Race and Ethnic Representation in the Mortgage Data

In this exercise, you'll get the race and ethnic proportions of borrowers in the mortgage data set, adjusted by the total number of borrowers. This will turn the race and ethnicity table you created before into a proportion. Later on, you'll use these values to adjust for the race and ethnic proportions of the US population.

This exercise is part of the course

Scalable Data Processing in R

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Exercise instructions

The reference object mort is available in your workspace.

Create a table from the borrower_race column in the mortgage data (mort) using bigtable().
Where the race is known (first 7 values) find the proportion by dividing by the sum of the counts.

Hands-on interactive exercise

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

# Create a table of borrower_race column
race_table <- ___(mort, ___)

# Rename the elements
names(race_table) <- race_cat[as.numeric(names(race_table))]

# Find the proportion
race_table[___] / ___(race_table[1:7])

Edit and Run Code