Metadata-Version: 2.1
Name: edahub
Version: 0.0.1
Summary: EDAHub helps structure exploratory data analysis (EDA) results.
Home-page: https://github.com/not-so-fat/edahub
Author: @not-so-fat
Author-email: conjurer.not.so.fat@gmail.com
License: UNKNOWN
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.9
Description-Content-Type: text/markdown

# EDAHub
## What is this?

EDA (exploratory data analysis) results can be more structured.

EDAHub provides a side screen in JupyterLab to summarize your data, making it easier and quicker to revisit.
![Screenshot](assets/readme_example.png)


## Why this is useful?
As a data scientist, I've seen many notebooks that mix data/ML pipeline logic with observations. EDAHub addresses this by organizing basic observations in one place.

## How to start
You can try it on your JupyterLab with pip install:

```bash
pip install edahub
```

then add your pandas.DataFrame with name:

```
import edahub
eda = edahub.EDAHub()

eda.add_table("customers", df)
```

You will see the widget on the right side.


