Pandas - Go through 2 columns (latitude and longitude) and find the distance between each coordinate and a specific place

Question

I have a data frame (called coordinates) containing 3 columns: index, Latitude, Longitude - it has roughly 1,000 rows. I have the coordinates of a specific place and want to find the distance between the place and all the coordinates in the data frame. Currently, I can use geopy.distance to find the distance between two specific coordiantes. E.g.

import geopy.distance
site_coords = (38.898556, -77.037852)
place2_coords = (38.897147, -77.043934)
print(geopy.distance.vincenty(site_coords, place2_coords).km)

The above code gives 0.5503161689006362 (I have checked and this is correct)

My issue is with looping through the data frame (called coordinates) and calculating the distance for all coordinates in that data frame. Currently, this is what I have:

import geopy.distance
import pandas as pd
df = pd.read_csv('coordinates.csv', sep=',', header=None)

site_coords = (38.898556, -77.037852)
for index, row in df.iterrows():
    place2_coords = df
    x = geopy.distance.vincenty(site_coords, place2_coords).km
    print(x)

However when i print x it prints the same distance many times and the distance is incorrect. The coordinates file looks something like (when opened in notepad) - but has many more rows:

,Latitude,Longitude
0,73.3645,-0.9015
1,73.3645,-0.3995
2,73.3645,-0.5825

So i need a way to loop through and find the distance.

Answer 1

See here a variation on the one of sechilds. The site_coords are an input to the def. The apply function now uses 2 arguments: the row from the DataFrame and site_coords:

import pandas as pd
import numpy as np
import geopy.distance

def calc_distance(row, site_coords):
    station_coords = (row['lat'], row['lon'])
    d = geopy.distance.distance(site_coords, station_coords).km
    return(d)

df['distance'] = df.apply(calc_distance, site_coords=(38.898556, -77.037852), axis=1)

Answer 2

If your file looks like

,Latitude,Longitude
0,73.3645,-0.9015
1,73.3645,-0.3995
2,73.3645,-0.5825

but you read with "head=None",

df = pd.read_csv('coordinates.csv', sep=',', header=None)

the first line will become a data row instead. This may be the reason why you get a "AttributeError: 'Series' object has no attribute 'Latitude'.".

Try deleting "header=None" from your code.

df = pd.read_csv(StringIO(s), sep=',')
site_coords = (38.898556, -77.037852)

df.apply(lambda row: geopy.distance.vincenty(site_coords, (row.Latitude, row.Longitude)).km, axis=1)