california_housing_prices/main.py
new file mode 100644
index 0000000..98ba74b
--- /dev/null
+++ b/california_housing_prices/main.py
@@ -0,0 +1,196 @@
+# -*- coding:utf-8 -*-
+
+# ******************************************************************************
+# 模块说明 ：应用程序的主调用程序
+# 开发人员 ：Edwin.Zhang
+# 开发时间 : 2018-5-18
+# ******************************************************************************
+import warnings
+import os
+import subprocess
+import tkinter as tk
+import tkutils as tku
+import numpy as np
+from sklearn.linear_model import LinearRegression
+from sklearn.tree import DecisionTreeRegressor
+from sklearn.ensemble import RandomForestRegressor
+from load_data import DataLoader
+from prepare_data import PrepareData
+from train_model import TrainModel, GridSearchModel
+
+# 忽略一些警告信息
+warnings.filterwarnings("ignore", category=DeprecationWarning)
+warnings.filterwarnings("ignore", category=FutureWarning)
+
+# 通过当前文件的绝对路径，获得相关目录信息
+CURRENT_DIR = os.path.dirname(os.path.abspath(__file__))
+VENV_DIR = os.path.join(os.path.dirname(os.path.dirname(os.path.abspath(__file__))), ".venv", "Scripts")
+
+
+class App:
+    def __init__(self):
+        self.root = tk.Tk()
+        self.root.geometry("%dx%d" % (680, 100))   # 窗体尺寸
+        tku.center_window(self.root)               # 将窗体移动到屏幕中央
+        self.root.title("california_housing_prices Housing Process")
+        self.root.resizable(False, False)          # 设置窗体不可改变大小
+        self.no_title = True
+        self.but_download = None
+        self.but_prepare = None
+        self.but_train = None
+        self.but_predict = None
+        self.body()
+
+    def body(self):
+        self.but_download = tk.Button(self.root, text="下载训练数据", height=2, width=20)
+        self.but_download.pack(side=tk.LEFT, padx=10)
+        self.but_download.configure(command=do_download_data)
+
+        self.but_prepare = tk.Button(self.root, text="数据处理演示", height=2, width=20)
+        self.but_prepare.pack(side=tk.LEFT, padx=10)
+        self.but_prepare.configure(command=do_prepare_data)
+
+        self.but_train = tk.Button(self.root, text="训练模型", height=2, width=20)
+        self.but_train.pack(side=tk.LEFT, padx=10)
+        self.but_train.configure(command=do_training_model)
+
+        self.but_predict = tk.Button(self.root, text="模型预测", height=2, width=20)
+        self.but_predict.pack(side=tk.LEFT, padx=10)
+        self.but_predict.configure(command=do_predict)
+
+
+def myprint(message):
+    """
+    说明：一个小函数，为了缩减文件，使重点突出，没有加共用函数库，冗余了这段代码
+    """
+    import time
+    print(time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(time.time())) + " : " + message)
+
+
+def get_model_by_type(model_type):
+    """
+    说明：
+        获得模型实例
+    输入：
+        model_type:(string) - 模型类型
+    输出：
+        reg_model:(scikit-Learn model) - 输入的标识符必须能正确匹配，否则返回 None
+    """
+    models = {
+        "linear": LinearRegression(),
+        "decisiontree": DecisionTreeRegressor(),
+        "random_forest": RandomForestRegressor()
+    }
+
+    return models.get(model_type)
+
+
+def do_download_data():
+    """
+    下载训练数据
+    :return:
+    """
+    data_loader = DataLoader()
+    data_loader.download_training_data()
+
+    dir_name = data_loader.DATASETS_DIR
+    if os.path.exists(dir_name):
+        os.startfile(dir_name)
+
+
+def do_prepare_data():
+    """
+    打开Jupter notebook, 预处理数据的代码演示，非实际预处理代码
+    实际数据预处理，在模型训练时，会自动处理
