matplotlib: plotting histogram plot just above scatter plot

Question

I would like to make beautiful scatter plots with histograms above and right of the scatter plot, as it is possible in seaborn with jointplot:

I am looking for suggestions on how to achieve this. In fact I am having some troubles in installing pandas, and also I do not need the entire seaborn module

To be clear, your question is how to implement `sns.jointplot` in vanilla matplotlib? — wflynny, May 03 '16 at 15:32
more or less. my question is how to place another box above a scatter plot, so I can draw an histogram there — simona, May 03 '16 at 15:34
Check out [`matplotlib.gridspec.GridSpec`](http://matplotlib.org/users/gridspec.html#gridspec-with-varying-cell-sizes), specifically the example at the bottom. Without gridspec, you can follow this [clear example](http://matplotlib.org/examples/pylab_examples/scatter_hist.html) — wflynny, May 03 '16 at 15:36
Further, here's a similar example on stackoverflow: https://stackoverflow.com/questions/20525983/matplotlib-imshow-a-2d-array-with-plots-of-its-marginal-densities — wflynny, May 03 '16 at 15:38

BiGYaN · Answer 1 · 2021-01-18T18:03:33.903

I encountered the same problem today. Additionally I wanted a CDF for the marginals.

Code:

import matplotlib.pyplot as plt
import matplotlib.gridspec as gridspec
import numpy as np

x = np.random.beta(2,5,size=int(1e4))
y = np.random.randn(int(1e4))

fig = plt.figure(figsize=(8,8))
gs = gridspec.GridSpec(3, 3)
ax_main = plt.subplot(gs[1:3, :2])
ax_xDist = plt.subplot(gs[0, :2],sharex=ax_main)
ax_yDist = plt.subplot(gs[1:3, 2],sharey=ax_main)
    
ax_main.scatter(x,y,marker='.')
ax_main.set(xlabel="x data", ylabel="y data")

ax_xDist.hist(x,bins=100,align='mid')
ax_xDist.set(ylabel='count')
ax_xCumDist = ax_xDist.twinx()
ax_xCumDist.hist(x,bins=100,cumulative=True,histtype='step',density=True,color='r',align='mid')
ax_xCumDist.tick_params('y', colors='r')
ax_xCumDist.set_ylabel('cumulative',color='r')

ax_yDist.hist(y,bins=100,orientation='horizontal',align='mid')
ax_yDist.set(xlabel='count')
ax_yCumDist = ax_yDist.twiny()
ax_yCumDist.hist(y,bins=100,cumulative=True,histtype='step',density=True,color='r',align='mid',orientation='horizontal')
ax_yCumDist.tick_params('x', colors='r')
ax_yCumDist.set_xlabel('cumulative',color='r')

plt.show()

Hope it helps the next person searching for scatter-plot with marginal distribution.

Your pic is beautiful, +1, but the code returns an error: `AttributeError: 'Polygon' object has no property 'normed'`. Please correct your solution or tell me what I'm doing wrong. — Leo, Apr 21 '20 at 21:15

tmdavison · Accepted Answer · 2016-05-03T16:55:04.097

13

Here's an example of how to do it, using gridspec.GridSpec:

import matplotlib.pyplot as plt
from matplotlib.gridspec import GridSpec
import numpy as np

x = np.random.rand(50)
y = np.random.rand(50)

fig = plt.figure()

gs = GridSpec(4,4)

ax_joint = fig.add_subplot(gs[1:4,0:3])
ax_marg_x = fig.add_subplot(gs[0,0:3])
ax_marg_y = fig.add_subplot(gs[1:4,3])

ax_joint.scatter(x,y)
ax_marg_x.hist(x)
ax_marg_y.hist(y,orientation="horizontal")

# Turn off tick labels on marginals
plt.setp(ax_marg_x.get_xticklabels(), visible=False)
plt.setp(ax_marg_y.get_yticklabels(), visible=False)

# Set labels on joint
ax_joint.set_xlabel('Joint x label')
ax_joint.set_ylabel('Joint y label')

# Set labels on marginals
ax_marg_y.set_xlabel('Marginal x label')
ax_marg_x.set_ylabel('Marginal y label')
plt.show()

edited May 03 '16 at 16:55

answered May 03 '16 at 15:46

tmdavison

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nice, but how do I remove ticks only from the histograms (without suppressing axes), and how do I add labels selectively? – simona May 03 '16 at 16:33
1

See here http://stackoverflow.com/questions/4209467/matplotlib-share-x-axis-but-dont-show-x-axis-tick-labels-for-both-just-one – tmdavison May 03 '16 at 16:37
now my labels appear on the plot [0,0] instead than [1,0]. I want ylabel on plot [0,0], xlabel on plot[1,1], and both labels on plot [1,0] – simona May 03 '16 at 16:51

Carlos Pinzón · Answer 3 · 2022-01-07T02:59:15.330

I strongly recommend to flip the right histogram by adding these 3 lines of code to the current best answer before plt.show() :

ax_yDist.invert_xaxis()
ax_yDist.yaxis.tick_right()
ax_yCumDist.invert_xaxis()

The advantage is that any person who is visualizing it can compare easily the two histograms just by moving and rotating clockwise the right histogram on their mind.

On contrast, in the plot of the question and in all other answers, if you want to compare the two histograms, your first reaction is to rotate the right histogram counterclockwise, which leads to wrong conclusions because the y axis gets inverted. Indeed, the right CDF of the current best answer looks decreasing at first sight:

matplotlib: plotting histogram plot just above scatter plot

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