CODEWITHSUNDEEP
pythonpandasdatetime
Emi OB
Emi OB

Reputation: 3278

Get all dates between start and end date pandas columns

I'm trying to get a list of dates between two start and end date pandas columns, with individual IDs. I've found an answer that is basically what I'm after (https://stackoverflow.com/a/53409207/14463396) but this only works if the periods between the start and end dates don't overlap, and I can't seem to work out how to adapt this/use an alternative method to get the output I'm after.

Below is an example dataframe:

df = pd.DataFrame({'ID' : [1, 2, 3],
'Start Date': ["2021-06-01", "2021-06-02", "2021-06-04"],
'End Date': ["2021-06-03", "2021-06-05", "2021-06-08"]})

And this is what the desired output should be:

    ID  Start Date    End Date       Dates
0    1  2021-06-01  2021-06-03  2021-06-01
1    1  2021-06-01  2021-06-03  2021-06-02
2    1  2021-06-01  2021-06-03  2021-06-03
3    2  2021-06-02  2021-06-05  2021-06-02
4    2  2021-06-02  2021-06-05  2021-06-03
5    2  2021-06-02  2021-06-05  2021-06-04
6    2  2021-06-02  2021-06-05  2021-06-05
7    3  2021-06-04  2021-06-08  2021-06-04
8    3  2021-06-04  2021-06-08  2021-06-05
9    3  2021-06-04  2021-06-08  2021-06-06
10   3  2021-06-04  2021-06-08  2021-06-07
11   3  2021-06-04  2021-06-08  2021-06-08

Any help greatly appreciated :)

Upvotes: 1

Views: 2025

Answers (1)

BENY
BENY

Reputation: 323226

Try with create the date list then explode

df['Start Date'] = pd.to_datetime(df['Start Date'])
df['End Date'] = pd.to_datetime(df['End Date'])
df['Dates'] = [pd.date_range(x, y) for x , y in zip(df['Start Date'],df['End Date'])]
df = df.explode('Dates')
df
Out[108]: 
   ID Start Date   End Date      Dates
0   1 2021-06-01 2021-06-03 2021-06-01
0   1 2021-06-01 2021-06-03 2021-06-02
0   1 2021-06-01 2021-06-03 2021-06-03
1   2 2021-06-02 2021-06-05 2021-06-02
1   2 2021-06-02 2021-06-05 2021-06-03
1   2 2021-06-02 2021-06-05 2021-06-04
1   2 2021-06-02 2021-06-05 2021-06-05
2   3 2021-06-04 2021-06-08 2021-06-04
2   3 2021-06-04 2021-06-08 2021-06-05
2   3 2021-06-04 2021-06-08 2021-06-06
2   3 2021-06-04 2021-06-08 2021-06-07
2   3 2021-06-04 2021-06-08 2021-06-08

Upvotes: 3

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