+    :return:
+    """
+    note_book_path = os.path.join(CURRENT_DIR, "california_data_prepare.ipynb")
+    command_line = VENV_DIR + "\\" + "jupyter notebook " + note_book_path
+    subprocess.Popen(command_line, creationflags=subprocess.CREATE_NEW_CONSOLE)
+    tku.show_info("在Jupyter Notebook 界面中，请设置 Kernel 为 env_python367，以便让代码可正常执行！ ")
+
+
+def do_training_model():
+    """
+        执行数据的处理和模型的训练，需要反复调试，以获得最好的训练模型
+    """
+    myprint("Step 1： 获取并装载训练数据集")
+    data_loader = DataLoader()
+    train_set = data_loader.load_train_set()
+
+    myprint("step 2 : 清理训练数据")
+    preparer = PrepareData(train_set)
+    preparer.prepare_data()
+
+    train_prepared = preparer.train_prepared
+    train_label = preparer.train_label
+
+    myprint("step 3 : 开始训练各种模型，并记录各模型的性能评分")
+
+    myprint("step 3.1 : 使用默认参数训练线性模型 - LinearRegression")
+    trainer = TrainModel("lin_model_1", get_model_by_type("linear"), train_prepared, train_label)
+    trainer.train_model()
+
+    myprint("step 3.2 : 使用默认参数训练决策树模型 - DecisionTreeRegressor")
+    trainer = TrainModel("decision_model_1", get_model_by_type("decisiontree"), train_prepared, train_label)
+    trainer.train_model()
+
+    myprint("step 3.3 : 使用默认参数训练随机森林模型 - RandomForestRegressor")
+    trainer = TrainModel("random_model_1", get_model_by_type("random_forest"), train_prepared, train_label)
+    trainer.train_model()
+
+    myprint("step 3.4 : 使用自定义参数训练随机森林线性模型 - RandomForestRegressor")
+    reg_model = RandomForestRegressor(n_estimators=10, max_features=4, bootstrap=False)
+    trainer = TrainModel("random_model_s1", reg_model, train_prepared, train_label)
+    trainer.train_model()
+
+    myprint("step 3.5 : 利用GridSearchCV，使用多组网格参数，批量训练随机森林模型")
+    param_grid = [
+        {'n_estimators': [3, 10, 30], 'max_features':[2, 4, 6, 8]},
+        {'bootstrap': [False], 'n_estimators':[3, 10], 'max_features':[2, 3, 4]}
+    ]
+    trainer = GridSearchModel("random_grid_1",
+                              get_model_by_type("random_forest"),
+                              param_grid,
+                              train_prepared,
+                              train_label)
+    trainer.train_model()  # 若传入参数 True, 将显示所有参数组合的性能评分
+
+    myprint("")
+    myprint("模型训练已完成， 模型文件保存在子目录【trainmodels】中！可用于预测使用")
+    myprint("")
+
+
+def do_predict():
+    """
+    利用训练好的模型，进行价格预测分析
+    """
+    myprint("step 1 : 获取并装载测试数据或待预测的数据")
+    data_loader = DataLoader()
+    test_set = data_loader.load_test_set()
+
+    # 有一个问题要解决：若测试文本字段的分类数量跟训练集不一致，则会造成特征列个数不同的情况，需要考虑如何处理
+    # 在大数据情况下没有关系，若只取几十条，或单条进行预测，会引起报错（待解决）
+
+    # step 2 : 清理数据
+    myprint("step 2 : 清理数据（采用跟清理训练数据相同的处理方式）")
+    preparer = PrepareData(test_set)
+    preparer.prepare_data()
+
+    test_prepared = preparer.train_prepared
+    test_label = preparer.train_label
+
+    myprint("step 3 : 用指定的训练模型进行预测计算")
+    best_model_name = 'random_grid_1'
+    trainer = TrainModel(best_model_name)
+    test_pred, test_rmse_score = trainer.predict(test_prepared, test_label)
+    myprint("")
+
+    myprint("step 4 : 显示预测结果值，供后续使用 ")
+    print(np.c_[test_label[:20], test_pred[:20]])
+    print(np.c_[test_prepared[:5], test_label[:5], test_pred[:5]])
+
+
+if __name__ == "__main__":
+    app = App()
+    app.root.mainloop()
diff --git a/California Housing Prices/prepare_data.py b/california_housing_prices/prepare_data.py
similarity index 99%
rename from California Housing Prices/prepare_data.py
