Add a Y-Axis Label to the Secondary Y-Axis in Matplotlib
Suraj Joshi
Dec 10, 2020
Apr 22, 2020
Matplotlib
Matplotlib Axes
-
Direct Interaction With
axesObject -
DataFrame.plotMethod 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:
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:
