creating stacked histogram with pandas dataframes data python

Question

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

Answer 1

The method in that post should work:

plt.hist([df1['text'],df2['printed']],
          bins=100, range=(1,100), stacked=True, color = ['r','g'])