Colorblind-friendly palettes in Matplotlib - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to import the matplotlib library with the common alias.

Matplotlib

import [1] as plt

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

Amatplotlib.pyplot

Bmatplotlib

Cpyplot

Dmpl

Attempts:

3 left

💡 Hint

Common Mistakes

Importing 'matplotlib' as plt instead of 'matplotlib.pyplot'

Using an uncommon alias like 'mpl'

We import matplotlib.pyplot as plt to access plotting functions.

2fill in blank

medium

Complete the code to create a colorblind-friendly palette using seaborn.

Matplotlib

palette = sns.color_palette("[1]")

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

Acolorblind

Bdeep

Cpastel

Dbright

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'deep' or 'bright' palettes which are not optimized for colorblindness

Misspelling the palette name

The 'colorblind' palette in seaborn is designed to be friendly for colorblind viewers.

3fill in blank

hard

Fix the error in the code to apply a colorblind-friendly palette to a bar plot.

Matplotlib

sns.barplot(x='category', y='value', data=df, palette=[1])

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

A"colorblind"

Bpalette.colorblind

Ccolorblind

Dsns.color_palette("colorblind")

Attempts:

3 left

💡 Hint

Common Mistakes

Passing the palette name without quotes (syntax error)

Using an undefined variable 'colorblind'

The palette argument accepts a list of colors, which sns.color_palette("colorblind") returns. (Note: "colorblind" string also works.)

4fill in blank

hard

Fill both blanks to create a dictionary of colors from the colorblind palette for categories 'A' and 'B'.

Matplotlib

colors = {'A': palette[[1]], 'B': palette[[2]]}

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

A0

B1

C2

D3

Attempts:

3 left

💡 Hint

Common Mistakes

Using indexes starting at 1 instead of 0

Using the same index for both categories

The first two colors in the colorblind palette are at indexes 0 and 1.

5fill in blank

hard

Fill all three blanks to create a scatter plot with colorblind-friendly colors and a legend.

Matplotlib

for cat, color in colors.items():
    subset = df[df['category'] == [1]]
    plt.scatter(subset['x'], subset['y'], color=[2], label=[3])
plt.legend()

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

Acat

Bcolor

Dsubset

Attempts:

3 left

💡 Hint

Common Mistakes

Using wrong variable names for filtering or labeling

Mixing up color and category variables

We filter by category 'cat', use the color variable for color, and label points by 'cat'.

Practice

1. What is the main purpose of using a colorblind-friendly palette in matplotlib charts?

easy

A. To reduce the file size of the chart image

B. To add more colors to the chart for decoration

C. To make charts easier to read for people with color vision differences

D. To speed up the chart rendering process

Solution

1. Step 1: Understand colorblind-friendly palettes

   These palettes are designed to help people with color vision differences distinguish chart elements clearly.

2. Step 2: Identify the main goal

   The goal is to improve chart readability and accessibility for everyone, especially those with colorblindness.

3. Final Answer:

   To make charts easier to read for people with color vision differences -> Option C

4. Quick Check:

   Accessibility = C [OK]

Hint: Think about accessibility and readability for all viewers [OK]

Common Mistakes:

• Confusing decoration with accessibility
• Thinking it affects file size or speed
• Assuming it adds random colors

2. Which of the following is the correct way to set a colorblind-friendly palette using seaborn with matplotlib?

easy

A. sns.set_palette('colorblind')

B. plt.color_palette('colorblind')

C. sns.colorblind_palette()

D. plt.set_palette('colorblind')

Solution

1. Step 1: Recall seaborn palette setting syntax

   Seaborn uses sns.set_palette() to set the color palette globally.

2. Step 2: Identify the correct palette name

   The palette name for colorblind-friendly colors is exactly 'colorblind'.

