Customizing Seaborn plots with Matplotlib - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to import the seaborn library as sns.

Matplotlib

import [1] as sns

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Aseaborn

Bmatplotlib

Cpandas

Dnumpy

Attempts:

3 left

💡 Hint

Common Mistakes

Importing matplotlib as sns

Importing pandas or numpy instead of seaborn

Seaborn is imported using import seaborn as sns to use its plotting functions.

2fill in blank

medium

Complete the code to create a seaborn scatter plot using the 'tips' dataset.

Matplotlib

sns.scatterplot(data=tips, x='total_bill', y=[1])

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A'size'

B'time'

C'day'

D'tip'

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'size' or 'day' which are not numeric for y-axis

Using 'time' which is categorical

The y-axis should be the 'tip' column to plot tip amounts against total bill.

3fill in blank

hard

Fix the error in the code to set the plot title using Matplotlib.

Matplotlib

plt.[1]('Scatter plot of Total Bill vs Tip')

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Axlabel

Blegend

Ctitle

Dylabel

Attempts:

3 left

💡 Hint

Common Mistakes

Using plt.xlabel or plt.ylabel instead of plt.title

Using plt.legend which is for legends

The function plt.title() sets the title of the plot.

4fill in blank

hard

Fill both blanks to change the x-axis label and y-axis label using Matplotlib.

Matplotlib

plt.xlabel([1])
plt.ylabel([2])

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A'Total Bill ($)'

B'Tip ($)'

C'Total Bill'

D'Tip Amount'

Attempts:

3 left

💡 Hint

Common Mistakes

Using labels without quotes

Mixing up x and y labels

Use plt.xlabel and plt.ylabel to set axis labels with descriptive text.

5fill in blank

hard

Fill all three blanks to customize the plot: set figure size, add grid, and show the plot.

Matplotlib

plt.figure(figsize=[1])
plt.grid([2])
plt.[3]()

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A(8, 6)

BTrue

Cshow

DFalse

Attempts:

3 left

💡 Hint

Common Mistakes

Passing grid as string instead of boolean

Forgetting plt.show() to display plot

Using incorrect figure size format

Use plt.figure(figsize=(8,6)) to set size, plt.grid(True) to add grid, and plt.show() to display the plot.