Longitude and Latitude Distance Calculation between 2 dataframes

I have the following two dataframes. Call this df1

    City              Latitude       Longitude
0   NewYorkCity       40.7128        74.0060
1   Chicago            41.8781       87.6298
2   LA                34.0522        118.2437
3   Paris             48.8566        2.3522

and call this one df2

    Place      Latitude      Longitude
0   75631      26.78436      -80.103
1   89210      26,75347      -80.0192

I want to know how I can calculate the distance between place and all cities listed. So it should look something like this.

    Place      Latitude      Longitude     NewYorkCity    Chicago     Paris
0   75631      26.78436      -80.103       some number     .....         ....
1   89210      26,75347      -80.0192      some number      ....        ....

I’m reading through this particular post and attempting to adapt:Pandas Latitude-Longitude to distance between successive rows

def haversine(lat1, lon1, lat2, lon2, to_radians=True, earth_radius=6371):
   
    
    if to_radians:
        lat1, lon1, lat2, lon2 = np.radians([lat1, lon1, lat2, lon2])

    a = np.sin((lat2-lat1)/2.0)**2 + 
        np.cos(lat1) * np.cos(lat2) * np.sin((lon2-lon1)/2.0)**2

    return earth_radius * 2 * np.arcsin(np.sqrt(a))


df['dist'] = haversine(df1.Latitude, df.Longitude, df2.Latitude, df2.Longitude)

I know this looks wrong. Am I needing a for loop to go through each of the ones in df1?

Answer

The following code worked for me:

a=list(range(19))

for i in a:
    Lat1=df1[i,2] #works down 3rd column
    Lon1=df1[i,3] #works down 4th column
    Lat2=df2['Latitude']
    Lon2= df2['Longitude']

    #the i in the below piece works down the 1st column to grab names
    #the code then places them into column names

    df2[df1iloc[i,0]] = 3958.756*np.arccos(np.cos(math.radians(90-Lat1)) *np.cos(np.radians(90-Lat2)) +np.sin(math.radians(90-Lat1)) *np.sin(np.radians(90-Lat2)) *np.cos(np.radians(Lon1-Lon2)))

Note that this calculates the miles between each location as direct shots there. Doesn’t factor in twists and turns.