How can I make a blank subplot in matplotlib?
Asked Answered
B

6

130

I am making a group of subplot (say, 3 x 2) in matplotlib, but I have fewer than 6 datasets. How can I make the remaining subplot blank?

The arrangement looks like this:

+----+----+
| 0,0| 0,1|
+----+----+
| 1,0| 1,1|
+----+----+
| 2,0| 2,1|
+----+----+

This may go on for several pages, but on the final page, there are, for example, 5 datasets to the 2,1 box will be empty. However, I have declared the figure as:

cfig,ax = plt.subplots(3,2)

So in the space for subplot 2,1 there is a default set of axes with ticks and labels. How can I programatically render that space blank and devoid of axes?

Berkey answered 5/4, 2012 at 20:22 Comment(0)
F
225

You could always hide the axes which you do not need. For example, the following code turns off the 6th axes completely:

import matplotlib.pyplot as plt

hf, ha = plt.subplots(3,2)
ha[-1, -1].axis('off')

plt.show()

and results in the following figure:

An image of a 3x2 grid of graphs, with no graph rendered in the bottom right cell

Alternatively, see the accepted answer to the question Hiding axis text in matplotlib plots for a way of keeping the axes but hiding all the axes decorations (e.g. the tick marks and labels).

Flyback answered 5/4, 2012 at 21:3 Comment(7)
Thanks - that's actually even closer to my original question. I already accepted the other answer and adapted my code to use it, but both approaches are great.Berkey
Cool, that's indeed nice as there's less add_subplot() clutter.Philately
This is marvependous!Pavlish
This does show no plot and one could say that this is a blank plot. I was looking for a plot which has no data, to explicitly show that there is no data. Any easy modification of this answer, which does that?Curve
@Zelphir I'm not sure what you're after: the other five plots are empty graphs with no data, so I'm not sure what extra you're asking for. Also, this is a new question. In the future, please ask this as a new question rather than commenting on a old answer.Flyback
@Chris, that last blank space is perfect for adding a legend. Do you know any way to set the legend there?Coralloid
The answer is great but does not work for GeoAxes. Readers are also recommended using axes[-1,-1].set_visible(False) to meet the goal.Millman
C
29

A much improved subplot interface has been added to matplotlib since this question was first asked. Here you can create exactly the subplots you need without hiding the extras. In addition, the subplots can span additional rows or columns.

import pylab as plt

ax1 = plt.subplot2grid((3,2),(0, 0))
ax2 = plt.subplot2grid((3,2),(0, 1))
ax3 = plt.subplot2grid((3,2),(1, 0))
ax4 = plt.subplot2grid((3,2),(1, 1))
ax5 = plt.subplot2grid((3,2),(2, 0))

plt.show()

enter image description here

Colloquium answered 15/1, 2013 at 16:12 Comment(3)
Wow - that's a nice improvement. So much simpler! Thanks @Hooked!Berkey
@Hooked, that last blank space is perfect for adding a legend. Do you know any way to set the legend there?Coralloid
@Coralloid sure there are ways of doing this -- but this would be best posed as a new question, you can even link this answer in your question (welcome to StackOverflow btw!)Colloquium
R
17

It's also possible to hide a subplot using the Axes.set_visible() method.

import matplotlib.pyplot as plt
import pandas as pd

fig = plt.figure()
data = pd.read_csv('sampledata.csv')

for i in range(0,6):
    ax = fig.add_subplot(3,2,i+1)
    ax.plot(range(1,6), data[i])
    if i == 5:
        ax.set_visible(False)
Rigamarole answered 10/4, 2017 at 20:19 Comment(1)
Your answer is great for both original Axes and extended GeoAxes!Millman
S
3

With newer versions of matplotlib (since 3.4.0), you can use an array of strings to design your subplots pattern (rows and columns) and use it to create the figure by calling matplotlib.pyplot.subplot_mosaic.

Instead of cfig, ax = plt.subplots(3,2), use cfig, axs = plt.subplot_mosaic(mosaic) and define mosaic this way:

mosaic = [['a', 'b'],
          ['c', 'd'],
          ['e', '.']]

In this pattern, blank subplots are denoted by '.' (by default, this can be parametrized in the call). You do not need to delete blank subplots, as they are not even created.

To select an axis for plotting, just use axs[id] where id is the string used to identify the subplot in the mosaic array.

Example:

mosaic = [['b', 'a'], ['.', 'au']]
kw = dict(layout='constrained')
fig, axs = plt.subplot_mosaic(mosaic, **kw)

ax = axs['b']
ax.grid(axis='y')
ax.bar(n, d)

ax = axs['a']
ax.grid(axis='y')
ax.bar(n, prior)

[...]

enter image description here

With subplot_mosaic, not only you can introduce blank subplots, but you can also merge 'cells' in order to create subplots on multiple rows and/or columns, just by crafting the required mosaic array, the rest of the code is unchanged. In addtion mosaic doesn't need to be an array, it can also be a multiline string. E.g. from Complex and semantic figure composition, using:

"""
A.C
BBB
.D.
"""

results in:

enter image description here

Stearic answered 18/7, 2023 at 7:19 Comment(1)
So much more powerful! Thanks for the update @StearicBerkey
P
2

Would it be an option to create the subplots when you need them?

import matplotlib
matplotlib.use("pdf")
import matplotlib.pyplot as plt

plt.figure()
plt.gcf().add_subplot(421)
plt.fill([0,0,1,1],[0,1,1,0])
plt.gcf().add_subplot(422)
plt.fill([0,0,1,1],[0,1,1,0])
plt.gcf().add_subplot(423)
plt.fill([0,0,1,1],[0,1,1,0])
plt.suptitle("Figure Title")
plt.gcf().subplots_adjust(hspace=0.5,wspace=0.5)
plt.savefig("outfig")
Philately answered 5/4, 2012 at 20:42 Comment(2)
I don't think so because there are other formatting things I need to do that I didn't include in the original question for brevity. One of these is plt.subplots_adjust(wspace=0,hspace=0). I'm not sure that would work after the fact.Berkey
@Berkey : you can do subplots_adjust() using this approach. See my edit.Philately
B
1

To delete the the plot positioned at (2,1) you may use

import matplotlib.pyplot as plt
cfig,ax = plt.subplots(3,2)
cfig.delaxes(ax.flatten()[5])
Blomquist answered 27/8, 2021 at 22:14 Comment(0)

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