Heatmap with plt.pcolormesh in Matplotlib - Practice Problems & Coding Challenges

Challenge - 5 Problems

❓ Predict Output

intermediate

Output of plt.pcolormesh with given data

What will be the shape of the array used to create the heatmap with plt.pcolormesh in this code?

Matplotlib

import numpy as np
import matplotlib.pyplot as plt

Z = np.array([[1, 2, 3], [4, 5, 6]])
plt.pcolormesh(Z)
plt.close()  # Close plot to avoid display
print(Z.shape)

A (2, 2)

B (3, 2)

C (3, 3)

D (2, 3)

💡 Hint

Remember that the shape of the array Z is rows by columns.

The array Z has 2 rows and 3 columns, so its shape is (2, 3). This shape is used by plt.pcolormesh to create the heatmap grid.

❓ data_output

intermediate

Data values shown by plt.pcolormesh

Given this code, what is the color value at position (1, 1) in the heatmap data array?

Matplotlib

import numpy as np
Z = np.array([[10, 20, 30], [40, 50, 60]])
value = Z[1, 1]
print(value)

A 50

B 40

C 20

D 60

💡 Hint

Remember that indexing starts at 0 for rows and columns.

Z[1, 1] accesses the second row and second column, which is 50.

❓ visualization

advanced

Effect of shading='auto' in plt.pcolormesh

What visual difference does setting shading='auto' make in plt.pcolormesh when plotting a 2x2 array?

Matplotlib

import numpy as np
import matplotlib.pyplot as plt

Z = np.array([[1, 2], [3, 4]])
plt.figure(figsize=(4, 3))
plt.pcolormesh(Z, shading='auto')
plt.close()

A The heatmap cells have gaps between them.

B The heatmap cells align exactly with the data points without gaps.

C The heatmap uses a different color map automatically.

D The heatmap cells are plotted as circles instead of squares.

💡 Hint

shading='auto' adjusts the grid to match the data shape.

Using shading='auto' makes the cells align perfectly with the data points, avoiding gaps or overlaps.

🔧 Debug

advanced

Identify the error in plt.pcolormesh usage

What error will this code raise when run?

Matplotlib

import numpy as np
import matplotlib.pyplot as plt

Z = np.array([[1, 2], [3, 4]])
plt.pcolormesh(Z, cmap='viridis', shading='invalid')
plt.close()

A ValueError: shading must be 'flat', 'gouraud', or 'auto'

B TypeError: cmap must be a Colormap instance

C SyntaxError: invalid syntax in plt.pcolormesh call

D No error, plot displays normally

💡 Hint

Check the allowed values for the shading parameter.

The shading parameter only accepts 'flat', 'gouraud', or 'auto'. 'invalid' causes a ValueError.

🚀 Application

expert

Creating a heatmap with custom X and Y coordinates

Which option correctly creates a heatmap with plt.pcolormesh using custom X and Y coordinates for a 2x2 data array?

Matplotlib

import numpy as np
import matplotlib.pyplot as plt

Z = np.array([[1, 2], [3, 4]])
X = np.array([0, 1, 2])
Y = np.array([0, 1, 2])
# Fill in the correct plt.pcolormesh call below

A

plt.pcolormesh(Z, X, Y)
plt.close()

B

plt.pcolormesh(X, Y, Z.T)
plt.close()

C

plt.pcolormesh(X, Y, Z)
plt.close()

D

plt.pcolormesh(Z.T, X, Y)
plt.close()

💡 Hint

X and Y must be 1D arrays with length one more than Z's dimensions.

X and Y define the grid edges and must have length one more than Z's shape. Z is passed as is without transpose.