3. Final Answer:

   sns.set_palette('colorblind') -> Option A

4. Quick Check:

   Seaborn set_palette with 'colorblind' = B [OK]

Hint: Use sns.set_palette('colorblind') to apply palette [OK]

Common Mistakes:

• Using plt instead of sns for palette setting
• Calling a non-existent function sns.colorblind_palette()
• Using wrong function names like plt.set_palette

3. What will be the output of the following code snippet?

import matplotlib.pyplot as plt
import seaborn as sns
sns.set_palette('colorblind')
colors = sns.color_palette()
print(colors[0])

medium

A. (0.0, 0.0, 0.0)

B. (0.0, 0.45, 0.70)

C. (1.0, 0.0, 0.0)

D. Error: palette not found

Solution

1. Step 1: Understand sns.set_palette and sns.color_palette

   Setting 'colorblind' palette changes the default colors to a known colorblind-friendly set. Calling sns.color_palette() returns the current palette colors.

2. Step 2: Identify the first color in 'colorblind' palette

   The first color in seaborn's 'colorblind' palette is approximately (0.0, 0.45, 0.70), a blue shade.

3. Final Answer:

   (0.0, 0.45, 0.70) -> Option B

4. Quick Check:

   First color in 'colorblind' palette = A [OK]

Hint: Remember 'colorblind' palette starts with blue (0.0, 0.45, 0.7) [OK]

Common Mistakes:

• Expecting black or red as first color
• Confusing palette names causing error
• Not calling sns.set_palette before sns.color_palette

4. Identify the error in this code that tries to apply a colorblind-friendly palette:

import seaborn as sns
import matplotlib.pyplot as plt
sns.set_palette('colorblind')
plt.plot([1, 2, 3], [4, 5, 6], color='colorblind')
plt.show()

medium

A. Using 'colorblind' as a single color in plt.plot is invalid

B. sns.set_palette should be called after plt.plot

C. Missing import for matplotlib.colors

D. plt.show() is missing parentheses

Solution

1. Step 1: Analyze plt.plot color argument

   The color parameter expects a single color value, not a palette name.

2. Step 2: Understand how palettes are applied

   Palettes set default colors for multiple plots, but you cannot use the palette name as a color string directly.

3. Final Answer:

   Using 'colorblind' as a single color in plt.plot is invalid -> Option A

4. Quick Check:

   Palette name ≠ single color string [OK]

Hint: Palette sets defaults; don't use palette name as color string [OK]

Common Mistakes:

• Thinking palette name can be used as a color string
• Wrong order of sns.set_palette and plotting
• Forgetting plt.show() parentheses

5. You want to create a bar chart with 5 bars using matplotlib and ensure it is colorblind-friendly. Which code snippet correctly applies a colorblind-friendly palette and plots the bars with different colors?

hard

A. import seaborn as sns
import matplotlib.pyplot as plt
plt.bar(range(5), [1,2,3,4,5])
sns.set_palette('colorblind')
plt.show()

B. import matplotlib.pyplot as plt
plt.bar(range(5), [1,2,3,4,5], color='colorblind')
plt.show()

C. import seaborn as sns
import matplotlib.pyplot as plt
colors = sns.set_palette('colorblind')
plt.bar(range(5), [1,2,3,4,5], color=colors)
plt.show()

D. import seaborn as sns
import matplotlib.pyplot as plt
sns.set_palette('colorblind')
colors = sns.color_palette()
plt.bar(range(5), [1,2,3,4,5], color=colors)
plt.show()

Solution

1. Step 1: Apply the colorblind palette correctly

   Use sns.set_palette('colorblind') to set the palette globally, then get the colors with sns.color_palette().

2. Step 2: Use the colors list in plt.bar

   Pass the list of colors to the color parameter to color each bar differently.

3. Final Answer:

   The code that sets the palette, retrieves the colors list, and passes it to plt.bar color parameter -> Option D

4. Quick Check:

   Set palette + use colors list = A [OK]

Hint: Set palette, get colors list, pass to color parameter [OK]

Common Mistakes:

• Passing palette name as color string
• Assigning sns.set_palette() return to colors
• Not passing colors list to bar plot