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Visually detecting redundant features

Data visualization is a crucial step in any data exploration. Let's use Seaborn to explore some samples of the US Army ANSUR body measurement dataset.

Two data samples have been pre-loaded as ansur_df_1 and ansur_df_2.

Seaborn has been imported as sns.

This exercise is part of the course

Dimensionality Reduction in Python

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Hands-on interactive exercise

Have a go at this exercise by completing this sample code.

# Create a pairplot and color the points using the 'Gender' feature
sns.____(____, ____=_____, diag_kind='hist')

# Show the plot
plt.show()
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