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?

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')


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).

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))


enter image description here

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:

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

import matplotlib
import matplotlib.pyplot as plt

plt.suptitle("Figure Title")

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

import matplotlib.pyplot as plt
cfig,ax = plt.subplots(3,2)