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

# In[1]:


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


# # Stacked Barplot

# A function to conveniently plot stacked bar plots in matplotlib using pandas `DataFrame`s. 

# > from mlxtend.general_plotting import category_scatter

# ## Overview

# A matplotlib convenience function for creating barplots from DataFrames where each sample is associated with several categories.

# ### References
# 
# - -

# ## Example 1 - Stacked Barplot from Pandas DataFrames

# In[2]:


import pandas as pd

s1 = [1.0, 2.0, 3.0, 4.0]
s2 = [1.4, 2.1, 2.9, 5.1]
s3 = [1.9, 2.2, 3.5, 4.1]
s4 = [1.4, 2.5, 3.5, 4.2]
data = [s1, s2, s3, s4]

df = pd.DataFrame(data, columns=['X1', 'X2', 'X3', 'X4'])
df.columns = ['X1', 'X2', 'X3', 'X4']
df.index = ['Sample1', 'Sample2', 'Sample3', 'Sample4']
df


# By default, the index of the `DataFrame` is used as column labels, and the `DataFrame` columns are used for the plot legend.

# In[3]:


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

fig = stacked_barplot(df, rotation=45, legend_loc='best')


# ## API

# In[1]:


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