Metadata-Version: 1.1
Name: pairplotr
Version: 1.2.3
Summary: Pairplotr is a Python library used to graph combinations of numerical and categorical data in a pair plot
Home-page: http://packages.python.org/pairplotr
Author: Christopher Shymansky
Author-email: CMShymansky@gmail.com
License: OSI Approved :: Apache Software License
Description: <img src="https://github.com/JaggedParadigm/pairplotr/blob/master/pairplot_demo.png" width="500" />
        
        # How
        ## Installation
        For now, simply clone the respository and link to the location in your code. 
        
        ## Use
        See the [demo](https://nbviewer.jupyter.org/github/JaggedParadigm/pairplotr/blob/master/pairplotr_demo.ipynb) for use of pairplotr.
        
        # What
        Pairplotr is a Python library used to graph combinations of numerical and categorical data in a pair plot,
        similar to Seaborn's pairplot(), given a cleaned Pandas dataframe with a mixture of categorical and numerical
        values.
        
        Here are the formats for Row feature|Column feature combinations in either on- or off-diagonal cells: 
        
        - On-diagonal:        
          - Categorical|Categorical:
            - Value counts of feature values ordered by ascending value count and colored by feature values
          - Numerical|Numerical:
            - Histogram of feature w/ no coloring (or by desired label)
        - Off-diagonal:
          - Categorical|Categorical:
            - Stacked value count of row feature values colored by column feature values
          - Categorical|Numerical:
            - Histograms of column feature for each row feature value colored by row feature value
          - Numerical|Numerical:
            - Scatter plot of row feature values vs column feature values w/ no coloring (or by desired label)
        
        # Why
        The available tools I've found don't seem to be able to combine numerical and categorical feature data
        in a quick and easy way and I wanted to customize the comparisons as the plot types I find most useful.
Keywords: scikit-learn pandas data visualization pairplot
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Topic :: Utilities
Classifier: License :: OSI Approved :: Apache Software License
