Python library to make plotting simpler for data scientists
Chartify is a Python library that aims to make it as easy as possible 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.
- Chartify can be installed via pip:
pip3 install chartify
- Install chromedriver requirement:
- 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
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.
Code of Conduct
This project adheres to the Open Code of Conduct. By participating, you are expected to honor this code.
- Fix scatter plot bug that can occur due to nested data types.
- Added hexbin plot type.
- More control over grouped axis label orientation.
- Added alpha control to scatter, line, and parallel plots.
- Added control over marker style to scatter plot.
- Added ability to create custom color palettes.
- Changed default accent color.
- Visual tweaks to lollipop plot.
- Bar plots with a few number of series will have better widths.
- First release on PyPI.
Release history Release notifications
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