matplotlib create broken axis in subplot

Question

I have a problematic subplot that has two scales of data. Instead of using a log scale, I want to break the axis, so that half of the subplot y axis runs from 0 to 10 and th

Answer 1

I might suggest to use only two subplots, one at the top and one at the bottom. Then, divide the upper one into two via mpl_toolkits.axes_grid1.make_axes_locatable.

import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits.axes_grid1 import make_axes_locatable


x = np.random.uniform(0, 10, 40)
y = np.concatenate([np.random.uniform(0, 1, 30), np.random.uniform(0, 100, 10)])
y2 = np.random.uniform(0, 1, 40) 

fig, axes = plt.subplots(nrows=2, sharex=True)

ax = axes[0]
divider = make_axes_locatable(ax)
ax2 = divider.new_vertical(size="100%", pad=0.1)
fig.add_axes(ax2)

ax.scatter(x, y)
ax.set_ylim(0, 1)
ax.spines['top'].set_visible(False)
ax2.scatter(x, y)
ax2.set_ylim(10, 100)
ax2.tick_params(bottom=False, labelbottom=False)
ax2.spines['bottom'].set_visible(False)


# From https://matplotlib.org/examples/pylab_examples/broken_axis.html
d = .015  # how big to make the diagonal lines in axes coordinates
# arguments to pass to plot, just so we don't keep repeating them
kwargs = dict(transform=ax2.transAxes, color='k', clip_on=False)
ax2.plot((-d, +d), (-d, +d), **kwargs)        # top-left diagonal
ax2.plot((1 - d, 1 + d), (-d, +d), **kwargs)  # top-right diagonal

kwargs.update(transform=ax.transAxes)  # switch to the bottom axes
ax.plot((-d, +d), (1 - d, 1 + d), **kwargs)  # bottom-left diagonal
ax.plot((1 - d, 1 + d), (1 - d, 1 + d), **kwargs)  # bottom-right diagonal


#create bottom subplot as usual
axes[1].scatter(x, y2)


plt.show()