How to Add a Y-Axis Label to the Secondary Y-Axis in Matplotlib

  1. Direct Interaction With axes Object
  2. DataFrame.plot Method to Add a Y-Axis Label to the Secondary Y-Axis

We can interact with the axes object directly or use DataFrame.plot method to add a y-axis label to the secondary y-axis in Matplotlib.

Direct Interaction With axes Object

We can make a plot with two different y-axis by using two different axes objects with the help of twinx() function. Now we can use the second axes object to make the plot of the second y-axis variable and update its label.

import numpy as np
import matplotlib.pyplot as plt

a=np.linspace(0,5,100)

y1 = np.sin(2 * np.pi * a)
y2 = np.cos(2 * np.pi * a)

fig, ax1 = plt.subplots()

ax1.set_xlabel('time (s)')
ax1.set_ylabel('sin', color='red')
ax1.plot(a, y1, color=color)
ax1.tick_params(axis='y', labelcolor=color)

ax2 = ax1.twinx()  
ax2.set_ylabel('cos', color='green')  
ax2.plot(a, y2, color=color)
ax2.tick_params(axis='y', labelcolor=color)

fig.tight_layout()
plt.show()

Output:

direct interaction with axes to add a y-axis label to the secondary y-axis object

ax2 = ax1.twinx()

Axes.twinx() creates a new Axes with a y-axis that is opposite to the original axis, in this example ax1.

DataFrame.plot Method to Add a Y-Axis Label to the Secondary Y-Axis

We can add a y-axis label to the secondary y-axis with pandas too. When we set the secondary_y option to be True in DataFrame.plot method, it returns different axes that can be used to set the labels.

import pandas as pd
import matplotlib.pyplot as plt

df = pd.DataFrame({'Age': [22, 12, 18, 25, 30],
                   'Height': [155,129,138,164,145],
                   'Weight': [60,40,45,55,60]})
ax=df.plot(kind='line', x='Age', y='Height', color='DarkBlue')

ax2=df.plot(kind='line', x='Age', y='Weight', secondary_y=True,color='Red', ax=ax)

ax.set_ylabel('Height')
ax2.set_ylabel('Weight')
plt.tight_layout()
plt.show()

Output:

DataFrame.plot method to add a y-axis label to the secondary y-axis

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