Support installation of custom widgets.

[blois]

Currently Colab only supports the widgets included in the ipywidgets package and does not allow installing additional widgets.

Additional background is available at https://github.com/nteract/nes/tree/master/portable-widgets.

[korakot]

Qgrid would make it easier to work with pandas dataframe.

Hope it will be supported in the future.

[cornhundred]

We're building a custom widget called Clustergrammer2 that is a webgl DataFrame viewer and is currently supported on Kaggle https://www.kaggle.com/cornhundred/heatmap-view-of-modern-era-player-stats

Also see nbviewer https://nbviewer.jupyter.org/github/ismms-himc/clustergrammer2-notebooks/blob/master/notebooks/3.0_10X_Genomics_2700_Dataset_NBViewer.ipynb

[blois]

Glancing at the widget code in https://github.com/ismms-himc/clustergrammer2/blob/5acea9bff7eda546cf0647b9e3647f631eb6f5f5/clustergrammer2/clustergrammer_fun/__init__.py#L222, it doesn't seem like it's making much use of the Widgets API, specifically comms messages.

A quick example of your (very slick) notebook running in Colab, with the visualizations:
https://colab.sandbox.google.com/gist/blois/dd01cd63d199acca951aadefb22067a8/heatmap-view-of-modern-era-player-stats.ipynb

[cornhundred]

Thanks @blois for your help. In order to run the notebook you sent I had to add the Seasons_Stats.csv (from here https://www.kaggle.com/drgilermo/nba-players-stats) to the filesystem.

However, I did not see the interactive visualization. Update: the heatmap did show up after a minute. I'll think about how to clean up the implementation. Thanks again!!

Looking forward to custom widget support, but this definitely helps out in the interim.

BTW @blois, how can I upload a dataset permanently into a shareable colab notebook (e.g. the sandbox link you sent)?

Here is a link to a notebook that does not require an external dataset https://colab.research.google.com/gist/cornhundred/b7154ee964c71cec6a2378f9cbba8eeb/clustergrammer2_example.ipynb?authuser=1

cc @manugarciaquismondo.

[blois]

@korakot we recently added an interactive dataframe viewer that we've been using internally for ages.

You can enable it by default with:

%load_ext google.colab.data_table
from vega_datasets import data
data.cars()

Or use it on a per-dataframe basis:

from google.colab.data_table import DataTable
from vega_datasets import data
DataTable(data.cars())

[korakot]

@blois Thanks a lot. It will surely help.

BTW, is there a widget to edit the dataframe as well?

And what other %load_ext are available? Is there a list somewhere?