Unable to control scale of second y-axis on df.plo

Question

I am trying to plot 3 series with 2 on the left y-axis and 1 on the right using secondary_y, but it’s not clear to me how to define the right y-axis scale as I did on the left with ylim=().

I have seen this post: Interact directly with axes

… but once I have:

import matplotlib.pyplot as plt

df = pd.DataFrame(np.random.randn(10,3))

fig, ax1 = plt.subplots()

ax2 = ax1.twinx()
ax1.plot(df.index,df.iloc[:,[0,2]])
ax2.plot(df.index, df.iloc[:,2])

plt.show() doesn't produce anything at all. I am using:

• Spyder 2.3.5.2
• python: 3.4.3.final.0
• python-bits: 64
• OS: Windows
• OS-release: 7
• pandas: 0.16.2
• numpy: 1.9.2
• scipy: 0.15.1
• matplotlib: 1.4.3

I found these links helpful:

tcaswell, working directly with axes

matplotlib.axes documentation

Answer 1

You can do this without directly calling ax.twinx():

#Plot the first series on the LH y-axis
ax1 = df.plot('x_column','y1_column')

#Add the second series plot, and grab the RH axis
ax2 = df.plot('x_column','y2_column',ax=ax1)
ax2.set_ylim(0,10)

Note: Only tested in Pandas 19.2

Answer 2

You need to use set_ylim on the appropriate ax.

For example:

ax2 = ax1.twinx()
ax2.set_ylim(bottom=-10, top=10)

Also, reviewing your code, it appears that you are specifying your iloc columns incorrectly. Try:

ax1.plot(df.index, df.iloc[:, :2])  # Columns 0 and 1.
ax2.plot(df.index, df.iloc[:, 2])   # Column 2.

Answer 3

import matplotlib.pyplot as plt
import pandas as pd
import numpy as np

df = pd.DataFrame(np.random.randn(10,3))
print (df)
fig, ax1 = plt.subplots()

ax2 = ax1.twinx()
ax1.plot(df.index,df.iloc[:,[0,2]])
ax2.plot(df.index, df.iloc[:,2])

plt.show()