Read @emeek's post on designing the data explorer.
yarn add @nteract/data-explorer
Install react
and styled-components
if you are not already using them.
yarn add react styled-components
The data
prop must be a tabular data resource application/vnd.dataresource+json
// Default import complete with right side toolbar
import DataExplorer from "@nteract/data-explorer";
<DataExplorer data={data} />;
Or, with custom Toolbar
position:
// Individual components as named imports
import { DataExplorer, Toolbar, Viz } from "@nteract/data-explorer";
<DataExplorer data={data}>
<Toolbar />
<Viz />
</DataExplorer>;
// Toolbar is optional
<DataExplorer data={data}>
<Viz />
</DataExplorer>;
For expedited development, you can run npm run styleguide
and the data explorer documentation will be run live locally and you can experiment with the settings and data.
Navigate to the base directory of the repo and install all dependencies
yarn
Note: this requires Python >= 3.6
Now, install the Python package
cd applications/jupyter-extension
pip install -e .
jupyter serverextension enable nteract_on_jupyter
First we need to run the webpack server to live reload javascript and html assets. Anywhere in the nteract repository, run
npx lerna run hot --scope nteract-on-jupyter --stream
In another terminal, go to the directory that you want to run notebooks from and run
jupyter nteract --NteractConfig.asset_url="http://localhost:8080/"
The --NteractConfig.asset_url flag tells the Jupyter server where the webpack server will be serving the assets.
Once the assets have been built, you won't need to refresh the page, but you may need to manually refresh the page if it loads before the assets are built.
In the notebook launched from step 3, run the following code in a cell before anything else โฌ๏ธ
import pandas as pd
pd.options.display.html.table_schema = True
pd.options.display.max_rows = None