Plot one stacked bar from more different dataframes in python Pandas

Question

I need to plot data like this:

df1
id  value
ba1  4 
ba2  5
ba3  5

df2
   id     value
ba1, ba3  4
ba2       3
ba2, ba3  2
ba3       5

df3
     id       value
ba1, ba3       3
ba1, ba3, ba4  1
ba2            3
ba2, ba3       2
ba3            4
ba3, ba4       1

Every df has the same sum of value, 14. I think that would be a stacked bar plot good solution, with one bar per df, where values would be presented in percent. But I have no idea how to do from three different data frames. Everything I found there it was for the more numeric-value column from one df. Any help is welcomed. Thanks in advance.

The desired output would be something like this: example but in X would be name of dataframe

Joe · Accepted Answer · 2017-12-07 11:44:41Z

1

Something like this should work:

import pandas as pd
import matplotlib.pyplot as plt


df1 = {'id': ['ba1', 'ba2', 'ba3'], 'value': [4,5,5]}
df1 = pd.DataFrame(data=df1)
df1.set_index('id', inplace=True)

df2 = {'id': ['ba1, ba3', 'ba2', 'ba2, ba3', 'ba3'], 'value': [4,3,2,5]}
df2 = pd.DataFrame(data=df2)
df2.set_index('id', inplace=True)

df3 = {'id': ['ba1, ba3', 'ba1, ba3, ba4', 'ba2', 'ba2, ba3', 'ba3', 'ba3,\
ba4'], 'value': [3,1,3,2,4,1]}
df3 = pd.DataFrame(data=df3)
df3.set_index('id', inplace=True)

ax = plt.gca()
df1.T.plot(kind='bar', stacked=True, ax=ax, width=0.05, position=0)
df2.T.plot(kind='bar', stacked=True, ax=ax, width=0.05, position=1)
df3.T.plot(kind='bar', stacked=True, ax=ax, width=0.05, position=2)
plt.show()

answered Dec 7, 2017 at 11:44

Joe

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