How to create a dataframe with date range as values in a column?

Question

I have three variables

csiti - 23454 : (integer)

units - [ 11,22,33,44,55,66,77] : (integer list which is of specific length 'n' always )

begin_date - '2019-10-16' : (string)

How do I create a dataframe from this data like

csiti     units forecast_date
1928422     11    2019-10-16  
1928422     22    2019-10-17  
1928422     33    2019-10-18  
1928422     44    2019-10-19  
1928422     55    2019-10-20  
1928422     66    2019-10-21  
1928422     77    2019-10-22

The forecast_date column should be future dates starting from begin_date value.

`df.explode('units')`, then add the respective date range to the forecast date? — Quang Hoang, Oct 31 '19 at 13:34

jezrael · Accepted Answer · 2019-10-31T13:38:13.990

16

Use DataFrame constructor with date_range for datetimes with periods parameter by length of values in list units:

csiti = 23454
units = [11,22,33,44,55,66,77]
begin_date = '2019-10-16'

df = pd.DataFrame({'csiti':csiti, 
                   'units':units,
                   'forecast_date':pd.date_range(begin_date, periods=len(units))})
print (df.head(10))
   csiti  units forecast_date
0  23454     11    2019-10-16
1  23454     22    2019-10-17
2  23454     33    2019-10-18
3  23454     44    2019-10-19
4  23454     55    2019-10-20
5  23454     66    2019-10-21
6  23454     77    2019-10-22

edited Oct 31 '19 at 13:38

answered Oct 31 '19 at 13:34

jezrael

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2

I think OP wants each units for a future forecast_date. I might be wrong though. – Quang Hoang Oct 31 '19 at 13:37
1

Sorry. My bad. Updated the expected output in the question. – Underoos Oct 31 '19 at 13:37
1

@SukumarRdjf - Answer was changed. – jezrael Oct 31 '19 at 13:40

How to create a dataframe with date range as values in a column?

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