Creating new columns in pandas with shift and assign-CodePudding

I am trying to make many new columns only by shifting the 'amount_in_group_currency' column, here is my approach:

pay_history_by_interv = (temp.assign(due_amount= temp['amount_in_group_currency'])
                    .assign(period_1= temp['amount_in_group_currency'].shift(1))
                    .assign(period_2= temp['amount_in_group_currency'].shift(2))
                    .assign(period_3= temp['amount_in_group_currency'].shift(3))
                    .assign(period_4= temp['amount_in_group_currency'].shift(4))
                    .assign(period_5= temp['amount_in_group_currency'].shift(5))
                    .assign(period_6= temp['amount_in_group_currency'].shift(6))
                    .drop('amount_in_group_currency', axis=1).fillna(0).reset_index()
                    )

This works for a small number of shifts (e.g 6 in my case) but not for much more, is there a "pandas way" to automate this column making shifts with any desired number?

Thank you

CodePudding user response：

If the question is how to automate creation of columns so you do not have to type them by hand for each one, you can use a loop

n_shifts = 10 # specify how many shifts you want
for n in range(n_shifts):
    temp[f'period_{n 1}'] = temp['amount_in_group_currency'].shift(n 1)

pay_history_by_interv = temp.drop('amount_in_group_currency', axis=1).fillna(0).reset_index()