#!/usr/bin/env python
# coding: utf-8

# In[1]:


get_ipython().run_line_magic('matplotlib', 'inline')


# # Enrichment Plot

# A function to plot step plots of cumulative counts.

# > from mlxtend.general_plotting import category_scatter

# ## Overview

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

# ### References
# 
# - -

# ## Example 1 - Enrichment Plots from Pandas DataFrames

# In[2]:


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'])
df


# 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.

# In[3]:


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

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


# ## API

# In[4]:


with open('../../api_modules/mlxtend.plotting/enrichment_plot.md', 'r') as f:
    print(f.read())