Download any OSM Geospatial Entities with OSMnx¶

More info:

This notebook provides a quick tour of using OSMnx to download any geospatial entites/objects from OpenStreetMap as a geopandas GeoDataFrame.

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import osmnx as ox

%matplotlib inline
ox.__version__

Use the geometries module to download entities, such as grocery stores, transit stops, points of interest, or building footprints, and turn them into a GeoDataFrame: see docs.

To query, pass a tags dict where keys are OSM tags. The dict's values can be either:

True to retrieve all OSM objects with this tag, regardless of its value
a single value as a string to retrieve all OSM objects with this tag:value combination
a list of string values to retrieve all OSM objects where this tag matches any of these values

Pass multiple dict key:value pairs to retrieve the union (not intersection) of these pairs.

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# get all building footprints in some neighborhood
# `True` means retrieve any object with this tag, regardless of value
place = "Bunker Hill, Los Angeles, California"
tags = {"building": True}
gdf = ox.geometries_from_place(place, tags)
gdf.shape

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fig, ax = ox.plot_footprints(gdf, figsize=(3, 3))

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# get all the parks in some neighborhood
# constrain acceptable `leisure` tag values to `park`
tags = {"leisure": "park"}
gdf = ox.geometries_from_place(place, tags)
gdf.shape

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# get everything tagged amenity,
# and everything tagged landuse = retail or commercial,
# and everything tagged highway = bus_stop
tags = {"amenity": True, "landuse": ["retail", "commercial"], "highway": "bus_stop"}
gdf = ox.geometries_from_place("Piedmont, California, USA", tags)
gdf.shape

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# view just the banks
gdf[gdf["amenity"] == "bank"].dropna(axis=1, how="any")

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# view just the bus stops
gdf[gdf["highway"] == "bus_stop"].dropna(axis=1, how="any").head()

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