import pandas as pd
import numpy as np

def benford_function(value):
    if value == '':
        return []

    if ("." in value):
         before_decimal=value.split(".")[0]
         if len(before_decimal)==0:
             bd_first="0"
             bd_second="0"

         if len(before_decimal)>1:
             before_decimal=before_decimal[:2]
             bd_first=before_decimal[0]
             bd_second=before_decimal[1]
         elif len(before_decimal)==1:
             bd_first="0"
             bd_second=before_decimal[0]

         after_decimal=value.split(".")[1]
         if len(after_decimal)>1:
             ad_first=after_decimal[0]
             ad_second=after_decimal[1]
         elif len(after_decimal)==1:
             ad_first=after_decimal[0]
             ad_second="0"
         else:
             ad_first="0"
             ad_second="0"



    else:
        ad_first="0"
        ad_second="0"
        if len(value)>1:
             bd_first=value[0]
             bd_second=value[1]
        else:
            bd_first="0"
            bd_second=value[0]
    return pd.Series([bd_first,bd_second,ad_first,ad_second])

df.apply(lambda row: benford_function(row['a']), axis=1)

df[['bd_first'],['bd_second'],['ad_first'],['ad_second']]= df.apply(lambda row: benford_function(row['a']), axis=1)