Your first walkability map¶

The quickest way to feel what Close gives you: read the walk times from a starting point, map the supermarkets you can reach on foot, then draw how far a 30-minute walk takes you. The example city is Providence, Rhode Island.

Running this tutorial uses about 90 tokens.

Set up¶

Build a client, then read what you need from the free catalog.

from closecity import Client, close_map

close = Client("ck_live_your_key")   # use your own key here

amenity_types = close.destination_types()
supermarket_type = amenity_types.loc[amenity_types["label"] == "grocery_stores",
                                     "dest_type_id"].iloc[0]

providence_ri = close.places(q = "Providence").iloc[0]
start_lon = providence_ri["lon"]
start_lat = providence_ri["lat"]

Read travel times from a starting point¶

Pick a starting point, here the centre of Providence, and ask how long it takes to walk to each kind of amenity. point_summary() takes a lat/lon instead of a block GEOID. Join the catalog’s readable name and sort by time, so the nearest things are on top.

walk_times = close.point_summary(lat = start_lat, lon = start_lon, mode = "walk")
walk_times = walk_times.merge(
    amenity_types[["dest_type_id", "name"]],
    on = "dest_type_id"
)
walk_times.sort_values("travel_time")[["name", "travel_time"]]

	name	travel_time
27	Non-frequent other transit stops	0.0
26	Non-frequent transit stops	0.0
28	Other transit stops	0.0
17	All transit stops	0.0
4	Restaurants	1.0
8	Cafes and coffee shops	1.0
18	Parks	2.0
22	Parks (<0.5 acres)	2.0
16	Libraries	3.0
31	Public libraries	3.0
5	Bars	3.0
7	Grocery stores	6.0
19	Parks (0.5–1 acres)	6.0
20	Parks (1–10 acres)	6.0
30	Parks (>1 acre)	6.0
29	Parks (>0.5 acres)	6.0
11	Pharmacies	7.0
14	Bookstores	8.0
15	Bike shops	8.0
6	Convenience stores	9.0
23	Playgrounds	9.0
32	University/private libraries	9.0
3	High schools	11.0
0	Public schools	11.0
21	Parks (>10 acres)	12.0
24	Bakeries	13.0
12	Preschools	13.0
13	Community centers	14.0
9	Dentists	15.0
10	Gyms and exercise studios	18.0
2	Middle schools	21.0
1	Elementary schools	25.0
25	Hardware stores	25.0

Map the supermarkets within a 30-minute walk¶

A 30-minute walk is a travel-time question, not a distance one, so let the routing answer it directly: point_pois returns every POI reachable from the starting point within max_minutes, each carrying its walk time, with no isochrone to overlay. close_map() draws them in one line, shaded by that walk time (blue = closest), with the starting point marked by an X and the city boundary behind for context.

nearby_supermarkets = close.point_pois(
    lat = start_lat,
    lon = start_lon,
    mode = "walk",
    type = supermarket_type,
    max_minutes = 30
)

city_boundary = close.place_boundary(geoid = providence_ri["geoid"])
close_map(
    nearby_supermarkets,
    fill = "travel_time",
    boundary = city_boundary,
    label = "name",
    mark = (start_lon, start_lat)
)

Draw how far you can walk¶

An isochrone is the headline map: the area you can reach on foot in 10, 20, and 30 minutes. Shade it by the contour minutes; blue marks the nearest, most-reachable ring.

rings = close.isochrone(
    lon = start_lon,
    lat = start_lat,
    mode = "walk",
    direction = "from",
    contours = [10, 20, 30],
    format = "geojson"
)
close_map(rings, fill = "contour")

Walk versus transit¶

The same starting point and the same 30-minute budget, on foot and by bus: the clearest way to see what transit buys you.

walk = close.isochrone(
    lon = start_lon,
    lat = start_lat,
    mode = "walk",
    direction = "from",
    minutes = 30,
    format = "geojson"
)
transit = close.isochrone(
    lon = start_lon,
    lat = start_lat,
    mode = "transit",
    direction = "from",
    minutes = 30,
    format = "geojson"
)

close_map(walk, color = "#058040")

close_map(transit, color = "#202a5b")