chartify

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

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Python

Chartify

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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 the API as intuitive and easy to learn as possible.
  • Flexibility: Chartify is built on top of Bokeh <http://bokeh.pydata.org/en/latest/>_, so if you do need more control you can always fall back on Bokeh’s API.

Examples

… image:: https://raw.githubusercontent.com/spotify/chartify/master/docs/_static/chartify1.png
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See this notebook for more examples! </examples/Examples.ipynb>_.

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 <https://sites.google.com/chromium.org/driver/>_.
    • 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 <https://github.com/spotify/chartify/blob/master/examples/Chartify%20Tutorial.ipynb>_ is the best place to get started with a guided tour of the core concepts of Chartify.

From there, check out the example notebook <https://github.com/spotify/chartify/blob/master/examples/Examples.ipynb>_ for a list of all the available plots.

Docs

Documentation available on chartify.readthedocs.io <https://chartify.readthedocs.io/en/latest/>_

Getting support

Join #chartify on spotify-foss.slack.com (Get an invite <https://slackin.spotify.com/>_)

Use the chartify tag on StackOverflow <https://stackoverflow.com/questions/tagged/chartify>_.

Resources

  • Data Visualization with Chartify <https://www.section.io/engineering-education/data-viz-chartify/>_

Code of Conduct

This project adheres to the Open Code of Conduct <https://github.com/spotify/code-of-conduct/blob/master/code-of-conduct.md>_. By participating, you are expected to honor this code.

Contributing

See the contributing docs <https://github.com/spotify/chartify/blob/master/CONTRIBUTING.rst>_.