In [1]:

    

%%file test.csv
30.263888889,45.563456
23.457654,34.433425


    

    




Overwriting test.csv

In [2]:

    

import pandas as pd
import numpy as np


    

In [3]:

    

input = pd.read_csv('test.csv', names=['Latitude', 'Longitude'])
input


    

    
Out[3]:






  

    

      

      
Latitude
      
Longitude
    
  
  

    

      
0
      
30.263889
      
45.563456
    
    

      
1
      
23.457654
      
34.433425
    
  

In [49]:

    

def d2s(df,key='Latitude'):
    '''convert from decimal degrees to sessagesimal degrees
    take as input a pandas dataframe and a column name'''
    g = df[key].values.astype(int)
    p = ((( df[key].values) - df[key].values.astype(int))*60).astype(int)
    s = (((df[key].values - df[key].values.astype(int)) * 60. ) - p ) * 60.
    param = key
    ses = pd.DataFrame(np.array([g,p,s]).T, columns=['Degree','Minute','Second'] , dtype=float)
    return ses

def s2d(df,key=['Degree','Minute','Second']):
    '''convert from sessagesimal degrees to decimal degrees
    take as input a pandas dataframe and a list of column names'''
    deg=df[key[0]].values+(df[key[1]].values/60.+df[key[2]].values/3600.)
    return deg


    

In [39]:

    

Lat = d2s(df=input,key='Latitude')
Lon = d2s(df=input,key='Longitude')


    

In [40]:

    

Lat


    

    
Out[40]:






  

    

      

      
Degree
      
Minute
      
Second
    
  
  

    

      
0
      
30
      
15
      
50.0000
    
    

      
1
      
23
      
27
      
27.5544
    
  

In [44]:

    

Lon


    

    
Out[44]:






  

    

      

      
Degree
      
Minute
      
Second
    
  
  

    

      
0
      
45
      
33
      
48.4416
    
    

      
1
      
34
      
26
      
0.3300
    
  

In [45]:

    

s2d(Lat)


    

    
Out[45]:





array([ 30.26388889,  23.457654  ])

In [46]:

    

s2d(Lon)


    

    
Out[46]:





array([ 45.563456,  34.433425])

In [ ]: