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
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()