Data Science with Python Certification Data Science with Python Matplotlib and Seaborn Visualization 3

Question 1

In Matplotlib, how do you set the figure size when creating a new figure?

Accepted Answer

plt.figure(figsize=(10,6))

Answer

The figsize parameter accepts a tuple (width, height) in inches to set the figure dimensions.

Question 2

Which Seaborn function is best suited for visualizing the correlation matrix of a DataFrame?

Accepted Answer

sns.heatmap()

Answer

sns.heatmap(df.corr()) displays correlation values as color-coded cells, making it ideal for correlation matrices.

Question 3

What does the 'alpha' parameter control in Matplotlib plots?

Accepted Answer

Transparency/opacity

Answer

The alpha parameter sets the transparency level from 0 (fully transparent) to 1 (fully opaque).

Question 4

Which Seaborn function creates a bar chart that shows the mean (and confidence interval) of a numeric variable for each category?

Accepted Answer

sns.barplot()

Answer

sns.barplot() shows point estimates (default: mean) with confidence intervals as error bars for each category.

Question 5

In Matplotlib, which command adds a legend to the current axes using labels provided in plot() calls?

Accepted Answer

plt.legend()

Answer

plt.legend() automatically creates a legend using labels assigned via the 'label' parameter in plot functions.

Data Science with Python Certification Practice Test