Plotting three categories with two axes in matplotlib

Question

I am using a combination of pandas and matplotlib to plot three values for several categories. I would like one plot to have its own axis, and the other two to share an axis.

Close, but illustrates the issue with why I need dual axes:

pd.DataFrame([[1,2,3], [500,600,700], [500, 700, 650]], columns=['foo', 'bar','baz'],
             index=['a','b','c']).T.plot(kind='bar')

Instead, I would like a second axis for the a bars. My attempt:

smol = pd.DataFrame([[1,2,3], [500,600,700], [500, 700, 650]], columns=['foo', 'bar','baz'],
        index=['a','b','c']).T

fig = plt.figure(figsize=(10,5)) # Create matplotlib figure

ax = fig.add_subplot(111) # Create matplotlib axes
ax2 = ax.twinx() # Create another axes that shares the same x-axis as ax.

smol['a'].plot(kind='bar', color='red', ax=ax, width=0.3, 
                    position=1, edgecolor='black')
smol['b'].plot(kind='bar', color='blue', ax=ax2, width=0.3, 
                 position=0, edgecolor='black')

ax.set_ylabel('Small scale')
ax2.set_ylabel('Big scale')

plt.show()

Unfortunately, adding

smol['c'].plot(kind='bar', color='green', ax=ax2, width=0.3, 
                 position=0, edgecolor='black')

produces:

How can I have b and c share an axis, but appear next to each other, as in the first attempt?

Kamil Niski · Accepted Answer · 2018-10-15 21:49:37Z

2

I've used secondary_y keyword. The code is also considerably shorter

smol = pd.DataFrame([[1,2,3], [500,600,700], [500, 700, 650]], columns=['foo', 'bar','baz'],
        index=['a','b','c']).T

ax = smol.plot(kind="bar", secondary_y=['b', 'c'])

ax.set_ylabel('Small scale')
ax.right_ax.set_ylabel('Big scale')

plt.show()

answered Oct 15, 2018 at 21:49

Kamil Niski

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