rename to california_housing_prices/prepare_data.py
index 680e138..b5c735e 100644
--- a/California Housing Prices/prepare_data.py	
+++ b/california_housing_prices/prepare_data.py
@@ -28,7 +28,7 @@ class DataFrameSelector(BaseEstimator, TransformerMixin):
     """
         说明：
             这是一个自定义的转换器，用于将 DataFrame 中的指定列的数据取出，
-            返回 np.ndarry 数据后，往下继续进行处理
+            返回 np.ndarray 数据后，往下继续进行处理
     """
     def __init__(self, attribute_names):
         self.attribute_names = attribute_names
diff --git a/california_housing_prices/run.bat b/california_housing_prices/run.bat
new file mode 100644
index 0000000..ce5f798
--- /dev/null
+++ b/california_housing_prices/run.bat
@@ -0,0 +1 @@
+..\.venv\scripts\python.exe main.py
diff --git a/tkinter-pack Demo/tkutils.py b/california_housing_prices/tkutils.py
similarity index 100%
rename from tkinter-pack Demo/tkutils.py
rename to california_housing_prices/tkutils.py
diff --git a/California Housing Prices/train_model.py b/california_housing_prices/train_model.py
similarity index 70%
rename from California Housing Prices/train_model.py
rename to california_housing_prices/train_model.py
index fb96576..54bdae9 100644
--- a/California Housing Prices/train_model.py	
+++ b/california_housing_prices/train_model.py
@@ -9,8 +9,12 @@
 # 开发时间 : 2018-5-18
 # ******************************************************************************
 
-import numpy as np
 import os
+import numpy as np
+from sklearn.externals import joblib
+from sklearn.model_selection import cross_val_score
+from sklearn.metrics import mean_squared_error
+from sklearn.model_selection import GridSearchCV
 
 
 def myprint(message):
@@ -27,19 +31,19 @@ class TrainModel:
         1. 根据输入的训练数据集，训练模型，保存模型，显示性能评分
         2. 利用已经训练好的模型，进行预测
     """
-    def __init__(self, modelname, model=None, train_prepared=None, train_label=None):
+    def __init__(self, model_name, model=None, train_prepared=None, train_label=None):
         """
         输入：
-            modelname:(string) - 模型的名称，用于模型保存的文件名标识
+            model_name:(string) - 模型的名称，用于模型保存的文件名标识
             model:(sklearn.regressor) - scikit-Learn的一种回归模型
             train_prepared:(numpy.ndarray) - 训练数据的特征集
             train_label   :(numpy.ndarray or pandas.Series) - 训练数据的标签集
         """
         self.model = model
-        if modelname == "":
-            modelname = "default_model"
-        self.modelname = modelname
-        self.modelfilename = "trainmodels\\" + self.modelname + ".pkl"
+        if model_name == "":
+            model_name = "default_model"
+        self.model_name = model_name
+        self.model_filename = "trainmodels\\" + self.model_name + ".pkl"
 
         self.train_prepared = train_prepared
         self.train_label = train_label
@@ -52,26 +56,22 @@ def train_model(self):
         说明：
             利用交叉训练的方法，训练并测试模型，获得性能评分，保存训练模型
         """
-        from sklearn.model_selection import cross_val_score
-
         self.model.fit(self.train_prepared, self.train_label)
         self.mse_score = cross_val_score(self.model, self.train_prepared, self.train_label,
                                          scoring="neg_mean_squared_error", cv=10)
         self.rmse_score = np.sqrt(-self.mse_score)
         self.save_model()
-        myprint("%20s : Mean RMSE Score = %f " % (self.modelname, self.rmse_score.mean()))
+        myprint("%20s : Mean RMSE Score = %f " % (self.model_name, self.rmse_score.mean()))
 
