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 is a part of the course
“Analyzing US Census Data in Python”
Exercise instructions
- Use the
copymethod to create a deep copy of only thehispanic_racescolumns instates - As you iterate the races in the
hispanic_raceslist, calculate the percentage of Hispanics identifying as each race as100times the count of the currentracedivided by the total number of Hispanics. - Print the
headof 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(____)
This exercise is part of the course
Analyzing US Census Data in Python
Learn to use the Census API to work with demographic and socioeconomic data.
Start exploring Census data products with the Decennial Census. Use the Census API and the requests package to retrieve data, load into pandas data frames, and conduct exploratory visualization in seaborn. Learn about important Census geographies, including states, counties, and tracts.
Exercise 1: Census Subject TablesExercise 2: Aggregate and Calculate ProportionsExercise 3: Calculate ProportionsExercise 4: Identify Extreme ValuesExercise 5: Using the Census APIExercise 6: The Basic API RequestExercise 7: The API Response and PandasExercise 8: API to Visualization: Group QuartersExercise 9: Census GeographiesExercise 10: Specific PlacesExercise 11: Congressional Districts by StateExercise 12: Zip Code Tabulation AreasWhat is DataCamp?
Learn the data skills you need online at your own pace—from non-coding essentials to data science and machine learning.