Creating a Heatmap in matplotlib with pcolor

First, we can create an image using imshow method, taking a harvest matrix. After that, we can mark those image pixels with some value.


  • Create a list of subjects.

  • Create a list of students.

  • Create a harvest matrix.

  • Create fig and ax variables using subplots method, where default nrows and ncols are 1.

  • Display data as an image, i.e., on a 2D regular raster, with step 1 data.

  • Get or set the current tick locations and labels of the X-axis, with the length of students.

  • Get or set the current tick locations and labels of the Y-axis, with the length of subjects.

  • Set X-axis tick labels of the grid, with students.

  • Set Y-axis tick labels of the grid, with subjects.

  • Set a property on an artist object, with rotation, ha and rotation_mode="anchor".

  • Add text to the plot using the text method.

  • Set a title for the axes using the set_title() method.

  • To show the figure, use method.


import numpy as np
import matplotlib.pyplot as plt

subjects = ["math", "physics", "chemistry", "biology", "english"]
students = ["A", "B", "C", "D", "E"]

harvest = np.array([
   [1, 2, 3, 4, 5],
   [6, 7, 8, 9, 10],
   [11, 12, 13, 14, 15],
   [18, 19, 22, 14, 15],
   [5, 3, 2, 1, 6]
fig, ax = plt.subplots()
im = ax.imshow(harvest)



plt.setp(ax.get_xticklabels(), rotation=45, ha="right", rotation_mode="anchor")

for i in range(len(subjects)):
   for j in range(len(students)):
      text = ax.text(j, i, harvest[i, j], ha="center", va="center", color="w")

ax.set_title("Marks Distribution")