title: Pandas side-by-side stacked bar plot
body: <p>I want to create a stacked bar plot of the <a href="https://www.kaggle.com/c/titanic/data" rel="noreferrer">titanic dataset</a>. The plot needs to group by "Pclass", "Sex" and "Survived". I have managed to do this with a lot of tedious numpy manipulation to produce the normalized plot below (where "M" is male and "F" is female)<a href="https://i.stack.imgur.com/SqFGH.png" rel="noreferrer"><img src="https://i.stack.imgur.com/SqFGH.png" alt="enter image description here"></a></p>
  
  <p>Is there a way to do this using pandas inbuilt plotting functionality?</p>
  
  <p>I have tried this:</p>
  
  <pre><code>import pandas as pd
  import matplotlib.pyplot as plt
  df = pd.read_csv('train.csv')
  df_grouped = df.groupby(['Survived','Sex','Pclass'])['Survived'].count()
  df_grouped.unstack().plot(kind='bar',stacked=True,  colormap='Blues', grid=True, figsize=(13,5));
  </code></pre>
  
  <p><a href="https://i.stack.imgur.com/4uIY9.png" rel="noreferrer"><img src="https://i.stack.imgur.com/4uIY9.png" alt="enter image description here"></a></p>
  
  <p>Which is not what I want. Is there anyway to produce the first plot using pandas plotting? Thanks in advance</p>