creating stacked histogram with pandas dataframes data python
graphing, matplotlib, pandas, python
Solution
The method in that post should work:
plt.hist([df1['text'],df2['printed']],
bins=100, range=(1,100), stacked=True, color = ['r','g'])
Problem
I am trying to create a stacked histogram with data from 2 or more uneven pandas dataframes? So far I can get them to graph on top of each other but not stack. ``` import pandas as pd import matplotlib.pyplot as plt df = pd.read_csv('dert.csv', encoding = "ISO-8859-1", index_col=0) df1['text'] = df['text'].dropna(subset=['five']) df2['printed'] = df['text2'] ax = df1['text'].hist( bins=100, range=(1,100), stacked=True, color = 'r') ax = df2['printed'].hist(bins=100, range=(1,100), stacked=True, color = 'g') plt.setp(ax.get_xticklabels(), rotation=45) plt.show() ``` How do I get them to stack? I found a solution but it does not use pandas dataframes Matplotlib, creating stacked histogram from three unequal length arrays