Why does the Seaborn color palette not work for Pandas bar plots?
<p>An online Jupyter notebook demonstrating the code and showing the color differences is at:
<a href="https://anaconda.org/walter/pandas_seaborn_color/notebook" rel="noreferrer">https://anaconda.org/walter/pandas_seaborn_color/notebook</a></p>

<p>The colors are wrong when I make bar plots using Pandas dataframe method.  Seaborn improves the color palette of matplotlib.  All plots from matplotlib automatically use the new Seaborn palette.  However, bar plots from Pandas dataframes revert to the non-Seaborn colors.  This behavior is not consistent, because line plots from Pandas dataframes <strong>do</strong> use Seaborn colors.  This makes my plots appear to be in different styles, even if I use Pandas for all my plots.</p>

<p>How can I plot using Pandas methods while getting a consistent Seaborn color palette?</p>

<p>I'm running this in python 2.7.11 using a conda environment with just the necessary packages for this code (pandas, matplotlib and seaborn).</p>

<pre><code>import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns

df = pd.DataFrame({'y':[5,7,3,8]})

# matplotlib figure correctly uses Seaborn color palette
plt.figure()
plt.bar(df.index, df['y'])
plt.show()

# pandas bar plot reverts to default matplotlib color palette
df.plot(kind='bar')
plt.show()

# pandas line plots correctly use seaborn color palette 
df.plot()
plt.show()
</code></pre>