Note
Click here to download the full example code
Scatter plot with histograms¶
Show the marginal distributions of a scatter as histograms at the sides of the plot.
For a nice alignment of the main axes with the marginals, two options are shown below.
- the axes positions are defined in terms of rectangles in figure coordinates
- the axes positions are defined via a gridspec
An alternative method to produce a similar figure using the axes_grid1
toolkit is shown in the
Scatter Histogram (Locatable Axes) example.
Let us first define a function that takes x and y data as input, as well as three axes, the main axes for the scatter, and two marginal axes. It will then create the scatter and histograms inside the provided axes.
import numpy as np
import matplotlib.pyplot as plt
# Fixing random state for reproducibility
np.random.seed(19680801)
# some random data
x = np.random.randn(1000)
y = np.random.randn(1000)
def scatter_hist(x, y, ax, ax_histx, ax_histy):
# no labels
ax_histx.tick_params(axis="x", labelbottom=False)
ax_histy.tick_params(axis="y", labelleft=False)
# the scatter plot:
ax.scatter(x, y)
# now determine nice limits by hand:
binwidth = 0.25
xymax = max(np.max(np.abs(x)), np.max(np.abs(y)))
lim = (int(xymax/binwidth) + 1) * binwidth
bins = np.arange(-lim, lim + binwidth, binwidth)
ax_histx.hist(x, bins=bins)
ax_histy.hist(y, bins=bins, orientation='horizontal')
Axes in figure coordinates¶
To define the axes positions, Figure.add_axes
is provided with a rectangle
[left, bottom, width, height]
in figure coordinates. The marginal axes
share one dimension with the main axes.
# definitions for the axes
left, width = 0.1, 0.65
bottom, height = 0.1, 0.65
spacing = 0.005
rect_scatter = [left, bottom, width, height]
rect_histx = [left, bottom + height + spacing, width, 0.2]
rect_histy = [left + width + spacing, bottom, 0.2, height]
# start with a square Figure
fig = plt.figure(figsize=(8, 8))
ax = fig.add_axes(rect_scatter)
ax_histx = fig.add_axes(rect_histx, sharex=ax)
ax_histy = fig.add_axes(rect_histy, sharey=ax)
# use the previously defined function
scatter_hist(x, y, ax, ax_histx, ax_histy)
plt.show()
![scatter hist](../../_images/sphx_glr_scatter_hist_001.png)
Using a gridspec¶
We may equally define a gridspec with unequal width- and height-ratios to achieve desired layout. Also see the Customizing Figure Layouts Using GridSpec and Other Functions tutorial.
# start with a square Figure
fig = plt.figure(figsize=(8, 8))
# Add a gridspec with two rows and two columns and a ratio of 2 to 7 between
# the size of the marginal axes and the main axes in both directions.
# Also adjust the subplot parameters for a square plot.
gs = fig.add_gridspec(2, 2, width_ratios=(7, 2), height_ratios=(2, 7),
left=0.1, right=0.9, bottom=0.1, top=0.9,
wspace=0.05, hspace=0.05)
ax = fig.add_subplot(gs[1, 0])
ax_histx = fig.add_subplot(gs[0, 0], sharex=ax)
ax_histy = fig.add_subplot(gs[1, 1], sharey=ax)
# use the previously defined function
scatter_hist(x, y, ax, ax_histx, ax_histy)
plt.show()
![scatter hist](../../_images/sphx_glr_scatter_hist_002.png)
References¶
The use of the following functions, methods and classes is shown in this example:
Out:
<function Axes.hist at 0x7fedfebb6a60>
Total running time of the script: ( 0 minutes 1.274 seconds)
Keywords: matplotlib code example, codex, python plot, pyplot Gallery generated by Sphinx-Gallery