5

I have problem to analyse vincenty distance because the format is object and have km metrics in there, I want to analyse further. I want to convert vincenty distance to float format

Here's the data

customer_id lat_free    long_free   lat_device  long_device radius      timestamp
7509        -6.283468   106.857636  -7.802388   110.368660  1264.000000 2017-12-14 21:18:40.327
7509        -6.283468   106.857636  -7.804296   110.367192  14.000000   2017-12-15 20:02:21.923

Here's my code

from geopy.distance import vincenty
df['Vincenty_distance'] = df.apply(lambda x: vincenty((x['lat_free'], x['long_free']), (x['lat_device'], x['long_device'])), axis = 1)

This is the result

customer_id lat_free    long_free   lat_device  long_device radius      timestamp                 Vincenty_distance
7509        -6.283468   106.857636  -7.802388   110.368660  1264.000000 2017-12-14 21:18:40.327   422.7123873310482 km
7509        -6.283468   106.857636  -7.804296   110.367192  14.000000   2017-12-15 20:02:21.923   422.64674499172787 km

I need to convert Vincenty_distance to float

Nabih Bawazir
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2 Answers2

6

The best is add .km:

df['Vincenty_distance'] = df.apply(lambda x: vincenty((x['lat_free'], x['long_free']), (x['lat_device'], x['long_device'])).km, axis = 1)

Or use after processing - convert to string, remove last letters and cast to floats:

df['Vincenty_distance'] = df['Vincenty_distance'].astype(str).str[:-3].astype(float)

print (df)
   customer_id  lat_free   long_free  lat_device  long_device  radius  \
0         7509 -6.283468  106.857636   -7.802388   110.368660  1264.0   
1         7509 -6.283468  106.857636   -7.804296   110.367192    14.0   

                 timestamp  Vincenty_distance  
0  2017-12-14 21:18:40.327         422.712361  
1  2017-12-15 20:02:21.923         422.646709  

print (df.dtypes)

customer_id            int64
lat_free             float64
long_free            float64
lat_device           float64
long_device          float64
radius               float64
timestamp             object
Vincenty_distance    float64
dtype: object
jezrael
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2

You can use str.replace to remove "km" and use apply to set float to the series.

Ex:

df["Vincenty_distance"] = df["Vincenty_distance"].str.replace(" km", "").apply(float)
Rakesh
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