Welcome! This is a Python module that contains some useful data visualization functions.
Recommended method (in the terminal or command window, execute the following command):
pip install git+https://github.com/jsh9/python-plot-utils@v0.6.14For other installation alternatives, see the installation guide.
- 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)
Visualizing one column of data
api_docs/pie_chart api_docs/discrete_histogram
Visualizing two columns of data
api_docs/bin_and_mean api_docs/category_means api_docs/positive_rate api_docs/contingency_table api_docs/scatter_plot_two_cols
Visualizing multiple columns of data
api_docs/3d_histograms api_docs/hist_multi api_docs/violin_plot api_docs/correlation_matrix api_docs/missing_values
Map plotting
api_docs/choropleth_map
Time series plotting
api_docs/plot_time_series api_docs/plot_multiple_timeseries api_docs/fill_timeseries
Miscellaneous
api_docs/get_colors api_docs/get_linespecs api_docs/linespecs_demo api_docs/color_classes api_docs/plot_with_bounds api_docs/trim_image api_docs/pad_image api_docs/plot_ranking api_docs/visualize_cv_scores
Other helper functions
api_docs/_convert_FIPS_to_state_name api_docs/_translate_state_abbrev api_docs/_find_axes_lim
See here.
Examples are presented as Jupyter notebooks here.
Copyright: © 2017-2019, Jian Shi
License: GPL v3.0
https://github.com/jsh9/python-plot-utils
Bug reports and/or suggestions are welcome!
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