Set legend position when plotting a pandas dataframe with a second y-axis via pandas plotting interface [duplicate]

Question

I am plotting a pandas dataframe with a second y-axis via pandas plotting interface as described in the documentation like this:

df = pd.DataFrame(np.random.randn(24*3, 3),
                  index=pd.date_range('1/1/2019', periods=24*3, freq='h'))
df.columns = ['A (left)', 'B (right)', 'C (right)']
ax = df.plot(secondary_y=['B (right)', 'C (right)'], mark_right=False)
ax.set_ylabel('A scale')
ax.right_ax.set_ylabel('BC scale')
ax.legend(loc='upper right')
plt.show()

which yields As it can be seen, the legend looses entries when I set the position using ax.legend(loc='upper right').

Does anyone know how I can set the legend position and keep all entries?

Thanks in advance!

Answer 1

We can use .get_legend_handles_labels() for a more correct solution:

np.random.seed(42)

df = pd.DataFrame(np.random.randn(24*3, 3),
                  index=pd.date_range('1/1/2019', periods=24*3, freq='h'))
df.columns = ['A (left)', 'B (right)', 'C (right)']
ax = df.plot(secondary_y=['B (right)', 'C (right)'], mark_right=False)
ax.set_ylabel('A scale')
ax.right_ax.set_ylabel('BC scale')

h1, l1 = ax.get_legend_handles_labels()
h2, l2 = ax.right_ax.get_legend_handles_labels()
ax.legend(h1+h2, l1+l2, loc=1)

The reason we need to use that method is because ax and ax.right_ax each have their own legend and simply setting them to the same location will render them on top of each other.