Airports per state, as a script that runs again

PythonintermediateSpatial analysis

A federal infrastructure office publishes an annual table of airports per state from a global registry, and last year's was produced by hand in a desktop tool. The analyst has left. This year the office wants a script: the registry drops in, the same code runs, the same table comes out — including the states with nothing to count, which the desktop version quietly omitted.

Write a script that produces a per-state airport table.

The datasets are mounted where the script runs:

/data/states.geojson — the 50 states and DC
/data/airports.geojson — 893 airports worldwide; only some are in a state

geopandas, shapely, pyproj, pandas and numpy are available. Assign the finished table to a variable named `result`: a GeoDataFrame with one row per state, carrying the state polygon and

postal — the state
airports — airports inside the state, all types
major_airports — those whose type contains major

Assign airports to states by geometry. Airports outside every state — most of the file — are simply not counted. Do not write a file — the runner reads result.

The input files

/data/states.geojson — EPSG:4326; the geometry is in geometry (Polygon / MultiPolygon).

column	type	meaning
`state_id`	string	Natural Earth adm1 code
`name`	string	State name
`postal`	string	Two-letter postal abbreviation
`region`	string	Census region: Northeast \| Midwest \| South \| West
`type`	string	State \| Federal District

/data/airports.geojson — EPSG:4326; the geometry is in geometry (Point).

column	type	meaning
`airport_id`	string	AP- plus the Natural Earth id
`name`	string	Airport name
`iata_code`	string	Three-letter IATA code; null for a few
`gps_code`	string	Four-letter ICAO code
`type`	string	major \| mid \| small \| military \| spaceport, and combinations such as 'major and military'
`location`	string	What the point marks: terminal \| ramp \| runway \| parking \| freight \| approximate
`scalerank`	integer	Natural Earth prominence, 2 (largest) to 9

Run executes the script in your browser and shows you its output and a preview. Submit executes it again on the server and grades what result holds.

What to submit

Submit: A Python script that assigns its output to result.
Input files: /data/states.geojson · /data/airports.geojson
Required properties: postal, airports, major_airports

Objectives

Read both layers from /data and join airports to states with a spatial predicate
Count airports and major airports per state without losing a state that has none
Assign the finished GeoDataFrame, one row per state, to the variable named result

Constraints

These are where the teaching is. Read them twice.

Use a spatial relationship to assign airports to states
Every state appears, including the ones with zero airports in this registry
result carries the state polygons with postal, airports and major_airports

Graded requirements

Assigns airports to states with a spatial predicate
One row per state
Carries postal, airports and major_airports
Total airports inside the states
Total major airports inside the states

Points-in-polygons per administrative unit is the backbone of every national statistics table built from a facility registry, and scripting it is what lets the table be trusted next year.

Python

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Files: /data/states.geojson, /data/airports.geojson · assign result

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What will be checked

5 scored, 0 informational

Assigns airports to states with a spatial predicate
18%
One row per state
18%
Carries postal, airports and major_airports
18%
Total airports inside the states
27%
Total major airports inside the states
18%