# Calculate distance b/w two data frames and result into a cross distance matrix and find nearest location in python

## Question:

The data is as follows:

```
import pandas as pd
city_data = {'City': ['Delhi', 'Mumbai'],
'Lat': [28.7041, 19.0760,],
'Long':[77.1025,72.8777] }
person_data = {'City': ['A', 'B'],
'Lat': [12.9716, 13.0827,],
'Long':[77.5946,80.2707] }
df_city = pd.DataFrame(city_data)
df_person = pd.DataFrame(person_data)
```

The distance took haversine distance calculation. There are 1000+ people and 300+ locations

## Answers:

Here’s a way of doing this using `scipy.metrics.pairwise.haversine_distaces`

, which does a pairwise-computation for each pair of coordinates. Note that I added another city so that the two lists would be different sizes, just to make sure the array coordinates were in the right order:

```
import pandas as pd
import numpy as np
from sklearn.metrics.pairwise import haversine_distances
city_data = {'City': ['Delhi', 'Mumbai','Jakarta'],
'Lat': [28.7041, 19.0760,6.175],
'Long':[77.1025,72.8777,106.8275] }
person_data = {'Person': ['A', 'B'],
'Lat': [12.9716, 13.0827,],
'Long':[77.5946,80.2707] }
df_city = pd.DataFrame(city_data)
df_person = pd.DataFrame(person_data)
print(df_city)
print()
print(df_person)
print()
# Extract as arrays and convert to radians.
c1 = np.radians(df_city[['Lat','Long']].to_numpy())
c2 = np.radians(df_person[['Lat','Long']].to_numpy())
# Compute distances in kilometers.
dist = haversine_distances(c2, c1) * 6371000/1000
print(dist)
print()
# Convert back to dataframe.
df = pd.DataFrame( dist, columns=df_city['City'], index=df_person['Person'])
print(df)
print()
# Sort the data and return the indexes of the closest two.
distsort = dist.argsort(axis=1)[:,:2]
# Look those up in the city names.
distsort = df_city['City'].to_numpy()[distsort]
df2 = pd.DataFrame( distsort, columns=['Closest','Next'], index=df_person['Person'])
print(df2)
```

Output:

```
City Lat Long
0 Delhi 28.7041 77.1025
1 Mumbai 19.0760 72.8777
2 Jakarta 6.1750 106.8275
Person Lat Long
0 A 12.9716 77.5946
1 B 13.0827 80.2707
[[1750.11476241 845.31838566 3290.21557611]
[1767.65141115 1033.09851229 3008.41699612]]
City Delhi Mumbai Jakarta
Person
A 1750.114762 845.318386 3290.215576
B 1767.651411 1033.098512 3008.416996
Closest Next
Person
A Mumbai Delhi
B Mumbai Delhi
```