Selecing datetime index from a datetime list in pandas

Question

I have a datetime index in pandas:

    High    Low     Open    Close   Volume  Adj Close
Date                        
2021-01-04  14147.950195    13953.750000    14104.349609    14132.900391    495000  14132.900391
2021-01-05  14215.599609    14048.150391    14075.150391    14199.500000    492500  14199.500000
2021-01-06  14244.150391    14039.900391    14240.950195    14146.250000    632300  14146.250000
2021-01-07  14256.250000    14123.099609    14253.750000    14137.349609    559200  14137.349609
2021-01-08  14367.299805    14221.650391    14258.400391    14347.250000    613500  14347.250000
...     ...     ...     ...     ...     ...     ...
2021-06-21  15765.150391    15505.650391    15525.849609    15746.500000    351500  15746.500000
2021-06-22  15895.750000    15752.099609    15840.500000    15772.750000    322200  15772.750000
2021-06-23  15862.950195    15673.950195    15862.799805    15686.950195    287500  15686.950195
2021-06-24  15821.400391    15702.700195    15737.299805    15790.450195    316700  15790.450195
2021-06-25  15870.799805    15772.299805    15839.349609    15860.349609    314600  15860.349609

118 rows × 6 columns

I also have a list of dates in list:

[datetime.date(2021, 1, 4),
 datetime.date(2021, 1, 11),
 datetime.date(2021, 1, 18),
 datetime.date(2021, 1, 25),
 datetime.date(2021, 2, 1),
 datetime.date(2021, 2, 8),
 datetime.date(2021, 2, 15),
 datetime.date(2021, 2, 22),
 datetime.date(2021, 3, 1),
 datetime.date(2021, 3, 8),
 datetime.date(2021, 3, 15),
 datetime.date(2021, 3, 22),
 datetime.date(2021, 3, 29),
 datetime.date(2021, 4, 5),
 datetime.date(2021, 4, 12),
 datetime.date(2021, 4, 19),
 datetime.date(2021, 4, 26),
 datetime.date(2021, 5, 3),
 datetime.date(2021, 5, 10),
 datetime.date(2021, 5, 17),
 datetime.date(2021, 5, 24),
 datetime.date(2021, 5, 31),
 datetime.date(2021, 6, 7),
 datetime.date(2021, 6, 14),
 datetime.date(2021, 6, 21),
 datetime.date(2021, 6, 28),
 datetime.date(2021, 7, 5),
 datetime.date(2021, 7, 12),
 datetime.date(2021, 7, 19),
 datetime.date(2021, 7, 26),
 datetime.date(2021, 8, 2),
 datetime.date(2021, 8, 9),
 datetime.date(2021, 8, 16),
 datetime.date(2021, 8, 23),
 datetime.date(2021, 8, 30),
 datetime.date(2021, 9, 6),
 datetime.date(2021, 9, 13),
 datetime.date(2021, 9, 20),
 datetime.date(2021, 9, 27),
 datetime.date(2021, 10, 4),
 datetime.date(2021, 10, 11),
 datetime.date(2021, 10, 18),
 datetime.date(2021, 10, 25),
 datetime.date(2021, 11, 1),
 datetime.date(2021, 11, 8),
 datetime.date(2021, 11, 15),
 datetime.date(2021, 11, 22),
 datetime.date(2021, 11, 29),
 datetime.date(2021, 12, 6),
 datetime.date(2021, 12, 13),
 datetime.date(2021, 12, 20),
 datetime.date(2021, 12, 27)]

Not all the dates are there in the pandas df. What i want to do is select only the dates which are there in the list and not any other dates. The solution which i have come up with is to use a for-loop in datetime range to 'loc' for datetime index in df and append it to another dataframe. I was wondering if there is a simpler way to do this?

Mustafa Aydın · Accepted Answer · 2021-07-01 19:12:03Z

2

You can use pd.Index.isin to check if your dataframe's index's values are in a given list; this will return a True/ False array with which you can index into the original dataframe to select the rows whose indices are in the list:

dates_in_list = df.index.isin(your_list)
new_df = df[dates_in_list]

edited Jul 1, 2021 at 19:12

answered Jul 1, 2021 at 19:02

Mustafa Aydın

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1 Comment

Slartibartfast Over a year ago

Thank you for your help.

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