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import time
from collections import defaultdict
import pandas as pd
from shapely.geometry import Point
import geopandas
def _get_throttle_time(provider):
"""
Amount of time to wait between requests to a geocoding API, for providers
that specify rate limits in their terms of service.
"""
import geopy.geocoders
# https://operations.osmfoundation.org/policies/nominatim/
if provider == geopy.geocoders.Nominatim:
return 1
else:
return 0
def geocode(strings, provider=None, **kwargs):
"""
Geocode a set of strings and get a GeoDataFrame of the resulting points.
Parameters
----------
strings : list or Series of addresses to geocode
provider : str or geopy.geocoder
Specifies geocoding service to use. If none is provided,
will use 'photon' (see the Photon's terms of service at:
https://photon.komoot.io).
Either the string name used by geopy (as specified in
geopy.geocoders.SERVICE_TO_GEOCODER) or a geopy Geocoder instance
(e.g., geopy.geocoders.Photon) may be used.
Some providers require additional arguments such as access keys
See each geocoder's specific parameters in geopy.geocoders
Notes
-----
Ensure proper use of the results by consulting the Terms of Service for
your provider.
Geocoding requires geopy. Install it using 'pip install geopy'. See also
https://github.com/geopy/geopy
Examples
--------
>>> df = geopandas.tools.geocode( # doctest: +SKIP
... ["boston, ma", "1600 pennsylvania ave. washington, dc"]
... )
>>> df # doctest: +SKIP
geometry address
0 POINT (-71.05863 42.35899) Boston, MA, United States
1 POINT (-77.03651 38.89766) 1600 Pennsylvania Ave NW, Washington, DC 20006...
"""
if provider is None:
provider = "photon"
throttle_time = _get_throttle_time(provider)
return _query(strings, True, provider, throttle_time, **kwargs)
def reverse_geocode(points, provider=None, **kwargs):
"""
Reverse geocode a set of points and get a GeoDataFrame of the resulting
addresses.
The points
Parameters
----------
points : list or Series of Shapely Point objects.
x coordinate is longitude
y coordinate is latitude
provider : str or geopy.geocoder (opt)
Specifies geocoding service to use. If none is provided,
will use 'photon' (see the Photon's terms of service at:
https://photon.komoot.io).
Either the string name used by geopy (as specified in
geopy.geocoders.SERVICE_TO_GEOCODER) or a geopy Geocoder instance
(e.g., geopy.geocoders.Photon) may be used.
Some providers require additional arguments such as access keys
See each geocoder's specific parameters in geopy.geocoders
Notes
-----
Ensure proper use of the results by consulting the Terms of Service for
your provider.
Reverse geocoding requires geopy. Install it using 'pip install geopy'.
See also https://github.com/geopy/geopy
Examples
--------
>>> from shapely.geometry import Point
>>> df = geopandas.tools.reverse_geocode( # doctest: +SKIP
... [Point(-71.0594869, 42.3584697), Point(-77.0365305, 38.8977332)]
... )
>>> df # doctest: +SKIP
geometry address
0 POINT (-71.05941 42.35837) 29 Court Sq, Boston, MA 02108, United States
1 POINT (-77.03641 38.89766) 1600 Pennsylvania Ave NW, Washington, DC 20006...
"""
if provider is None:
provider = "photon"
throttle_time = _get_throttle_time(provider)
return _query(points, False, provider, throttle_time, **kwargs)
def _query(data, forward, provider, throttle_time, **kwargs):
# generic wrapper for calls over lists to geopy Geocoders
from geopy.geocoders import get_geocoder_for_service
from geopy.geocoders.base import GeocoderQueryError
if forward:
if not isinstance(data, pd.Series):
data = pd.Series(data)
else:
if not isinstance(data, geopandas.GeoSeries):
data = geopandas.GeoSeries(data)
if isinstance(provider, str):
provider = get_geocoder_for_service(provider)
coder = provider(**kwargs)
results = {}
for i, s in data.items():
try:
if forward:
results[i] = coder.geocode(s)
else:
results[i] = coder.reverse((s.y, s.x), exactly_one=True)
except (GeocoderQueryError, ValueError):
results[i] = (None, None)
time.sleep(throttle_time)
df = _prepare_geocode_result(results)
return df
def _prepare_geocode_result(results):
"""Convert the geocode results to a GeoDataFrame.
Takes a dict where keys are index entries, values are tuples containing:
(address, (lat, lon))
"""
# Prepare the data for the DataFrame as a dict of lists
d = defaultdict(list)
index = []
for i, s in results.items():
if s is None:
p = Point()
address = None
else:
address, loc = s
# loc is lat, lon and we want lon, lat
if loc is None:
p = Point()
else:
p = Point(loc[1], loc[0])
d["geometry"].append(p)
d["address"].append(address)
index.append(i)
df = geopandas.GeoDataFrame(d, index=index, crs="EPSG:4326")
return df
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