     def save_model(self):
-        from sklearn.externals import joblib
-        if self.modelname != "":
+        if self.model_name != "":
             if not os.path.exists("trainmodels"):
                 os.makedirs("trainmodels")
-            joblib.dump(self.model, self.modelfilename)
+            joblib.dump(self.model, self.model_filename)
 
     def load_model(self):
-        from sklearn.externals import joblib
-        if self.modelname != "" and os.path.exists(self.modelfilename):
-            self.model = joblib.load(self.modelfilename)
+        if self.model_name != "" and os.path.exists(self.model_filename):
+            self.model = joblib.load(self.model_filename)
 
     def predict(self, test_prepared, test_label=None):
         """
@@ -84,8 +84,6 @@ def predict(self, test_prepared, test_label=None):
             test_prediction:(numpy.ndarray) - 预测标签结果值
             test_rmse_score:(float)         - 预测性能评分值
         """
-        from sklearn.metrics import mean_squared_error
-
         # 获得训练好的模型
         if self.model is None:
             self.load_model()
@@ -100,27 +98,30 @@ def predict(self, test_prepared, test_label=None):
         if test_pred is not None and test_label is not None:
             test_mse_score = mean_squared_error(test_label, test_pred)
             test_rmse_score = np.sqrt(test_mse_score)  # 注意，这里是正数，看传入的变量前后顺序
-            myprint("%20s : Mean RMSE Score = %f " % (self.modelname, test_rmse_score))
+            myprint("%20s : Mean RMSE Score = %f " % (self.model_name, test_rmse_score))
 
         return test_pred, test_rmse_score
 
 
 class GridSearchModel:
-    def __init__(self, modelname, model, param_grid, train_prepared, train_label):
+    def __init__(self, model_name, model, param_grid, train_prepared, train_label):
         """
         输入:
-            modelname:(string) - 模型的名称，用于模型保存的文件名标识
-            model:(sklearn.regreesor) - scikit-Learn的一种回归模型
+            model_name:(string) - 模型的名称，用于模型保存的文件名标识
+            model:(sklearn.regressor) - scikit-Learn的一种回归模型
             param_grid:(list) - 参数组合列表
             train_prepared:(numpy.ndarray) - 训练数据特征集
             train_label   :(numpy.ndarray) - 训练数据标签集
         """
         self.model = model
         self.param_grid = param_grid
-        if modelname == "":
-            modelname = "gridsearch_model"
-        self.modelname = modelname
-        self.modelfilename = "trainmodels\\" + self.modelname + ".pkl"
+        if model_name == "":
+            model_name = "gridsearch_model"
+        self.model_name = model_name
+        self.model_filename = "trainmodels\\" + self.model_name + ".pkl"
+
+        if not os.path.exists("trainmodels"):
+            os.makedirs("trainmodels")
 
         self.train_prepared = train_prepared
         self.train_label = train_label
@@ -130,17 +131,15 @@ def __init__(self, modelname, model, param_grid, train_prepared, train_label):
         self.mse_score = None
         self.rmse_score = None
 
-    def train_model(self, showdetail=False):
+    def train_model(self, show_detail=False):
         """
         说明:
             训练模型
         输入：
-            showdetail:(bool) - True : 显示每个参数组合的训练结果；缺省为 False, 不显示
+            show_detail:(bool) - True : 显示每个参数组合的训练结果；缺省为 False, 不显示
         输出:
             无具体返回值，当会显示训练结果，并保存最佳训练器到模型同名文件
         """
