[FIXED] How to adjust the ticks and label size of a pandas plot with secondary_y

Issue

I have a plot with a left and right y-axis created with pandas.DataFrame.plot and specifying secondary_y=True.

I want to increase the font sizes of the y-axis tick params, but it seems that only the left side y-axis font size is increasing.

import pandas as pd
import numpy as np

# sample dataframe
sample_length = range(1, 2+1)
rads = np.arange(0, 2*np.pi, 0.01)
data = np.array([np.sin(t*rads) for t in sample_length])
df = pd.DataFrame(data.T, index=pd.Series(rads.tolist(), name='radians'), columns=[f'freq: {i}x' for i in sample_length])

# display(df.head(3))
         freq: 1x  freq: 2x
radians                    
0.00     0.000000  0.000000
0.01     0.010000  0.019999
0.02     0.019999  0.039989

# plot
ax1 = df.plot(y='freq: 1x', ylabel='left-Y', figsize=(8, 5))
df.plot(y='freq: 2x', secondary_y=True, ax=ax1)

ax1.tick_params(axis='both', labelsize=20)

What is the way to increase the font size for the right y-axis?

Solution

• Access the secondary_y axes with ax2.set_ylabel('right-Y', fontsize=30), or access it from ax1 with the .right_ax attribute. dir(ax1) will show all of the available methods for ax1.
  • .right_ax does not work if ax2 is implemented with .twinx():
    • ax2 = ax1.twinx() and df.plot(y='freq: 2x', ax=ax2)
    • ax2.set_ylabel('right-Y', fontsize=30) works with .twinx()
• See pandas User Guide: Plotting on a secondary y-axis
• Tested in python 3.8.12, pandas 1.3.4, matplotlib 3.4.3

# plot the primary axes
ax1 = df.plot(y='freq: 1x', ylabel='left-Y', figsize=(8, 5))

# add the secondary y axes and assign it
ax2 = df.plot(y='freq: 2x', secondary_y=True, ax=ax1)

# adjust the ticks for the primary axes
ax1.tick_params(axis='both', labelsize=14)

# adjust the ticks for the secondary y axes
ax2.tick_params(axis='y', labelsize=25)

# set the primary (left) y label
ax1.set_ylabel('left Y', fontsize=18)

# set the secondary (right) y label from ax1
ax1.right_ax.set_ylabel('right-Y', fontsize=30)

# alternatively (only use one): set the secondary (right) y label from ax2
# ax2.set_ylabel('right-Y', fontsize=30)

plt.show()

Note

• If plotting all of the available columns, where select column should be on secondary_y, there's no need to specify y=, and secondary_y=['...', '...', ..., '...'] can be a list.
• Because the secondary axes is created at the same time as the primary axes, the secondary axes is not assigned to a variable, but this can be done with ax2 = ax.right_ax, then ax2 can be used directly.

ax = df.plot(ylabel='left-Y', secondary_y=['freq: 2x'], figsize=(8, 5))

ax.tick_params(axis='both', labelsize=14)
ax.right_ax.tick_params(axis='y', labelsize=25)

ax.set_ylabel('left Y', fontsize=18)

# set the right y axes
ax.right_ax.set_ylabel('right-Y', fontsize=30)

Answered By - Dametime