airport_connections.py

"""
Connections Among U.S. Airports Interactive
-------------------------------------------
This example shows all the connections between major U.S. airports. Lookup transformations
are used to find the coordinates of each airport and connecting airports. Connections
are displayed on pointerover via a single selection.
"""
# category: case studies
import altair as alt
from vega_datasets import data

# Since these data are each more than 5,000 rows we'll import from the URLs
airports = data.airports.url
flights_airport = data.flights_airport.url

states = alt.topo_feature(data.us_10m.url, feature="states")

# Create pointerover selection
select_city = alt.selection_point(
    on="pointerover", nearest=True, fields=["origin"], empty=False
)

# Define which attributes to lookup from airports.csv
lookup_data = alt.LookupData(
    airports, key="iata", fields=["state", "latitude", "longitude"]
)

background = alt.Chart(states).mark_geoshape(
    fill="lightgray",
    stroke="white"
).properties(
    width=750,
    height=500
).project("albersUsa")

connections = alt.Chart(flights_airport).mark_rule(opacity=0.35).encode(
    latitude="latitude:Q",
    longitude="longitude:Q",
    latitude2="lat2:Q",
    longitude2="lon2:Q"
).transform_lookup(
    lookup="origin",
    from_=lookup_data
).transform_lookup(
    lookup="destination",
    from_=lookup_data,
    as_=["state", "lat2", "lon2"]
).transform_filter(
    select_city
)

points = alt.Chart(flights_airport).mark_circle().encode(
    latitude="latitude:Q",
    longitude="longitude:Q",
    size=alt.Size("routes:Q").legend(None).scale(range=[0, 1000]),
    order=alt.Order("routes:Q").sort("descending"),
    tooltip=["origin:N", "routes:Q"]
).transform_aggregate(
    routes="count()",
    groupby=["origin"]
).transform_lookup(
    lookup="origin",
    from_=lookup_data
).transform_filter(
    (alt.datum.state != "PR") & (alt.datum.state != "VI")
).add_params(
    select_city
)

(background + connections + points).configure_view(stroke=None)