Plotting categorical data with pandas and matplotlib

I have a data frame with categorical data:

     colour  direction
1    red     up
2    blue    up
3    green   down
4    red     left
5    red     right
6    yellow  down
7    blue    down

I want to generate some graphs, like pie charts and histograms based on the categories. Is it possible without creating dummy numeric variables? Something like

df.plot(kind='hist')

You can simply use value_counts on the series:

df['colour'].value_counts().plot(kind='bar')

You might find useful mosaic plot from statsmodels. Which can also give statistical highlighting for the variances.

from statsmodels.graphics.mosaicplot import mosaic
plt.rcParams['font.size'] = 16.0
mosaic(df, ['direction', 'colour']);

But beware of the 0 sized cell - they will cause problems with labels.

See this answer for details

like this :

df.groupby('colour').size().plot(kind='bar')

You could also use countplot from seaborn. This package builds on pandas to create a high level plotting interface. It gives you good styling and correct axis labels for free.

import pandas as pd
import seaborn as sns
sns.set()

df = pd.DataFrame({'colour': ['red', 'blue', 'green', 'red', 'red', 'yellow', 'blue'],
                   'direction': ['up', 'up', 'down', 'left', 'right', 'down', 'down']})
sns.countplot(df['colour'], color='gray')

It also supports coloring the bars in the right color with a little trick

sns.countplot(df['colour'],
              palette={color: color for color in df['colour'].unique()})