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Calculate Proportions

Nationally, 55% of Hispanics identify as White and 35% identify as "Some Other Race". (You can run Line 2 in the code window to confirm this.) But there is substantial state-to-state variation, which we will now investigate. As a reminder, we will express proportions as percentages throughout this course.

pandas has been imported, the DataFrame states is loaded with population counts by race and Hispanic origin. A list, hispanic_races, has names of columns with Hispanics by race data, and is shown in the console.

This exercise is part of the course

Analyzing US Census Data in Python

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Exercise instructions

  • Use the copy method to create a deep copy of only the hispanic_races columns in states
  • As you iterate the races in the hispanic_races list, calculate the percentage of Hispanics identifying as each race as 100 times the count of the current race divided by the total number of Hispanics.
  • Print the head of the resulting DataFrame.

Hands-on interactive exercise

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

# What percentage of Hispanics identify as each race?
print(100 * states[hispanic_races].sum() / states["hispanic"].sum())

# Create a deep copy of only the Hispanic race columns
states_hr = ____.copy()

# Calculate percentages for all columns in the date frame
for race in hispanic_races:
    states_hr[race] = ____ * ____ / states["hispanic"]

# View the result
print(____)
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