Aggregating Techniques
📚 Schema reference · towns & counties 3 tables
- fips
- name
- state
- county_id
- county
- state
- fips_short
- county_seat
- county_seat_town_id
- year_established
- origin
- etymology
- population_2022
- land_area_sq_mi
- town_id
- town
- state
- primary_county
- secondary_county
- tertiary_county
- primary_county_id
- secondary_county_id
- tertiary_county_id
- population_2020_census
- population_2010_census
- land_area_sq_mi
Numerical summaries
Aggregate functions (AVG, SUM, MIN, MAX, COUNT) collapse multiple rows into summary statistics.
Aggregating 1: What’s the average town size in each state?
Scenario: Compare typical town sizes between Oregon and Washington. For each state, report the average town population rounded to a whole number as avg_population.
Aggregating 2: What’s the total urban population by state?
Scenario: How much of each state’s population lives in incorporated towns? For each state, report the summed town population as total_town_population.
Aggregating 3: Find the smallest incorporated town
Scenario: A journalist wants to profile the smallest town in the Pacific Northwest. Show the town with its state and population_2020_census.
Aggregating 4: Find the largest city
Scenario: Identify the region’s largest metropolitan center. Show the town with its state and population_2020_census.
Aggregating 5: Summary statistics for county land areas
Scenario: Get a complete statistical overview of county sizes: the count of counties as num_counties, the smallest and largest land areas as smallest_area and largest_area, the average rounded to a whole number as avg_size, and the sum as total_area.
Categorical summaries
MIN and MAX aren’t just for measurements — they also pick out the extremes of columns like year_established (and they even work on text, returning alphabetically first/last values).
Aggregating 6: When were the earliest and most recent counties established?
Scenario: Historical research on regional development. Report the earliest establishment year as earliest_year and the most recent as newest_year.
Aggregating 7: Find the actual earliest and newest counties
Scenario: Get the county names, not just the years. Show each county with its state and year_established.
Rounding summaries
ROUND helps create cleaner, more readable output for reports and presentations.
Aggregating 8: Calculate and round population density
Scenario: Create a readable density report (people per square mile). Show each town with its state, population_2020_census, land_area_sq_mi, and the density rounded to 1 decimal as people_per_sq_mile.
Aggregating 9: Round to whole numbers for simpler reporting
Scenario: Executive summaries often need whole numbers. For each state, report the average town population as avg_town_pop and the average town land area as avg_town_area, both rounded to whole numbers.