Mosaiq for Python
This is a simplified mosaic plot technique that works for numeric/categorical data.
For categorical data, a frequency table of values is calculated. Only the top 7 most common categories are preserved. The rest are replaced by "NA_TOPN".
For numeric data, a histogram is calculated over the distribution. The precise numeric values are replaced by its respective bin.
Call it with the following arguments:
- A dataframe
- The name of a "feature" column
- The name of a "target" column
- Whether the color ramp should be inverted (default : False)
- A colormap (default : derived from target column)
- The number of categories to preserve in categorical data (default : 7)
# dat (pandas dataframe) # feature (feature name string) # target (target name string) mosaiq(dat, feature, target)
Using this visualization makes it easy to iterate through all feature/target interactions in a given dataset:
for col in dat.columns: if col == target: continue # skip the plot if the column is the target mosaiq(mdat, col, target) plt.show()