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I have the following code, where I want to determine if a datetime object exists in a data frame.

Here is the code:

df_grid['Date'] = pd.to_datetime(df_grid['Date'])
start_date = df_grid['Date'].iloc[0].date() 
end_date = df_grid['Date'].iloc[-1].date()
current_date = start_date

while current_date < end_date:
    current_date += datetime.timedelta(days=1)
    print(current_date)
    if current_date in df_grid['Date']: continue
    print('not in')

And here is what the dataframe column looks like:

Date
2021-11-01
2021-11-01
2021-11-01
2021-11-02
2021-11-02
2021-11-03
2021-11-03
...

Most of the dates do exist in the column; however, when I run the code, it indicates that none of the dates exist in the dataframe column. I've tried matching with and without .date() and get the same results.

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  • 1
    Did you check data type of the columns after loading the data? You need to pass the date fields to parse_date parameter. Commented Mar 31, 2022 at 15:56
  • I did convert the column to datetime when I imported the csv file. Don't know why they would be different data types, but it's worth a check. Added that bit of code to the question. Commented Mar 31, 2022 at 16:14
  • 1
    Let's take a step back and tell us what you want to do. Are you looking for sequential dates that do not exist between the start_date and end_date? Commented Apr 1, 2022 at 0:23
  • That is exactly what I'm trying to do. And the dates that do exist aren't unique. So say 11/1/2021 is in the df. It will occur multiple times. Commented Apr 1, 2022 at 13:56

1 Answer 1

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Well, this is what I ended up doing to identify missing dates in the dateframe

    while current_date < end_date:
        missing = True
        for row in df_grid.index:
            if current_date == df_grid['Date'].iloc[row]:
                missing = False
                break
        if missing == True:
            [code to execute when date is missing]
        current_date += datetime.timedelta(days=1)

Seems a lot more inefficient than what I originally tried to do, but at least this works.

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