How to avoid the extra set of y-axis labels?

[deanhystad]

This creates two subplots. It returns a figure and an axes array.

fig, axs = plt.subplots(2,1)

axs[0] are the axes for the first subplot. axs[1] are the axes for the second subplot.

This is creating ONE additional y axis for each of your subplots.

twin0 = axs[0].twinx()   # Calling twinx() once for axs[0] creates 2nd y axis for first subplot
twin1 = axs[1].twinx()  # calling twinx() once for axs[1] creates 2nd y axis for second subplot

Each of your subplots now has 2 y axes

What you did in your initial post was treat twinx() like it returned a 2nd y axis. It does not. twinx() creates a new y axis. If you call twinx() ten times it will create 10 new y axes.

This is creating TWO additional y axes for one of your subplots.

axs[0].twinx().set_ylabel('SPX Price') # This creates a new axis (#2 y axis for the first subplot)
axs[0].plot(sample_df['Spread_Price'],color='red')
axs[0].twinx().plot(sample_df['SPX']) # This also creates a new y axis (#3 y axis for the first subplot)

For proof you could rewrite your original code like this.

import matplotlib.pyplot as plt
import pandas as pd

sample_data = [[3000,18], [3200,17], [3500,16], [4000,12]]
sample_df = pd.DataFrame(sample_data, columns = ['SPX', 'Spread_Price'])
fig, axs = plt.subplots(2,1)
axs[0].set_ylabel('Spread Price')

a = axs[0].twinx()
a.set_ylabel('SPX Price')

b = axs[0].twinx()
b.twinx().plot(sample_df['SPX'])

axs[1].twinx().plot(sample_df['Spread_Price'])
axs[1].plot(sample_df['SPX'],color='red')

c = axs[0].twinx()
c.twinx().set_yticklabels([])
print("These are all different axes", id(a), id(b), id(c))

plt.tight_layout()
plt.show()