[FIXED] Count Number of Values Less than Value in Another Column in Dataframe

Issue

Given a dataframe like the one below, for each date in Enrol Date how can I count the number of values in preceding rows in Close Date that are earlier? Ideally I would like to add the results as a new column.

Class	Enrol Date	Close Date
A	30/10/2003	05/12/2003
A	22/12/2003	23/09/2005
A	06/09/2005	29/09/2005
A	15/11/2005	07/12/2005
A	27/02/2006	28/03/2006

Desired result:

Class	Enrol Date	Close Date	Prior Dates
A	30/10/2003	05/12/2003	0
A	22/12/2003	23/09/2005	1
A	06/09/2005	29/09/2005	1
A	15/11/2005	07/12/2005	3
A	27/02/2006	28/03/2006	4

Solution

A possible option using triu :

cols = ["Enrol Date", "Close Date"]
df[cols] = df[cols].apply(pd.to_datetime, dayfirst=True)

enrol = df["Enrol Date"].to_numpy()
close = df["Close Date"].to_numpy()[:, None]

df["Prior Dates"] = np.triu(enrol>close).sum(0)

Output :

print(df)

  Class Enrol Date Close Date  Prior Dates
0     A 2003-10-30 2003-12-05            0
1     A 2003-12-22 2005-09-23            1
2     A 2005-09-06 2005-09-29            1
3     A 2005-11-15 2005-12-07            3
4     A 2006-02-27 2006-03-28            4

Answered By - Timeless