I have a pandas DataFrame
and I want to plot a bar chart that includes a legend.
import pylab as pl
from pandas import *
x = DataFrame({"Alpha": Series({1: 1, 2: 3, 3:2.5}), "Beta": Series({1: 2, 2: 2, 3:3.5})})
If I call plot directly, then it puts the legend above the plot:
x.plot(kind="bar")
If I turn of the legend in the plot and try to add it later, then it doesn't retain the colors associated with the two columns in the DataFrame (see below):
x.plot(kind="bar", legend=False)
l = pl.legend(('Alpha','Beta'), loc='best')
What's the right way to include a legend in a matplotlib plot from a Pandas DataFrame?
The most succinct way to go is:
x.plot(kind="bar").legend(bbox_to_anchor=(1.2, 0.5))
or in general
x.plot(kind="bar").legend(*args, **kwargs)
If you want to add the legend manually, you have to ask the subplot for the elements of the bar plot:
In [17]: ax = x.plot(kind='bar', legend=False)
In [18]: patches, labels = ax.get_legend_handles_labels()
In [19]: ax.legend(patches, labels, loc='best')
Out[19]: <matplotlib.legend.Legend at 0x10b292ad0>
Also, plt.legend(loc='best')
or ax.legend(loc='best')
should "just work", because there are already "links" to the bar plot patches set up when the plot is made, so you don't have to pass a list of axis labels.
I'm not sure if the version of pandas you're using returns a handle to the subplot (ax = ...
) but I'm fairly certain that 0.7.3 does. You can always get a reference to it with plt.gca()
.
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