Metadata-Version: 1.2
Name: chartify
Version: 3.0.0
Summary: Python library to make plotting simpler for data scientists
Home-page: https://github.com/spotify/chartify
Author: 
Author-email: chalpert@spotify.com
License: Apache 2
Description: Chartify
        ========
        
        |status|  |release|  |python|
        
        .. |status| image:: https://img.shields.io/badge/Status-Beta-blue.svg
        .. |release| image:: https://img.shields.io/badge/Release-3.0.0-blue.svg
        .. |python| image:: https://img.shields.io/badge/Python-3.6-blue.svg
        
        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 <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
        .. image:: https://raw.githubusercontent.com/spotify/chartify/master/docs/_static/chartify2.png
        .. image:: https://raw.githubusercontent.com/spotify/chartify/master/docs/_static/chartify3.png
        .. image:: https://raw.githubusercontent.com/spotify/chartify/master/docs/_static/chartify4.png
        .. image:: https://raw.githubusercontent.com/spotify/chartify/master/docs/_static/chartify5.png
        .. image:: https://raw.githubusercontent.com/spotify/chartify/master/docs/_static/chartify6.png
        
        `See this notebook for more examples! </examples/Examples.ipynb>`_.
        
        Installation
        ------------
        
        1. Chartify can be installed via pip:
        
        ``pip3 install chartify``
        
        2. 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/a/chromium.org/chromedriver/downloads>`_.
            - 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>`_.
        
        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 <CONTRIBUTING.rst>`_.
        
        
        =======
        History
        =======
        
        3.0.0 (2020-05-29)
        ------------------
        
        * Updated Python to 3.6+ and Pandas to 1.0+ (Thanks @tomasaschan!)
        * Updated Bokeh to 2.0+
        * Removed colour dependency to fix setup errors.
        
        2.7.0 (2019-11-27)
        ------------------
        
        Bugfixes:
        
        * Updated default yaml loader to move off of
          deprecated method (Thanks @vh920!)
        * Updated legend handling to adjust for deprecated methods
          in recent versions of Bokeh (Thanks for reporting @jpkoc)
        * Updated license in setup.py (Thanks for reporting @jsignell)
        * Bump base Pillow dependency to avoid insecure version.
        * Update MANIFEST to include missing files (Thanks @toddrme2178!)
        
        2.6.1 (2019-08-15)
        ------------------
        
        Bugfixes:
        
        * Moved package requirements and fixed bug that occured with
          latest version of Bokeh (Thanks @emschuch & @mollymzhu!)
        * Fixed bug in README while generating docs (Thanks @Bharat123rox!)
        
        2.6.0 (2019-03-08)
        ------------------
        
        Improvements:
        
        * Allows users to plot colors on bar charts that aren't contained in the
          categorical axis.
        
        
        Bugfixes:
        
        * Fixed bug that caused float types to break when plotted with categorical
          text plots (Thanks for finding @danela!)
        * Fixed broken readme links.
        
        2.5.0 (2019-02-17)
        ------------------
        
        Improvements:
        
        * Added Radar Chart
        
        2.4.0 (2019-02-16)
        ------------------
        
        Improvements:
        
        * Added second Y axis plotting.
        * Removed Bokeh loading notification on import (Thanks @canavandl!)
        * Added support for custom Bokeh resource loading (Thanks @canavandl!)
        * Added example for Chart.save() method (Thanks @david30907d!)
        
        Bugfixes:
        
        * Updated documentation for saving and showing svgs.
        * Fixed bug that broke plots with no difference between min and max
          points. (Thanks for finding @fabioconcina!)
        
        2.3.5 (2018-11-21)
        ------------------
        
        Improvements:
        
        * Updated docstrings (Thanks @gregorybchris @ItsPugle!)
        * Added SVG output options to Chart.show() and Chart.save()
          (Thanks for the suggestion @jdmendoza!)
        
        Bugfixes:
        
        * Fixed bug that caused source label to overlap with xaxis labels.
        * Fixed bug that prevented x axis orientation changes
          with datetime axes (Thanks for finding @simonwongwong!)
        * Fixed bug that caused subtitle to disappear
          with `outside_top` legend location (Thanks for finding @simonwongwong!)
        * Line segment callout properties will work
          correctly. (Thanks @gregorybchris!)
        
        2.3.4 (2018-11-13)
        ------------------
        
        * Updated Bokeh version requirements to support 1.0
        
        2.3.3 (2018-10-24)
        ------------------
        
        * Removed upper bound of Pillow dependency.
        
        2.3.2 (2018-10-18)
        ------------------
        
        * Stacked bar and area order now matches default vertical legend order.
        * Added method for shifting color palettes.
        * Added scatter plots with a single categorical axis.
        * Fixed bug with text_stacked that occurred with multiple categorical levels.
        
        2.3.1 (2018-09-27)
        ------------------
        
        * Fix scatter plot bug that can occur due to nested data types.
        
        2.3.0 (2018-09-26)
        ------------------
        
        * 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.
        
        
        2.2.0 (2018-09-17)
        ------------------
        
        * First release on PyPI.
        
Keywords: chartify
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Science/Research
Classifier: Natural Language :: English
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Classifier: License :: OSI Approved :: Apache Software License
Requires-Python: >=3.5,<4
