Adding a y-axis label to secondary y-axis in matplotlib

I can add a y label to the left y-axis using plt.ylabel, but how can I add it to the secondary y-axis?

table = sql.read_frame(query,connection) table[0].plot(color=colors[0],ylim=(0,100)) table[1].plot(secondary_y=True,color=colors[1]) plt.ylabel('$') 

5 Answers

The best way is to interact with the axes object directly

import numpy as np import matplotlib.pyplot as plt x = np.arange(0, 10, 0.1) y1 = 0.05 * x**2 y2 = -1 *y1 fig, ax1 = plt.subplots() ax2 = ax1.twinx() ax1.plot(x, y1, 'g-') ax2.plot(x, y2, 'b-') ax1.set_xlabel('X data') ax1.set_ylabel('Y1 data', color='g') ax2.set_ylabel('Y2 data', color='b') plt.show() 

There is a straightforward solution without messing with matplotlib: just pandas.

Tweaking the original example:

table = sql.read_frame(query,connection) ax = table[0].plot(color=colors[0],ylim=(0,100)) ax2 = table[1].plot(secondary_y=True,color=colors[1], ax=ax) ax.set_ylabel('Left axes label') ax2.set_ylabel('Right axes label') 

Basically, when the secondary_y=True option is given (eventhough ax=ax is passed too) pandas.plot returns a different axes which we use to set the labels.

I know this was answered long ago, but I think this approach worths it.

I don't have access to Python right now, but off the top of my head:

fig = plt.figure() axes1 = fig.add_subplot(111) # set props for left y-axis here axes2 = axes1.twinx() # mirror them axes2.set_ylabel(...) 

For everyone stumbling upon this post because pandas gets mentioned, you now have the very elegant and straightforward option of directly accessing the secondary_y axis in pandas with ax.right_ax

So paraphrasing the example initially posted, you would write:

table = sql.read_frame(query,connection) ax = table[[0, 1]].plot(ylim=(0,100), secondary_y=table[1]) ax.set_ylabel('$') ax.right_ax.set_ylabel('Your second Y-Axis Label goes here!') 

(this is already mentioned in these posts as well: 1 2)

Simple example with few loc:

plot(y1) plt.gca().twinx().plot(y2, color = 'r') # default color is same as first ax 

Explanation:

ax = plt.gca() # Get current axis ax2 = ax.twinx() # make twin axis based on x ax2.plot(...) # ...