-        from sklearn.model_selection import GridSearchCV
-
         # 执行训练
         grid_search = GridSearchCV(self.model, self.param_grid, cv=5, scoring='neg_mean_squared_error')
         grid_search.fit(self.train_prepared, self.train_label)
@@ -151,17 +150,14 @@ def train_model(self, showdetail=False):
         self.mse_score = grid_search.best_score_
         self.rmse_score = np.sqrt(-self.mse_score)
         self.save_model()
-        myprint("%20s : Mean RMSE Score = %f  : Best Params = %s " % (self.modelname, self.rmse_score.mean(),
+        myprint("%20s : Mean RMSE Score = %f  : Best Params = %s " % (self.model_name, self.rmse_score.mean(),
                                                                       str(self.best_params)))
 
-        if showdetail:
-            cvres = grid_search.cv_results_
-            for mean_score, params in zip(cvres["mean_test_score"], cvres["params"]):
+        if show_detail:
+            cv_res = grid_search.cv_results_
+            for mean_score, params in zip(cv_res["mean_test_score"], cv_res["params"]):
                 myprint(np.sqrt(-mean_score), params)
 
     def save_model(self):
-        from sklearn.externals import joblib
-        if self.modelname != "":
-            if not os.path.exists("trainmodels"):
-                os.makedirs("trainmodels")
-            joblib.dump(self.best_model, self.modelfilename)
+        if self.model_name != "":
+            joblib.dump(self.best_model, self.model_filename)
diff --git a/requirements.txt b/requirements.txt
new file mode 100644
index 0000000..90992e4
--- /dev/null
+++ b/requirements.txt
@@ -0,0 +1,9 @@
+pygame==1.9.4
+pillow==5.3.0
+keras==2.1.2
+tensorflow==1.12.0
+matplotlib==3.0.1
+pandas==0.23.4
+scikit-learn==0.20.1
+scipy==1.1.0
+opencv-python==3.4.1.15
diff --git a/setup.bat b/setup.bat
new file mode 100644
index 0000000..040e474
--- /dev/null
+++ b/setup.bat
@@ -0,0 +1,23 @@
+@ECHO OFF
+
+REM 设置 64位 python 3.6.7 的 python.exe 的全称文件名
+if not defined PYTHON (set PYTHON="C:\Users\Edwin\AppData\Local\Programs\Python\Python36\python.exe")
+
+REM 创建虚拟环境, 目录名为 .venv
+%PYTHON% -m venv .venv
+
+REM  更新升级 pip
+.venv\scripts\python.exe -m pip install --upgrade pip
+
+REM 根据 requirements.txt , 从国内镜像网站安装依赖模块。（分开写，是由于涉及模块的编译依赖）
+.venv\scripts\pip install -r requirements.txt -i https://pypi.tuna.tsinghua.edu.cn/simple
+
+.venv\scripts\pip install maturin==0.12.20 -i https://pypi.tuna.tsinghua.edu.cn/simple
+
+.venv\scripts\pip install notebook==6.4.10 -i https://pypi.tuna.tsinghua.edu.cn/simple
+
+.venv\scripts\python.exe -m ipykernel install --user --name .venv --display-name "env_python367"
+
+REM 创建激活虚拟环境的批处理文件 activate.bat
+echo chcp 65001 > activate.bat
+echo %~dp0.venv\scripts\activate >> activate.bat
\ No newline at end of file
diff --git a/tkinter-pack Demo/.idea/inspectionProfiles/profiles_settings.xml b/tkinter-pack Demo/.idea/inspectionProfiles/profiles_settings.xml
deleted file mode 100644
index 0eefe32..0000000
--- a/tkinter-pack Demo/.idea/inspectionProfiles/profiles_settings.xml	
+++ /dev/null
@@ -1,5 +0,0 @@
-<component name="InspectionProjectProfileManager">
-  <settings>
-    <option name="PROJECT_PROFILE" />
-  </settings>
-</component>
\ No newline at end of file
diff --git a/tkinter-pack Demo/.idea/misc.xml b/tkinter-pack Demo/.idea/misc.xml
deleted file mode 100644
index abf4cbe..0000000
--- a/tkinter-pack Demo/.idea/misc.xml	
+++ /dev/null
@@ -1,4 +0,0 @@
