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Tutorial Exercises MCQs Interview Q & A Tests
python-for-ai / Seaborn Basics
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Direction: Choose the correct option

Q1.

What is Seaborn primarily used for?
A. Data cleaning
B. Machine learning
C. Statistical data visualization
D. Array operations
Direction: Choose the correct option

Q2.

How do you import Seaborn with the common alias?
A. import seaborn
B. import seaborn as sb
C. import sns
D. import seaborn as sns
Direction: Choose the correct option

Q3.

Which Seaborn function creates a simple line plot?
A. sns.lmplot()
B. sns.barplot()
C. sns.plot()
D. sns.lineplot()
Direction: Choose the correct option

Q4.

What does `sns.histplot()` do?
A. Plots boxplot
B. Plots bar chart
C. Plots scatter
D. Plots histogram with KDE option
Direction: Choose the correct option

Q5.

How do you create a scatter plot with Seaborn?
A. sns.relplot(kind='scatter')
B. sns.scatter(x, y)
C. Both A and C
D. sns.scatterplot(x, y, data=df)
Direction: Choose the correct option

Q6.

What is the purpose of `sns.pairplot()`?
A. Plots pairwise correlations
B. Plots histograms
C. Creates matrix of scatter plots for multiple variables
D. Both A and B
Direction: Choose the correct option

Q7.

Which Seaborn function is used for categorical scatter plots with jitter?
A. sns.catplot(kind='strip')
B. sns.stripplot()
C. Both A and B
D. sns.swarmplot()
Direction: Choose the correct option

Q8.

How do you set the overall style of Seaborn plots?
A. sns.style('ggplot')
B. Both A and B
C. sns.set_style('whitegrid')
D. sns.set_theme(style='darkgrid')
Direction: Choose the correct option

Q9.

What does `sns.jointplot()` produce?
A. Heatmap
B. Scatter plot with marginal histograms
C. Both A and B
D. Joint distribution
Direction: Choose the correct option

Q10.

How do you create a heatmap of correlation matrix?
A. sns.corrplot(df)
B. sns.correlation_heatmap(df)
C. sns.heatmap(df.corr())
D. sns.heatmap(df)