Plot a curve on top of 2 subplots simultaneously

Question

EDIT: My question was closed because someone thought another question was responding to it (but it doesn't: Matplotlib different size subplots). To clarify what I want: I would like to replicate something like what is done on this photo: having a 3rd dataset plotted on top of 2 subplots, with its y-axis displayed on the right.

I have 3 datasets spanning the same time interval (speed, position, precipitation). I would like to plot the speed and position in 2 horizontal subplots, and the precipitation spanning the 2 subplots. For example in the code below, instead of having the twinx() only on the first subplot, I would like to have it overlap the two subplots (ie. on the right side have a y-axis with 0 at the bottom right of the 2nd subplot, and 20 at the top right of the 1st subplot). I could I achieve that ?

import matplotlib.pyplot as plt
import numpy as np



fig, ax = plt.subplots(2,1,figsize=(20,15), dpi = 600)
#plot 1:
x = np.array([0, 1, 2, 3])
y = np.array([3, 8, 1, 10])

ax[0].plot(x,y, label = 'speed')
plt.legend()

#plot 2:
x = np.array([0, 1, 2, 3])
y = np.array([3, 8, 1, 10])

ax[1].plot(x,y, label = 'position')
plt.legend()


#plot 3:

x = np.array([0, 1, 2, 3])
y = np.array([10, 0, 4, 20])
ax2=ax[0].twinx()
ax2.plot(x,y, label = 'precipitation')

plt.legend(loc='upper right')
plt.show()

Answer 1

Best way I found is not very elegant but it works:

# Prepare 2 subplots
fig, ax = plt.subplots(2,1,figsize=(20,15), dpi = 600)
#plot 1:

# Dummy values for plotting
x = np.array([0, 1, 2, 3])
y = np.array([3, 8, 1, 10])

ax[0].plot(x,y, label = 'speed')

# Prints the legend
plt.legend()

#plot 2:
x = np.array([0, 1, 2, 3])
y = np.array([3, 8, 1, 10])

ax[1].plot(x,y, label = 'position')
plt.legend()


#plot 3:

x = np.array([0, 1, 2, 3])
y = np.array([10, 0, 4, 20])

# Add manually a 3rd subplot that stands on top of the 2 others
ax2 = fig.add_subplot(111, label="new subplot", facecolor="none")

# Move the y-axis to the right otherwise it will overlap with the ones on the left 
ax2.yaxis.set_label_position("right")

# "Erase" every tick and label of this 3rd plot
ax2.tick_params(left=False, right=True, labelleft=False, labelright=True,
                bottom=False, labelbottom=False)

# This line merges the x axes of the 1st and 3rd plot, and indicates
# that the y-axis of the 3rd plot will be drawn on the entirety of the 
# figure instead of just 1 subplot (because fig.add_subplot(111) makes it spread on the entirety of the figure) 
ax[0].get_shared_x_axes().join(ax[0],ax2)
ax2.plot(x,y, label = 'precipitation')

# Prints the legend in the upper right corner
plt.legend(loc='upper right')
plt.show()