Scaling Data Before PCA

When dealing with data that has features with different scales, it's often important to scale the data first. This is because data that has larger values may sway the data even with relatively little variability.

The combine data frame is loaded for you.

This exercise is part of the course

Linear Algebra for Data Science in R

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Exercise instructions

Use the scale() function to scale the 5th through the 12th columns of combine data. Name this data frame B and show some of the values using head().
Use prcomp() to perform principal component analysis on the data and summarize this analysis using summary().

Hands-on interactive exercise

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

# Scale columns 5-12 of combine
B <- ___(___[, 5:12])

# Print the first 6 rows of the data
___

# Summarize the principal component analysis
summary(____(B))

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