Rolling Unique Sum for 3 previous months in python

Question

The following is the dataset I am looking at.

Input:-
Date          Name
01/01/2017    A
01/03/2017    B
02/05/2017    A
03/17/2017    C
04/08/2017    D
05/10/2017    B
06/12/2017    D

Output:-
Date      Unique Count
Jan 2017    2
Feb 2017    2
Mar 2017    3
Apr 2017    3
May 2017    3
Jun 2017    2

I want to get unique counts of "Name" in previous 3 months on rolling basis. For example for date 06/12/2017 the previous 3 months including itself is april, May, June. So April had "D", May had "B" and June had "D". So the unique count of June Month is 2. Similarly for all the other months as well.

I am looking for a pandas function that could help me achieve this. Or any custom code that could implement this.

Any help is appreciated.

Answer 1

Try:

months = pd.to_datetime(d.loc[:, "Date"]).dt.to_period("M")
out = pd.DataFrame([
    (month, len(d.loc[(-2 <= months - month) & (months - month <= 0), "Name"].unique()))
    for month in months.unique()])