geopy | Geocoding library for Python | REST library
kandi X-RAY | geopy Summary
kandi X-RAY | geopy Summary
Geocoding library for Python.
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Top functions reviewed by kandi - BETA
- Geocode a query
- Handle adapter errors
- Parse the Retry - After header
- Wrapper for geocoder
- Perform geocode request
- Format a degrees
- Format the object as a string
- Request raw content
- Geocode a word
- Call geocoding API
- Geocoding API endpoint
- Performs a reverse lookup
- Parse an XML page
- Reverse timezone query
- Reverse a point
- The geocode API endpoint
- Parse geocoder response
- Perform a geocoding query
- Perform geocode
- Perform geocoding
- Geocode a location
- Generate geocode coordinates
- Reverse geocode query
- Perform a reverse lookup
- Reverse geocoder
- Perform a reverse search
geopy Key Features
geopy Examples and Code Snippets
Lines of Code : 0License : Permissive (MIT)
Copy>>> from geopy.geocoders import Nominatim
>>> geolocator = Nominatim(user_agent="specify_your_app_name_here")
>>> location = geolocator.geocode("175 5th Avenue NYC")
>>> print(location.address)
Flatiron Building, 1 >>> from geopy.distance import geodesic
>>> newport_ri = (41.49008, -71.312796)
>>> cleveland_oh = (41.499498, -81.695391)
>>> print(geodesic(newport_ri, cleveland_oh).miles)
538.390445368
>>> from geopy.d import geopy
import geopy.distance
lat = 30.456025341663068
lon = -86.41408883615411
distance_ft = 86
bearing = 0
start_point = geopy.Point(lat, lon)
end_point = geopy.distance.geodesic(feet=distance_ft).destination(start_point, bearing)for i in split_dfs:
i['Destination Coordinates'] = i['Destination Coordinates'].transform(
lambda x: x[:2] if isinstance(x, list) else x)
from shapely.geometry import Point
d = {'col1': ['name1', 'name2'], 'geometry': [Point(1, 2), Point(2, 1)]}
gdf = geopandas.GeoDataFrame(d, crs="EPSG:4326")
gdf
def flatten_nested_json_df(df):
df = df.reset_indgeocache_list_by_distance = sorted(geocache_list, key=operator.attrgetter('distance'))
return geocache_list_by_distance
from geopy.geocoders import Nominatim
geolocator = Nominatim(user_agent="geoapiExercises")
location = geolocation.geocode('city-name')
print(location.address)
Brno, okres Brno-město, Jihomoravský kraj, Jihovýchod,for element in distance_data_to_add:
distance_data.write(str(element) + "\n")
distance_data.write('\n'.join(map(repr, distance_to_add)))
from geopy import distance
# slice the big area into small ones for Google map radius restriction problem
def slice_search_area(point_a=(None, None), point_b=(None, None), region=None, radius=50000):
if (None in point_a) or (None in Community Discussions
Trending Discussions on geopy
QUESTION
When trying to run this line G = ox.graph_from_place('Piedmont, CA, USA', network_type='drive') I get this error:
...ANSWER
Answered 2022-Mar-26 at 07:01Does this URL work in your browser: https://nominatim.openstreetmap.org//search?format=json&polygon_geojson=1&dedupe=0&limit=50&q=Piedmont%2C+CA%2C+USA
you can also set request params:
ox.config(request_kwargs={})
QUESTION
I need to add a column with changes ow worker coordinates through different stages. We have a DataFrame:
...ANSWER
Answered 2022-Mar-18 at 17:33I think that the problem could be the following line:
QUESTION
I have a list of 200+ latitude and longitude coordinate pairs.
For each coordinate pair I want to create a dataframe which contains column district and column state. So my dataframe will have 3 columns cord, district and state.
For this I am using geopy library but I am unable to get record for more than 115 coordinates.
Sample Data
ANSWER
Answered 2022-Feb-24 at 10:29From Nominatim Usage Policy they require not to do heavy usage i.e. maximum 1 request per second. "No heavy uses (an absolute maximum of 1 request per second)." You can use geopy's RateLimiter to send 1 request per second. I've tested the following code works for more than 115 requests:
QUESTION
I am brand new to Python in general and have a limited but aged knowledge of Javascript. I am trying to accomplish a small project using Python, but I have gotten stuck with my own comprehension.
I have a GPS coordinate in decimal degrees as a starting point (30.456025341663068, -86.41408883615411), a distance in feet (86 feet) from the start point to the expected endpoint and I have a bearing in degrees (0 to 360) from start point to endpoint. Given these values, I am attempting to simply return the GPS coordinate in decimal degrees of the endpoint.
I found one StackExchange post that appears to give me a viable option using GeoPy, but I'm simply getting lost in trying to implement it. Can someone assist with how to accomplish this? GeoPy is not a requirement for me, I just imported it based on the answer in the other StackExchange question:
calculating a gps coordinate given a point, bearing and distance
...ANSWER
Answered 2022-Feb-16 at 15:43Perhaps you could do something like this:
QUESTION
I have this df:
...ANSWER
Answered 2022-Feb-07 at 11:45If you want to compare your df coordinates with some external coordinates tuple, try this:
QUESTION
I am working on a project for university, where I have two pandas dataframes:
...ANSWER
Answered 2022-Feb-01 at 13:32You can cross-merge the two dfs to get a distance between each id in df1 vs df2:
QUESTION
Currently, I am adding a field, 'distance', to a queryset after it's been created, and then returning it. However, I would like to sort the queryset by distance, if it's possible to annotate it.
Currently, my model, GeoCache, has fields latitude and longitude as models.DecimalField(max_digits=15, decimal_places=10, null=True, blank=True). Using geopy, I can add distance to my queryset like this:
...ANSWER
Answered 2022-Jan-02 at 23:58Thanks to the comment from Andre Borie, I decided to focus on sorting the queryset after-the-fact, and fixed it with this:
QUESTION
I have two dictionaries. One where UserID is the key and their location is the value.
The first items look like this:
ANSWER
Answered 2021-Dec-20 at 15:03You can create RDDs from the users_dict and places_dict then join with ratings_rdd to get the coordinates of the user and the rated place. Then using map, call geodesic to calculate the distance.
Here's an example:
QUESTION
My dataframe:
...ANSWER
Answered 2021-Dec-11 at 13:15You need to define a custom user-defined-function:
QUESTION
Given a list of lat/lon points, how can we find the minimum number of 50-mile radius circles (and their lat/lon points) such that these circles cover all the points in the list?
The solution does not need to be optimal, and the calculation of radiuses/distances can be approximated, for simplicity. Or use a helper library like geopy.distance.
For example, here is a CSV list of lat/lon points:
...ANSWER
Answered 2021-Nov-22 at 00:09Updated answer based on comments:
You have many options.
Here are 3 differents ways of doing that:
1. With scipy.CKDTree:
Pros :
- This will be fast
Cons :
- less accurate because the computed distance is euclidean
- and the radius will be the same as your inputs, so here in degrees
I would go with a cKDTree and a radius query to find all points in radius, remove theses points from list, and continue with remaining points. This is not optimal but can be a good basis.
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
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Install geopy
You can use geopy like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.
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