https://github.com/chmduquesne/quickviz

Visualize a pandas dataframe in a few clicks
https://github.com/chmduquesne/quickviz

binder binder-ready ipywidgets pandas pandas-dataframe

Last synced: 5 months ago
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Visualize a pandas dataframe in a few clicks

• Host: GitHub
• URL: https://github.com/chmduquesne/quickviz
• Owner: chmduquesne
• Created: 2018-08-20T21:21:24.000Z (almost 8 years ago)
• Default Branch: master
• Last Pushed: 2019-05-01T03:20:40.000Z (about 7 years ago)
• Last Synced: 2025-12-07T02:55:19.116Z (6 months ago)
• Topics: binder, binder-ready, ipywidgets, pandas, pandas-dataframe
• Language: Jupyter Notebook
• Homepage:
• Size: 4.66 MB
• Stars: 21
• Watchers: 1
• Forks: 3
• Open Issues: 1
• Metadata Files:
  • Readme: README.md

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README

          
[![Build Status](https://travis-ci.org/chmduquesne/quickviz.svg?branch=master)](https://travis-ci.org/chmduquesne/quickviz)

[![Binder](https://mybinder.org/badge.svg)](https://mybinder.org/v2/gh/chmduquesne/quickviz/master?filepath=examples/Tutorial.ipynb)

Quickviz

========

Quickviz provides widgets for quickly visualizing pandas dataframes. It

interfaces with seaborn and pandas.plot.

Example

-------

![View of the interface](examples/ui.png)

See the

[gallery](https://nbviewer.jupyter.org/github/chmduquesne/quickviz/tree/master/quickviz/tests/seaborn/)

(which is also a test suite) for more.

Usage

-----

There only one function, visualize. Apply it to your dataframe, and start

playing.

    from quickviz import visualize as v

    from vega_datasets import data

    df = data.cars()

    v(df)

[Try it live!](https://mybinder.org/v2/gh/chmduquesne/quickviz/master?filepath=examples/Tutorial.ipynb)

Rationale

---------

It is often necessary to plot data in order to understand it. Plotting

allows to quiclky spot glitches in the data: that person who is 180 meters

tall or this car which can speed thousands of kilometers per hour will

immediately stand out. In this situation, one wants a way to quickly

(rather than beautifully) plot their data. Quickviz provides a set of

widgets to do this in a few clicks.

Installation

------------

    pip install ipywidgets

    jupyter nbextension enable --py widgetsnbextension

    pip install quickviz

Disclaimer

----------

Quickviz does not read the documentation for you! It only makes it easier

to use seaborn/pandas with a mouse. In order to understand what you are

doing, you still need to dig in their respective APIs.