How to convert string date column to timestamp in a new column in Python Pandas

Question

I have the following example dataframe:

d = {'col1': ["2022-05-16T12:31:00Z", "2021-01-11T11:32:00Z"]}
df = pd.DataFrame(data=d)
df

    col1
0   2022-05-16T12:31:00Z
1   2021-01-11T11:32:00Z

I need a second column (say col2) which will have the corresponding timestamp value for each col1 date string value from col1.

How can I do that without using a for loop?

Does this answer your question? pandas datetime to unix timestamp seconds — FObersteiner
– FObersteiner, Commented May 16, 2022 at 17:41
@FObersteiner Thank you for your comment. It includes similar solutions to the ones I got here. — edn
– edn, Commented May 16, 2022 at 20:07

Royce Anton Jose · Accepted Answer · 2022-05-16 15:55:02Z

1

Maybe try this?

import pandas as pd
import numpy as np

d = {'col1': ["2022-05-16T12:31:00Z", "2021-01-11T11:32:00Z"]}
df = pd.DataFrame(data=d)

df['col2'] = pd.to_datetime(df['col1'])
df['col2'] = df.col2.values.astype(np.int64) // 10 ** 9

df

edited May 16, 2022 at 15:55

answered May 16, 2022 at 15:49

Royce Anton Jose

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Comments

BENY · Accepted Answer · 2022-05-16 15:45:26Z

1

Let us try to_datetime

df['col2'] = pd.to_datetime(df['col1'])
df
Out[614]: 
                   col1                      col2
0  2022-05-16T12:31:00Z 2022-05-16 12:31:00+00:00
1  2021-01-11T11:32:00Z 2021-01-11 11:32:00+00:00

Update

st = pd.to_datetime('1970-01-01T00:00:00Z')
df['unix'] = (pd.to_datetime(df['col1'])- st).dt.total_seconds()
Out[632]: 
0    1.652704e+09
1    1.610365e+09
Name: col1, dtype: float64

edited May 16, 2022 at 15:45

answered May 16, 2022 at 15:37

BENY

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3 Comments

edn Over a year ago

Thank you for your answer. But I need the timestamp value i.e. 1652706735, not the date object. How can I achieve that?

BENY Over a year ago

@edn check the update

edn Over a year ago

Thank you for the update! Can I somehow use the timetuple() function on the column? I get the "'Series' object has no attribute 'timetuple'" error when I try it.

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