Create random datetime column conditional on another datetime column pandas

Question content

I have a pandas data frame df_sample:

columna columnb
a         aa
a         ab
b         ba
b         bb
b         bc

I have created a random column containing some date objects:

df_sample['contract_starts'] = np.random.choice(pd.date_range('2024-01-01', '2024-05-01'), len(df_sample))

This results in the following output:

columna columnb contract_starts
a         aa     2024-01-21
a         ab     2024-03-03
b         ba     2024-01-18
b         bb     2024-02-18
b         bc     2024-04-03

How to create another datetime column contract_noted that also has a given range of values ​​(e.g. until 2024-05-01) but does not exceed contract_startscolumn, for example:

columnA columnB contract_starts contract_noted
A         AA     2024-01-21      2024-01-20
A         AB     2024-03-03      2024-01-01
B         BA     2024-01-18      2024-01-13
B         BB     2024-02-18      2024-02-01
B         BC     2024-04-03      2024-03-28

Correct answer

You can subtract a random time increment from the contract_starts column by numpy.random. randint andto_timedelta:< /a>

df_sample['contract_noted'] = (df_sample['contract_starts'] - 
                               pd.to_timedelta(np.random.randint(1,30, len(df_sample)), 
                                               unit='d'))

print (df_sample)
  columna columnb contract_starts contract_noted
0       a      aa      2024-04-18     2024-03-21
1       a      ab      2024-02-12     2024-01-22
2       b      ba      2024-02-21     2024-02-02
3       b      bb      2024-04-12     2024-03-29
4       b      bc      2024-02-10     2024-02-03

If you also need the date and time between start and end, such as

contract_starts generate inetegers between 1 and the difference from the start date and time:

days =(df_sample['contract_starts'] - pd.Timestamp('2024-01-01')).dt.days
print (days)

df_sample['contract_noted'] = (df_sample['contract_starts'] - 
                               pd.to_timedelta(np.random.randint(1,days, len(df_sample)), 
                                               unit='d'))
print (df_sample)
  columnA columnB contract_starts contract_noted
0       A      AA      2024-02-09     2024-01-09
1       A      AB      2024-04-26     2024-02-23
2       B      BA      2024-04-10     2024-04-06
3       B      BB      2024-01-31     2024-01-07
4       B      BC      2024-01-14     2024-01-08

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