Bulk process a number of latitude and longitude values from a dataframe and make a new column from t-CodePudding

In my Dataframe I have two columns of latitude and longitude. I want to use these two columns to calculate my test_url column for getting the country inside it.

I'm using the Nominatim OpenStreetMap api url for this.

My imports:

import pandas as pd
import requests

My check_country function:

def check_country(url):
    
    r = requests.get(url)
    results = r.json()['address']
    
    return results['country']

Column calculation:

df['test_url'] = df[['latitude','longitude']].apply(lambda x : check_country(f"https://nominatim.openstreetmap.org/reverse?lat={x[0]}&lon={x[1]}&format=json"),axis=1)

But with this I'm getting a connection error.

Error

ConnectionError: 

HTTPSConnectionPool(host='nominatim.openstreetmap.org', port=443): Max retries exceeded with url: /reverse?lat=10.75161&lon=77.11299&format=json 

(Caused by NewConnectionError('<urllib3.connection.HTTPSConnection object at 0x000002262FC94C40>: 

Failed to establish a new connection:

[WinError 10061] No connection could be made because the target machine actively refused it'

))

CodePudding user response：

You can use GeoPandas and use the "World Administrative Boundaries" dataset to make local requests. First step is to ownload the GeoJSON file and install geopandas then:

# Python env: pip install geopandas
# Anaconda env: conda install geopandas

import geopandas as gpd
from shapely.geometry import Point

gdf = gpd.read_file('world-administrative-boundaries.geojson')
p = Point(77.11299, 10.75161)

out = gdf.loc[gdf.intersects(p), 'name']
print(out)

# Output:
226    India
Name: name, dtype: object

Advanced usage: Multiple coordinates:

coords = [(40.730610, -73.935242), (10.75161, 77.11299)]
points = [Point(lon, lat) for lat, lon in  coords]
dfp = gpd.GeoDataFrame({'geometry': points}, crs=gdf.crs)
out = gpd.sjoin(dfp, gdf, predicate='within')
print(out)

# Output
                     geometry  index_right           french_short iso3        status iso_3166_1_alpha_2_codes                      name            region color_code continent
0  POINT (-73.93524 40.73061)          182  États-Unis d'Amérique  USA  Member State                       US  United States of America  Northern America        USA  Americas
1   POINT (77.11299 10.75161)          226                   Inde  IND  Member State                       IN                     India     Southern Asia        IND      Asia