python - PANDAS plot multiple Y axes

Question

I know pandas supports a secondary Y axis, but Im curious if anyone knows a way to put a tertiary Y axis on plots... currently I am achieving this with numpy+pyplot ... but it is slow with large data sets.

this is to plot different measurements with distinct units on the same graph for easy comparison (eg Relative Humidity/Temperature/ and Electrical Conductivity)

so really just curious if anyone knows if this is possible in pandas without too much work.

[Edit] I doubt that there is a way to do this(without too much overhead) however I hope to be proven wrong , this may be a limitation of matplotlib...

Answer 1

I think this might work:

import matplotlib.pyplot as plt
import numpy as np
from pandas import DataFrame
df = DataFrame(np.random.randn(5, 3), columns=['A', 'B', 'C'])

fig, ax = plt.subplots()
ax3 = ax.twinx()
rspine = ax3.spines['right']
rspine.set_position(('axes', 1.15))
ax3.set_frame_on(True)
ax3.patch.set_visible(False)
fig.subplots_adjust(right=0.7)

df.A.plot(ax=ax, style='b-')
# same ax as above since it's automatically added on the right
df.B.plot(ax=ax, style='r-', secondary_y=True)
df.C.plot(ax=ax3, style='g-')

# add legend --> take advantage of pandas providing us access
# to the line associated with the right part of the axis
ax3.legend([ax.get_lines()[0], ax.right_ax.get_lines()[0], ax3.get_lines()[0]],
           ['A','B','C'], bbox_to_anchor=(1.5, 0.5))

Output: