How to define custom fiscal quarters in pandas?-CodePudding

I have a dataframe shown below

df = pd.DataFrame(
    {'stud_id' : [101, 101, 101, 101, 
                  101, 101, 101, 101],
     'ques_date' : ['13/11/2020', '10/1/2018','11/11/2017', '27/03/2016', 
                '13/05/2010',  '10/11/2008','11/1/2007', '27/02/2006']})

Basically, I would like to do the below

a) Get the fiscal quarter for each ques_date

However, our company follows their own definition for quarter which is given below

Q1 - Oct to Dec
Q2 - Jan to Mar
Q3 - Apr to Jun
Q4 - July - Sep

I was trying something like below

df['act_qtr'] = df['ques_date'].dt.to_period('Q')
df['custom_qtr'] = np.where(df['act_qtr'] == 'Q1','Q2',(df['act_qtr'] == 'Q2', 'Q3',(df['act_qtr'] == 'Q3', 'Q4', (df['act_qtr'] == 'Q4', 'Q1'))))

But this is not elegant and efficient.

Is there any pythonic or better way to do this?

I expect my output to be like below

CodePudding user response：

One idea is add 1 for next quarter, then use Series.dt.strftime for custom string Q1, Q2, Q3, Q4:

df['ques_date'] = pd.to_datetime(df['ques_date'], dayfirst=True)

df['act_qtr'] = df['ques_date'].dt.to_period('Q').add(1).dt.strftime('Q%q')
print (df)
   stud_id  ques_date act_qtr
0      101 2020-11-13      Q1
1      101 2018-01-10      Q2
2      101 2017-11-11      Q1
3      101 2016-03-27      Q2
4      101 2010-05-13      Q3
5      101 2008-11-10      Q1
6      101 2007-01-11      Q2
7      101 2006-02-27      Q2