Machine Learning with Python | Geocoding and Reverse Geocoding using Python- P76

Publicado el: 13 junio 2018
en el canal de: technologyCult

3,198

Machine Learning with Python | Geocoding and Reverse Geocoding using Python- P76

Session # 76

Topic to be covered - Geocode and Reverse Geocode

Geocoding is the process of transforming a description of a location—such as a pair of coordinates, an address, or a name of a place—to a location on the earth's surface. You can geocode by entering one location description at a time or by providing many of them at once in a table. The resulting locations are output as geographic features with attributes, which can be used for mapping or spatial analysis.

You can quickly find various kinds of locations through geocoding. The types of locations that you can search for include points of interest or names from a gazetteer, like mountains, bridges, and stores; coordinates based on latitude and longitude or other reference systems, such as the Military Grid Reference System (MGRS) or the U.S. National Grid system; and addresses, which can come in a variety of styles and formats, including street intersections, house numbers with street names, and postal codes.

Code Starts Here
==============

from geopy.geocoders import Nominatim

geolocator = Nominatim()

city = 'kolkata'
country = 'India'

Both City and Country
loc = geolocator.geocode(str(city + ','+ country))

print(loc.latitude,loc.longitude)

loc1 = geolocator.geocode(country)
print(loc1.latitude, loc1.longitude)

from pygeocoder import Geocoder

result = Geocoder.reverse_geocode(19.1334321,72.8882172)

print(result.coordinates)
print(result.country)
print(result.city)
print(result.administrative_area_level_1)
print(result.administrative_area_level_2)

address1 = Geocoder.geocode('221B Baker Street,LONDON NW1 6XE')

print(address1.street_number)

print(address1.route)

print(address1.city)
print(address1.country)
print(address1.administrative_area_level_1)
print(address1.administrative_area_level_2)

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