Convert integer to datetime in pandas dataframe

Question

I used pd.to_numeric (df['dates'], downcast = 'integer') to convert a datetime64 to int64 but if I want to convert it back to datetime format, what should I do? Earlier it was in format: 2020-02-19 but after conversion it is now 1582070400000000000. I can't find a way to revert it back to datetime64.

And you didn't consider reading up on documentation how to convert to a datetime in Pandas ( pandas.pydata.org/docs/reference/api/… ). Say, pd.to_datetime(1582070400000000000)? — 9769953
– 9769953, Commented Jun 25, 2021 at 10:29
pd.to_datetime works for me, pd.Timestamp(1582070400000000000) also works. — Umar.H
– Umar.H, Commented Jun 25, 2021 at 10:31

Søren · Accepted Answer · 2021-06-25 10:37:04Z

Pandas to_datatime does the trick

See example:

import pandas as pd
# Example DataFrame
df = pd.DataFrame({'dates' : pd.date_range('01-01-2021','01-10-2021',freq='D')})
# To numeric, as you did
df['numeric'] = pd.to_numeric (df['dates'] , downcast = 'integer')
# Back to date
df['back_do_date'] = pd.to_datetime( df['numeric'] )

gives the DataFrame: df

    dates       numeric             back_do_date
0   2021-01-01  1609459200000000000 2021-01-01
1   2021-01-02  1609545600000000000 2021-01-02
2   2021-01-03  1609632000000000000 2021-01-03
3   2021-01-04  1609718400000000000 2021-01-04
4   2021-01-05  1609804800000000000 2021-01-05
5   2021-01-06  1609891200000000000 2021-01-06
6   2021-01-07  1609977600000000000 2021-01-07
7   2021-01-08  1610064000000000000 2021-01-08
8   2021-01-09  1610150400000000000 2021-01-09
9   2021-01-10  1610236800000000000 2021-01-10

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Convert integer to datetime in pandas dataframe

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Pandas to_datatime does the trick

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