-<?xml version="1.0" encoding="UTF-8"?>
-<project version="4">
-  <component name="ProjectRootManager" version="2" project-jdk-name="Python 3.6.3 (C:\ProgramData\Anaconda3\python.exe)" project-jdk-type="Python SDK" />
-</project>
\ No newline at end of file
diff --git a/tkinter-pack Demo/.idea/modules.xml b/tkinter-pack Demo/.idea/modules.xml
deleted file mode 100644
index e169803..0000000
--- a/tkinter-pack Demo/.idea/modules.xml	
+++ /dev/null
@@ -1,8 +0,0 @@
-<?xml version="1.0" encoding="UTF-8"?>
-<project version="4">
-  <component name="ProjectModuleManager">
-    <modules>
-      <module fileurl="file://$PROJECT_DIR$/.idea/tkinter-pack Demo.iml" filepath="$PROJECT_DIR$/.idea/tkinter-pack Demo.iml" />
-    </modules>
-  </component>
-</project>
\ No newline at end of file
diff --git a/tkinter-pack Demo/.idea/tkinter-pack Demo.iml b/tkinter-pack Demo/.idea/tkinter-pack Demo.iml
deleted file mode 100644
index d0876a7..0000000
--- a/tkinter-pack Demo/.idea/tkinter-pack Demo.iml	
+++ /dev/null
@@ -1,8 +0,0 @@
-<?xml version="1.0" encoding="UTF-8"?>
-<module type="PYTHON_MODULE" version="4">
-  <component name="NewModuleRootManager">
-    <content url="file://$MODULE_DIR$" />
-    <orderEntry type="inheritedJdk" />
-    <orderEntry type="sourceFolder" forTests="false" />
-  </component>
-</module>
\ No newline at end of file
diff --git a/tkinter-pack Demo/.idea/workspace.xml b/tkinter-pack Demo/.idea/workspace.xml
deleted file mode 100644
index 366f187..0000000
--- a/tkinter-pack Demo/.idea/workspace.xml	
+++ /dev/null
@@ -1,33 +0,0 @@
-<?xml version="1.0" encoding="UTF-8"?>
-<project version="4">
-  <component name="ChangeListManager">
-    <list default="true" id="8bb229da-f2b6-4873-8706-801cc22bb81e" name="Default" comment="" />
-    <option name="TRACKING_ENABLED" value="true" />
-    <option name="SHOW_DIALOG" value="false" />
-    <option name="HIGHLIGHT_CONFLICTS" value="true" />
-    <option name="HIGHLIGHT_NON_ACTIVE_CHANGELIST" value="false" />
-    <option name="LAST_RESOLUTION" value="IGNORE" />
-  </component>
-  <component name="PropertiesComponent">
-    <property name="settings.editor.selected.configurable" value="sshConsole" />
-  </component>
-  <component name="ShelveChangesManager" show_recycled="false">
-    <option name="remove_strategy" value="false" />
-  </component>
-  <component name="TaskManager">
-    <task active="true" id="Default" summary="Default task">
-      <created>1539788216319</created>
-      <option name="number" value="Default" />
-      <option name="presentableId" value="Default" />
-      <updated>1539788216319</updated>
-    </task>
-    <servers />
-  </component>
-  <component name="VcsContentAnnotationSettings">
-    <option name="myLimit" value="2678400000" />
-  </component>
-  <component name="XDebuggerManager">
-    <breakpoint-manager />
-    <watches-manager />
-  </component>
-</project>
\ No newline at end of file
diff --git a/tkinter-pack Demo/__pycache__/tkutils.cpython-36.pyc b/tkinter-pack Demo/__pycache__/tkutils.cpython-36.pyc
deleted file mode 100644
index 3fe8297..0000000
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diff --git a/tkinter-pack Demo/__pycache__/win_ai.cpython-36.pyc b/tkinter-pack Demo/__pycache__/win_ai.cpython-36.pyc
deleted file mode 100644
index c753ba8..0000000
Binary files a/tkinter-pack Demo/__pycache__/win_ai.cpython-36.pyc and /dev/null differ
