How to plot Heatmap in Python

To plot heatmap(heat map) in Python we can use different libraries like:

seaborn
matplotlib

or combination or them.

Steps

Import libraries - matplotlib, seaborn
Select data to be plot
- create pivot table
Plot the heat map
- select heat map type
- select color scheme

Note: If you like to plot Pandas DataFrame as a heatmap you can check:
How to Display Pandas DataFrame As a Heatmap

Example 1 - Heatmap

Data

Data will be created by np.random.rand(10, 12). It is arrays of random numbers:

array([[0.5488135 , 0.71518937, 0.60276338, 0.54488318, 0.4236548 ,
        0.64589411, 0.43758721, 0.891773  , 0.96366276, 0.38344152,
        0.79172504, 0.52889492],
       [0.56804456, 0.92559664, 0.07103606, 0.0871293 , 0.0202184 ,
        0.83261985, 0.77815675, 0.87001215, 0.97861834, 0.79915856,
        0.46147936, 0.78052918],

Code

So to plot multiple plots with matplotlib we need to provide the plt.figure()

import numpy as np; np.random.seed(0)
import matplotlib.pyplot as plt
import seaborn as sns; sns.set_theme()

uniform_data = np.random.rand(10, 12)

ax = sns.heatmap(uniform_data)

Output

Example 2 - Python heatmap colors

Data

For this example we will use data coming with the seaborn library:

year	1949	1950	1951	1952	1953	1954	1955	1956	1957	1958	1959	1960
month
Jan	112	115	145	171	196	204	242	284	315	340	360	417
Feb	118	126	150	180	196	188	233	277	301	318	342	391
Mar	132	141	178	193	236	235	267	317	356	362	406	419
Apr	129	135	163	181	235	227	269	313	348	348	396	461
May	121	125	172	183	229	234	270	318	355	363	420	472

Code

First we load the dataset and then do a pivot table on columns:

month - index
year - columns
passengers - values

To change colors of heatmap in Python we can use parameter: cmap="YlGnBu"

flights = sns.load_dataset("flights")
flights = flights.pivot("month", "year", "passengers")
ax = sns.heatmap(flights, cmap="YlGnBu")

If you like to find more Python and matplotlib colors please check: Full List of Named Colors in Pandas and Python

Output

Example 3 - Correlogram

Data

Again we are using random numbers:

array([[ 1.        ,  0.08615821, -0.02380759,  0.01254937, -0.09259778,
        -0.06358862, -0.01470216, -0.07846244, -0.02754994,  0.00490301],
       [ 0.08615821,  1.        ,  0.18129382, -0.13650656,  0.05585866,
         0.02908082, -0.10838342,  0.04390444, -0.03423537,  0.02155898],
       [-0.02380759,  0.18129382,  1.        , -0.0554918 ,  0.01511297,
         0.09564635, -0.01457802,  0.02515053,  0.13420019, -0.1104883 ]])

Code

To plot correlogram in Python we will calculate the correlation coefficients by - np.corrcoef()

corr = np.corrcoef(np.random.randn(10, 200))
mask = np.zeros_like(corr)
mask[np.triu_indices_from(mask)] = True
with sns.axes_style("white"):
    f, ax = plt.subplots(figsize=(7, 5))
    ax = sns.heatmap(corr, mask=mask, vmax=.3, square=True)

Output

More examples can be found on the official page: seaborn.heatmap