I want to make a new grouped dataframe that has only the dates with holidays in them using .weekday()

So i have a dataframe:

dateRep day month   year    cases   deaths  country_name    Land.area..sq..km.
0   2021-09-21  21  9   2021    1162    7   Austria 82520.0
1   2021-09-20  20  9   2021    1708    7   Austria 82520.0
2   2021-09-19  19  9   2021    2072    5   Austria 82520.0
3   2021-09-18  18  9   2021    2235    9   Austria 82520.0
4   2021-09-17  17  9   2021    2283    8   Austria 82520.0
... ... ... ... ... ... ... ... ...
6145    2021-03-05  5   3   2021    4069    15  Sweden  407310.0
6146    2021-03-04  4   3   2021    4882    19  Sweden  407310.0
6147    2021-03-03  3   3   2021    4873    18  Sweden  407310.0
6148    2021-03-02  2   3   2021    6191    23  Sweden  407310.0
6149    2021-03-01  1   3   2021    668975  13086   Sweden  407310.0
6150 rows × 8 columns

And my target is to make a new dataframe which has only rows that follow specific condition in ‘dateRep’ column

The condition is being a holiday (Sunday or Saturday) using .weekday() function

But the problem is when i tried doing

df.loc[(df['dateRep'].weekday() == 5) or (df['dateRep'].weekday == 6)]

I had an error AttributeError: 'Series' object has no attribute 'weekday'

What do i do? How do i sort out these rows and what is an easier way of doing it?

>Solution :

Convert the dateRep to datetime Series and use .dt. accessor:

df["dateRep"] = pd.to_datetime(df["dateRep"])
print(df.loc[(df["dateRep"].dt.weekday == 5) | (df["dateRep"].dt.weekday == 6)])

Prints:

     dateRep  day  month  year  cases  deaths country_name  Land.area..sq..km.
2 2021-09-19   19      9  2021   2072       5      Austria             82520.0
3 2021-09-18   18      9  2021   2235       9      Austria             82520.0

OR: Use .isin() for shorter code:

df.loc[df["dateRep"].dt.weekday.isin([5, 6])]