diff --git a/tkinter-pack Demo/__pycache__/win_multi.cpython-36.pyc b/tkinter-pack Demo/__pycache__/win_multi.cpython-36.pyc
deleted file mode 100644
index 67f8798..0000000
Binary files a/tkinter-pack Demo/__pycache__/win_multi.cpython-36.pyc and /dev/null differ
diff --git a/tkinter-pack Demo/__pycache__/win_multi2.cpython-36.pyc b/tkinter-pack Demo/__pycache__/win_multi2.cpython-36.pyc
deleted file mode 100644
index 435997c..0000000
Binary files a/tkinter-pack Demo/__pycache__/win_multi2.cpython-36.pyc and /dev/null differ
diff --git a/tkinter-pack Demo/__pycache__/win_single.cpython-36.pyc b/tkinter-pack Demo/__pycache__/win_single.cpython-36.pyc
deleted file mode 100644
index 89a57ee..0000000
Binary files a/tkinter-pack Demo/__pycache__/win_single.cpython-36.pyc and /dev/null differ
diff --git a/tkinter-pack Demo/app.bat b/tkinter-pack Demo/app.bat
deleted file mode 100644
index 7a84f97..0000000
--- a/tkinter-pack Demo/app.bat	
+++ /dev/null
@@ -1 +0,0 @@
-python main.py
\ No newline at end of file
diff --git a/tkinter-pack Demo/images/001.png b/tkinter_pack_demo/images/001.png
similarity index 100%
rename from tkinter-pack Demo/images/001.png
rename to tkinter_pack_demo/images/001.png
diff --git a/tkinter-pack Demo/images/Money.ico b/tkinter_pack_demo/images/Money.ico
similarity index 100%
rename from tkinter-pack Demo/images/Money.ico
rename to tkinter_pack_demo/images/Money.ico
diff --git a/tkinter-pack Demo/images/bg1.PNG b/tkinter_pack_demo/images/bg1.PNG
similarity index 100%
rename from tkinter-pack Demo/images/bg1.PNG
rename to tkinter_pack_demo/images/bg1.PNG
diff --git a/tkinter-pack Demo/images/bg2.PNG b/tkinter_pack_demo/images/bg2.PNG
similarity index 100%
rename from tkinter-pack Demo/images/bg2.PNG
rename to tkinter_pack_demo/images/bg2.PNG
diff --git a/tkinter-pack Demo/images/close.PNG b/tkinter_pack_demo/images/close.PNG
similarity index 100%
rename from tkinter-pack Demo/images/close.PNG
rename to tkinter_pack_demo/images/close.PNG
diff --git a/tkinter-pack Demo/images/img_title.PNG b/tkinter_pack_demo/images/img_title.PNG
similarity index 100%
rename from tkinter-pack Demo/images/img_title.PNG
rename to tkinter_pack_demo/images/img_title.PNG
diff --git a/tkinter-pack Demo/images/python.PNG b/tkinter_pack_demo/images/python.PNG
similarity index 100%
rename from tkinter-pack Demo/images/python.PNG
rename to tkinter_pack_demo/images/python.PNG
diff --git a/tkinter-pack Demo/images/user.PNG b/tkinter_pack_demo/images/user.PNG
similarity index 100%
rename from tkinter-pack Demo/images/user.PNG
rename to tkinter_pack_demo/images/user.PNG
diff --git a/tkinter-pack Demo/main.py b/tkinter_pack_demo/main.py
similarity index 97%
rename from tkinter-pack Demo/main.py
rename to tkinter_pack_demo/main.py
index c7b4869..dd5d0e9 100644
--- a/tkinter-pack Demo/main.py	
+++ b/tkinter_pack_demo/main.py
@@ -59,7 +59,7 @@ def body(self):
 			.pack(side=tk.LEFT, expand=tk.YES, anchor=tk.CENTER, padx=5)
 		tk.Button(canvas, text="多组件演示", bg="cadetblue", command=self.show_multi, font=ft2, height=2, fg="white", width=15)\
 			.pack(side=tk.LEFT, expand=tk.YES, anchor=tk.CENTER, padx=5)
-		tk.Button(canvas, text="应用平台界面", bg="cadetblue", command=self.show_ai, font=ft2, height=2, fg="white", width=15)\
+		tk.Button(canvas, text="应用界面演示", bg="cadetblue", command=self.show_ai, font=ft2, height=2, fg="white", width=15)\
 			.pack(side=tk.RIGHT, expand=tk.YES, anchor=tk.CENTER, padx=5)
 
