Colormaps (sequential, diverging, qualitative) in Matplotlib - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to import the colormap module from matplotlib.

Matplotlib

from matplotlib import [1]

Drag options to blanks, or click blank then click option'

Acm

Bpyplot

Cstyle

Dcolors

Attempts:

3 left

💡 Hint

Common Mistakes

Importing pyplot instead of cm.

Importing colors which is related but not the colormap module.

The cm module in matplotlib contains colormaps used for coloring plots.

2fill in blank

medium

Complete the code to create a sequential colormap called 'Blues'.

Matplotlib

cmap = cm.[1]

Drag options to blanks, or click blank then click option'

ASet1

BBlues

Ccoolwarm

DPiYG

Attempts:

3 left

💡 Hint

Common Mistakes

Using diverging colormaps like 'coolwarm' for sequential data.

Using qualitative colormaps like 'Set1' here.

Blues is a sequential colormap that goes from light to dark blue.

3fill in blank

hard

Fix the error in the code to get a diverging colormap named 'PiYG'.

Matplotlib

div_cmap = cm.[1]

Drag options to blanks, or click blank then click option'

ABlues

Bviridis

CSet3

DPiYG

Attempts:

3 left

💡 Hint

Common Mistakes

Using sequential colormaps for diverging data.

Using qualitative colormaps like 'Set3' instead.

PiYG is a diverging colormap useful for data with a meaningful midpoint.

4fill in blank

hard

Fill both blanks to create a qualitative colormap named 'Set1' and apply it to a scatter plot.

Matplotlib

scatter = plt.scatter(x, y, c=labels, cmap=cm.[1])
plt.colorbar(scatter, cmap=cm.[2])

Drag options to blanks, or click blank then click option'

ASet1

Bcoolwarm

Dviridis

Attempts:

3 left

💡 Hint

Common Mistakes

Mixing different colormaps for scatter and colorbar.

Using sequential or diverging colormaps for categorical data.

Set1 is a qualitative colormap good for categorical data. It is used both in the scatter and colorbar.

5fill in blank

hard

Fill all three blanks to create a dictionary of colormaps for each type and print the name of the sequential colormap.

Matplotlib

colormaps = {
    'sequential': cm.[1],
    'diverging': cm.[2],
    'qualitative': cm.[3]
}
print(colormaps['sequential'].name)

Drag options to blanks, or click blank then click option'

ABlues

BPiYG

CSet1

Dviridis

Attempts:

3 left

💡 Hint

Common Mistakes

Assigning colormaps to wrong categories.

Using qualitative colormaps as sequential or diverging.

viridis is a popular sequential colormap, PiYG is diverging, and Set1 is qualitative.