In [1]:

    

import pandas as pd
import numpy as np


    

In [2]:

    

raw_data = {'geo': ['40.0024, -105.4102', '40.0068, -105.266', '39.9318, -105.2813', np.nan]}
df = pd.DataFrame(raw_data, columns = ['geo'])
df


    

    
Out[2]:






  

    

      

      
geo
    
  
  

    

      
0
      
40.0024, -105.4102
    
    

      
1
      
40.0068, -105.266
    
    

      
2
      
39.9318, -105.2813
    
    

      
3
      
NaN
    
  

In [3]:

    

# Create two lists for the loop results to be placed
lat = []
lon = []

# For each row in a varible,
for row in df['geo']:
    # Try to,
    try:
        # Split the row by comma and append
        # everything before the comma to lat
        lat.append(row.split(',')[0])
        # Split the row by comma and append
        # everything after the comma to lon
        lon.append(row.split(',')[1])
    # But if you get an error
    except:
        # append a missing value to lat
        lat.append(np.NaN)
        # append a missing value to lon
        lon.append(np.NaN)

# Create two new columns from lat and lon
df['latitude'] = lat
df['longitude'] = lon


    

In [4]:

    

df


    

    
Out[4]:






  

    

      

      
geo
      
latitude
      
longitude
    
  
  

    

      
0
      
40.0024, -105.4102
      
40.0024
      
-105.4102
    
    

      
1
      
40.0068, -105.266
      
40.0068
      
-105.266
    
    

      
2
      
39.9318, -105.2813
      
39.9318
      
-105.2813
    
    

      
3
      
NaN
      
NaN
      
NaN