Writing data frame for future 6 months in pandas for big amount of data-CodePudding

I would like to optimize my program which should check the date and write extra rows which will after all show 6 months with the input date. E.g. if I have date 2021-01-01 for some ID I will get rows with the same ID and date for 6 months in a row with the started one which is JAN 2021 (this is shown in example below).

I have a data frame with two columns: ID and Demand_date as it is in input:

ID         Demand_date
001        2021-01-01
002        2016-03-01
003        2015-10-01

And the output should look like that:

ID         Demand_date
001        2021-01-01
001        2021-02-01
001        2021-03-01
001        2021-04-01
001        2021-05-01
001        2021-06-01
002        2016-03-01
002        2016-04-01
002        2016-05-01
002        2016-06-01
002        2016-07-01
002        2016-08-01
003        2015-10-01
003        2015-11-01
003        2015-12-01
003        2016-01-01
003        2016-02-01
003        2016-03-01

I have too many loops in my program and for 1M of data it is taking too long time.

CodePudding user response：

You could use

You can map a date range, and explode it into a new dataframe

temp = DF["DATE"].map(lambda x: pd.date_range(x, periods=3, freq='D')).reset_index()
temp = temp.rename(columns={"index":"ID"})
temp = temp.explode("DATE")
temp

That results in a daily resample;

I imagine you can figure out the monthly resample.
Hope that helps!