HOWTO · Matplotlib

How to Plot a 2D Heatmap With Matplotlib

We can plot a 2D heatmap using imshow() function,seaborn library and pcolormesh() function.

By Suraj JoshiPublished 2020-04-28Updated 2024-02-02

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To plot a 2D heatmap, we can use any of the following methods:

imshow() function with parameters interpolation='nearest' and cmap='hot'
Seaborn library
pcolormesh() function

`imshow()` Function to Plot 2D Heatmap

Syntax for we can use the imshow function:

matplotlib.pyplot.imshow(X,
                         cmap=None,
                         norm=None,
                         aspect=None,
                         interpolation=None,
                         alpha=None,
                         vmin=None,
                         vmax=None,
                         origin=None,
                         extent=None,
                         shape= < deprecated parameter > ,
                         filternorm=1,
                         filterrad=4.0,
                         imlim= < deprecated parameter > ,
                         resample=None,
                         url=None,
                         *,
                         data=None,
                         **kwargs)

Example Codes:

import numpy as np
import matplotlib.pyplot as plt

data = np.random.random((8, 8))
plt.imshow(data, cmap="cool", interpolation="nearest")
plt.show()

2D histogram with imshow function

cmap is color map and we can choose another built-in colormaps too from here.

interpolation is the interpolation method that could be nearest, bilinear, hamming, etc.

2D Heatmap With `Seaborn` Library

The Seaborn library is built on top of Matplotlib. We could use seaborn.heatmap() function to create 2D heatmap.

import numpy as np
import seaborn as sns
import matplotlib.pylab as plt

data = np.random.rand(8, 8)
ax = sns.heatmap(data, linewidth=0.3)
plt.show()

2D histogram with seaborn

Seaborn also plots a gradient at the side of the heatmap.

`pcolormesh()` Function

Another way to plot 2D heatmap is using pcolormesh() function ,which creates a pseudo-color plot with a non-regular rectangular grid. It is a faster alternative to pcolor() function.

import numpy as np
import matplotlib.pyplot as plt

b, a = np.meshgrid(np.linspace(0, 5, 130), np.linspace(0, 5, 130))

c = (a ** 2 + b ** 2) * np.exp(-(a ** 2) - b ** 2)
c = c[:-1, :-1]
l_a = a.min()
r_a = a.max()
l_b = b.min()
r_b = b.max()
l_c, r_c = -np.abs(c).max(), np.abs(c).max()

figure, axes = plt.subplots()

c = axes.pcolormesh(a, b, c, cmap="copper", vmin=l_c, vmax=r_c)
axes.set_title("Heatmap")
axes.axis([l_a, r_a, l_b, r_b])
figure.colorbar(c)

plt.show()