 	def show_title(self, *args):
diff --git a/tkinter_pack_demo/run.bat b/tkinter_pack_demo/run.bat
new file mode 100644
index 0000000..ce5f798
--- /dev/null
+++ b/tkinter_pack_demo/run.bat
@@ -0,0 +1 @@
+..\.venv\scripts\python.exe main.py
diff --git a/tkinter_pack_demo/tkutils.py b/tkinter_pack_demo/tkutils.py
new file mode 100644
index 0000000..4f5cbf0
--- /dev/null
+++ b/tkinter_pack_demo/tkutils.py
@@ -0,0 +1,95 @@
+# coding: utf-8
+
+import tkinter as tk
+import tkinter.font as tkFont
+from PIL import Image, ImageTk
+from tkinter import messagebox
+
+
+def show_info(message=""):
+	messagebox.showinfo("提示框", message)
+
+
+def show_confirm(message=""):
+	"""
+		True  : yes
+		False : no
+	"""
+	return messagebox.askyesno("确认框", message)
+
+
+def center_window(win, width=None, height=None):
+	""" 将窗口屏幕居中 """
+	screenwidth = win.winfo_screenwidth()
+	screenheight = win.winfo_screenheight()
+	if width is None:
+		width, height = get_window_size(win)[:2]
+	size = '%dx%d+%d+%d' % (width, height, (screenwidth - width)/2, (screenheight - height)/3)
+	win.geometry(size)
+
+
+def get_window_size(win, update=True):
+	""" 获得窗体的尺寸 """
+	if update:
+		win.update()
+	return win.winfo_width(), win.winfo_height(), win.winfo_x(), win.winfo_y()
+
+
+def tkimg_resized(img, w_box, h_box, keep_ratio=True):
+	"""对图片进行按比例缩放处理"""
+	w, h = img.size
+
+	if keep_ratio:
+		if w > h:
+			width = w_box
+			height = int(h_box * (1.0 * h / w))
+
+		if h >= w:
+			height = h_box
+			width = int(w_box * (1.0 * w / h))
+	else:
+		width = w_box
+		height = h_box
+
+	img1 = img.resize((width, height), Image.ANTIALIAS)
+	tkimg = ImageTk.PhotoImage(img1)
+	return tkimg
+
+
+def image_label(frame, img, width, height, keep_ratio=True):
+	"""输入图片信息，及尺寸，返回界面组件"""
+	if isinstance(img, str):
+		_img = Image.open(img)
+	else:
+		_img = img
+	lbl_image = tk.Label(frame, width=width, height=height)
+
+	tk_img = tkimg_resized(_img, width, height, keep_ratio)
+	lbl_image.image = tk_img
+	lbl_image.config(image=tk_img)
+	return lbl_image
+
+
+def _font(fname="微软雅黑", size=12, bold=tkFont.NORMAL):
+	"""设置字体"""
+	ft = tkFont.Font(family=fname, size=size, weight=bold)
+	return ft
+
+
+def _ft(size=12, bold=False):
+	"""极简字体设置函数"""
+	if bold:
+		return _font(size=size, bold=tkFont.BOLD)
+	else:
+		return _font(size=size, bold=tkFont.NORMAL)
+
+
+def h_seperator(parent, height=2):  # height 单位为像素值
+	"""水平分割线, 水平填充 """
+	tk.Frame(parent, height=height, bg="whitesmoke").pack(fill=tk.X)
+
+
+def v_seperator(parent, width, bg="whitesmoke"):  # width 单位为像素值
+	"""垂直分割线 , fill=tk.Y, 但如何定位不确定，直接返回对象，由容器决定 """
+	frame = tk.Frame(parent, width=width, bg=bg)
+	return frame
\ No newline at end of file
diff --git a/tkinter-pack Demo/win_ai.py b/tkinter_pack_demo/win_ai.py
similarity index 100%
rename from tkinter-pack Demo/win_ai.py
rename to tkinter_pack_demo/win_ai.py
diff --git a/tkinter-pack Demo/win_multi.py b/tkinter_pack_demo/win_multi.py
similarity index 100%
rename from tkinter-pack Demo/win_multi.py
rename to tkinter_pack_demo/win_multi.py
diff --git a/tkinter-pack Demo/win_multi2.py b/tkinter_pack_demo/win_multi2.py
similarity index 100%
rename from tkinter-pack Demo/win_multi2.py
rename to tkinter_pack_demo/win_multi2.py
diff --git a/tkinter-pack Demo/win_single.py b/tkinter_pack_demo/win_single.py
similarity index 100%
rename from tkinter-pack Demo/win_single.py
rename to tkinter_pack_demo/win_single.py