Data Science with Python Certification Data Science with Python Matplotlib and Seaborn Visualization 4

Question 1

Which Seaborn function plots the distribution of a single variable alongside a scatter plot of two variables?

Accepted Answer

sns.jointplot()

Answer

sns.jointplot() displays a bivariate scatter (or other plot) in the center with marginal univariate distributions on the axes.

Question 2

In Matplotlib, what does plt.tight_layout() do?

Accepted Answer

Automatically adjusts subplot parameters to prevent overlap

Answer

plt.tight_layout() automatically adjusts subplot spacing so titles, labels, and tick marks don't overlap.

Question 3

Which parameter in sns.scatterplot() controls the size of each point based on a variable?

Accepted Answer

size

Answer

The 'size' parameter maps a numeric variable to the area of each scatter point, adding a fourth data dimension.

Question 4

What is the effect of calling plt.yscale('log') in Matplotlib?

Accepted Answer

Sets the y-axis to a logarithmic scale

Answer

plt.yscale('log') changes the y-axis to a logarithmic scale, useful for data spanning several orders of magnitude.

Question 5

In Seaborn, what does the 'order' parameter do in categorical plots like sns.boxplot()?

Accepted Answer

Controls the left-to-right display order of categories

Answer

The 'order' parameter accepts a list of category names to control the sequence in which they appear on the axis.

Data Science with Python Certification Practice Test