How To Compare Two Date By Iterating In A Pandas Data Frame And Create A New Column

I have a pandas data frame with customer transactions as shown below and create a column named 'Label' with 2 different values New Transaction performed before the end date of the

Solution 1:

Use numpy.where and Series.shift:

import numpy as np

df['Label'] = np.where(df['Transaction Start Date'].lt(df['Transaction End Date'].shift()), 'New Transaction performed before end date of previous transaction', 'New Transaction after the end date of previous transaction.')

Solution 2:

Use to_datetime first, then numpy.where with Series.lt form less compred shifted values by Series.shift and last set first value to empty string:

df['Transaction End Date'] = pd.to_datetime(df['Transaction End Date'])
df['Transaction Start Date'] = pd.to_datetime(df['Transaction Start Date'])

df['Label'] = np.where(df['Transaction Start Date'].lt(df['Transaction End Date'].shift()), 
                       'New Transaction performed before end date of previous transaction', 
                       'New Transaction after the end date of previous transaction.')
df.loc[0, 'Label'] = ''

Alternative solution:

m = df['Transaction Start Date'].lt(df['Transaction End Date'].shift())

df['Label'] = [''] + np.where(m, 
              'New Transaction performed before end date of previous transaction', 
              'New Transaction after the end date of previous transaction.')[1:].tolist()

---

print (df)
   Transaction ID Transaction Start Date Transaction End Date  \
0               1             2014-06-23           2014-07-15   
1               2             2014-07-14           2014-08-08   
2               3             2014-08-13           2014-08-22   
3               4             2014-08-21           2014-08-28   
4               5             2014-08-29           2014-09-05   
5               6             2014-09-06           2014-09-15   

                                               Label  
                                                     
1  New Transaction performed before end date of p...  
2  New Transaction after the end date of previous...  
3  New Transaction performed before end date of p...  
4  New Transaction after the end date of previous...  
5  New Transaction after the end date of previous...