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Last Commit
Dec. 15, 2018
Created
Sep. 17, 2018

Chartify

status release python

Chartify is a Python library that makes it easy for data scientists to create charts.

Why use Chartify?

  • Consistent input data format: Spend less time transforming data to get your charts to work. All plotting functions use a consistent tidy input data format.
  • Smart default styles: Create pretty charts with very little customization required.
  • Simple API: We've attempted to make to the API as intuitive and easy to learn as possible.
  • Flexibility: Chartify is built on top of Bokeh, so if you do need more control you can always fall back on Bokeh's API.

Examples

https://raw.githubusercontent.com/spotify/chartify/master/docs/_static/chartify1.png

https://raw.githubusercontent.com/spotify/chartify/master/docs/_static/chartify2.png

https://raw.githubusercontent.com/spotify/chartify/master/docs/_static/chartify3.png

https://raw.githubusercontent.com/spotify/chartify/master/docs/_static/chartify4.png

https://raw.githubusercontent.com/spotify/chartify/master/docs/_static/chartify5.png

https://raw.githubusercontent.com/spotify/chartify/master/docs/_static/chartify6.png

See this notebook for more examples!.

Installation

  1. Chartify can be installed via pip:

pip3 install chartify

  1. Install chromedriver requirement (Optional. Needed for PNG output):
    • Install google chrome.
    • Download the appropriate version of chromedriver for your OS here.
    • Copy the executable file to a directory within your PATH.
      • View directorys in your PATH variable: echo $PATH
      • Copy chromedriver to the appropriate directory, e.g.: cp chromedriver /usr/local/bin

Getting started

This tutorial notebook is the best place to get started with a guided tour of the core concepts of Chartify.

From there, check out the example notebook for a list of all the available plots.

Getting support

Join #chartify on spotify-foss.slack.com (Get an invite)

Use the chartify tag on StackOverflow.

Code of Conduct

This project adheres to the Open Code of Conduct. By participating, you are expected to honor this code.

Contributing

See the contributing docs.

Latest Releases
2.3.5
 Nov. 21 2018
Updated Bokeh requirement to support 1.0+
 Nov. 16 2018
Removed Pillow dependency upper bound
 Oct. 24 2018
Scatter plot with categorical axis
 Oct. 18 2018
Scatterplot bug fix
 Sep. 27 2018