plot_utils documentation

Welcome! This is a Python module that contains some useful data visualization functions.

Installation

Recommended method (in the terminal or command window, execute the following command):

pip install git+https://github.com/jsh9/python-plot-utilities@v0.6.7

For other installation alternatives, see the installation guide.

Dependencies

• Python 2.7 or 3.5+
• matplotlib 1.5.0+, or 2.0.0+ (Version 2.1.0+ is strongly recommended.)
• numpy: 1.11.0+
• scipy: 0.19.0+
• pandas: 0.20.0+
• cycler: 0.10.0+
• matplotlib/basemap: 1.0.7 (only if you want to plot the two choropleth maps)
• PIL (only if you want to use the trim_img() function)

API Documentation

1. Visualizing one column of data

   • Pie chart
   • Discrete histogram

2. Visualizing two columns of data

   • Bin and mean
   • Category means
   • Positive rate
   • Contingency table
   • Scatter plots of two columns

3. Visualizing multiple columns of data

   • 3D histograms
   • Multiple histograms
   • Violin plot
   • Correlation matrix
   • Missing values

4. Map plotting

   • Choropleth maps (state and county levels)

5. Time series plotting

   • Plot time series
   • Plot multiple time series
   • Plot time series with filled error bounds

6. Miscellaneous

   • Get colors
   • Get line specifications
   • Demonstrating get_linespecs()
   • Two classes for querying colors
   • Plot lines with upper/lower bounds
   • Trim images
   • Plot ranking
   • Visualize CV scores

7. Other helper functions

   • Convert FIPS codes to state names
   • Translate between full state names and abbreviations
   • Find axes limits

Gallery

See here.

Examples

Examples are presented as Jupyter notebooks here.

Copyright and license

Copyright: © 2017-2019, Jian Shi

License: GPL v3.0

GitHub repository

https://github.com/jsh9/python-plot-utilities

Bug reports and/or suggestions are welcome!

Indices and tables

• Index
• Module Index
• Search Page