Enrichment Plot

A function to plot step plots of cumulative counts.

from mlxtend.general_plotting import category_scatter


In enrichment plots, the y-axis can be interpreted as "how many samples are less or equal to the corresponding x-axis label."


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Example 1 - Enrichment Plots from Pandas DataFrames

import pandas as pd
s1 = [1.1, 1.5]
s2 = [2.1, 1.8]
s3 = [3.1, 2.1]
s4 = [3.9, 2.5]
data = [s1, s2, s3, s4]
df = pd.DataFrame(data, columns=['X1', 'X2'])
X1 X2
0 1.1 1.5
1 2.1 1.8
2 3.1 2.1
3 3.9 2.5

Plotting the data where the categories are determined by the unique values in the label column label_col. The x and y values are simply the column names of the DataFrame that we want to plot.

import matplotlib.pyplot as plt
from mlxtend.plotting import enrichment_plot

ax = enrichment_plot(df, legend_loc='upper left')



enrichment_plot(df, colors='bgrkcy', markers=' ', linestyles='-', alpha=0.5, lw=2, where='post', grid=True, count_label='Count', xlim='auto', ylim='auto', invert_axes=False, legend_loc='best', ax=None)

Plot stacked barplots


  • df : pandas.DataFrame

    A pandas DataFrame where columns represent the different categories. colors: str (default: 'bgrcky') The colors of the bars.

  • markers : str (default: ' ')

    Matplotlib markerstyles, e.g, 'sov' for square,circle, and triangle markers.

  • linestyles : str (default: '-')

    Matplotlib linestyles, e.g., '-,--' to cycle normal and dashed lines. Note that the different linestyles need to be separated by commas.

  • alpha : float (default: 0.5)

    Transparency level from 0.0 to 1.0.

  • lw : int or float (default: 2)

    Linewidth parameter.

  • where : {'post', 'pre', 'mid'} (default: 'post')

    Starting location of the steps.

  • grid : bool (default: True)

    Plots a grid if True.

  • count_label : str (default: 'Count')

    Label for the "Count"-axis.

  • xlim : 'auto' or array-like [min, max] (default: 'auto')

    Min and maximum position of the x-axis range.

  • ylim : 'auto' or array-like [min, max] (default: 'auto')

    Min and maximum position of the y-axis range.

  • invert_axes : bool (default: False)

    Plots count on the x-axis if True.

  • legend_loc : str (default: 'best')

    Location of the plot legend {best, upper left, upper right, lower left, lower right} No legend if legend_loc=False

  • ax : matplotlib axis, optional (default: None)

    Use this axis for plotting or make a new one otherwise


  • ax : matplotlib axis