Plotting histograms against classes in pandas / matplotlib
matplotlib, pandas, plot, python
Solution
How about `df.groupby("class").feature.hist()`? To see overlapping distributions you'll probably need to pass `alpha=0.4` to `hist()`. Alternatively, I'd be tempted to use a kernel density estimate instead of a histogram with `df.groupby("class").feature.plot(kind='kde')`.
As an example, I plotted the iris dataset's classes using:
iris.groupby("Name").PetalWidth.plot(kind='kde', ax=axs[1])
iris.groupby("Name").PetalWidth.hist(alpha=0.4, ax=axs[0])
Problem
Is there a idiomatic way to plot the histogram of a feature for two classes? In pandas, I basically want ``` df.feature[df.class == 0].hist() df.feature[df.class == 1].hist() ``` To be in the same plot. I could do ``` df.feature.hist(by=df.class) ``` but that gives me two separate plots. This seems to be a common task so I would imagine there to be an idiomatic way to do this. Of course I could manipulate the histograms manually to fit next to each other but usually pandas does that quite nicely. Basically I want this matplotlib example in one line of pandas: http://matplotlib.org/examples/pylab_examples/barchart_demo.html I thought I was missing something, but maybe it is not possible (yet).