Which Seaborn function is used to create a matrix of scatterplots for multiple variables, while also showing the distribution of each variable along the diagonal?

Question

BlackTom AI · Accepted Answer

The question asks which Seaborn function creates a matrix of scatterplots for multiple variables and displays the distribution of each variable along the diagonal.
Option A: seaborn.scatterplot() creates a single scatter plot between two variables, not a matrix of plots or diagonal distributions. This misses the multi-variable matrix aspect.
Option B: seaborn.jointplot() combines a bivariate plot with marginal distributions but is limited to two variables at a time and does not produce a full grid of all variable pairs with diagonals for every variable.
Option C: seaborn.pairplot() is designed to generate a grid (matrix) of scatterplots for all pairs of variables in a dataset, and it places distributions (histograms or KDEs) along the diagonal for each variable. This directly matches the described functionality.
Option D: seaborn.heatmap() visualizes matrix-valued data as colored cells and is not used for scatterplots or for displaying variable distributions along a diagonal. It serves a different purpose altogether.
Overall, the feature set described—multi-variable pairwise scatter plots with diagonal distributions—aligns with the purpose of pairplot. The other options do not provide the same matrix-based multi-variable comparison with diagonal distributions.

ISBA2401 - Data Analytics with Python (MW 05:45 PM, MW 7:35 PM, TTh 7:35PM) Quiz 4- Requires Respondus LockDown Browser

Which Seaborn function is used to create a matrix of scatterplots for multiple variables, while also showing the distribution of each variable along the diagonal?

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