How to select pandas dataframe rows between two dates without knowing the exact time

Question

I have a snippet of the dataframe here

  TIME                Value1 Value2
0 2014-10-02 12:45:03   5      6
1 2014-10-02 12:45:05   6      7
2 2014-10-02 12:45:08   3      5
3 2014-10-02 12:45:09   7      4
.....................   ...    ...
45 2014-11-03 00:51:09   7     8

Now, I would like to get all the dataframe rows between 2014-10-02 and 2014-11-02 without knowing the exact time to the second. I tried this method as shown below, but I am getting 0 rows.

start_date = pd.to_datetime('2014-10-02 00:00:01')
end_date = pd.to_datetime('2014-11-02 00:00:01')
df.loc[(df['TIME'] > start_date) & (df['TIME'] < end_date)]

But when I put in an exact datetime value like '2014-10-02 12:45:03' for the start date and end date, I get the output. The data has millions of rows and I could not possibly find out the exact time to the second for the start date and end date. I just need to get rows between two dates.

Anurag Dabas · Accepted Answer · 2021-04-24 15:56:34Z

1

You can try boolean masking:

df.loc[(df['TIME'].dt.date > start_date.date()) & (df['TIME'].dt.date< end_date,date())]

OR

You can also use boolean masking and between() method:

df[df['TIME'].dt.date.between(start_date.date(),end_date.date())]

answered Apr 24, 2021 at 15:56

Anurag Dabas

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1 Comment

SaveEarth Over a year ago

Thank you for the solution and sorry for the late reply. I solved this by setting the time as index which suited my work much better. Anyway thank you for this solution.

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