How to convert Pandas timestamps to datetime objects?

Today we’ll learn how to convert timestamps to Python datetime objects. In Pandas we use those terms almost interchangeably though, which renders this a bit confusing.

Creating Pandas timestamps

We can easily create timestamps using the Pandas pd.TimeStamp function. Here is a very simple example to get us started with the tutorial:

import pandas as pd
my_ts = pd.Timestamp('01/01/23')

This will return the following time stamp.

Timestamp('2023-01-01 00:00:00')

Cast single timestamp to date

Next, we would like to generate a Python datetime object from our time stamp.

my_dt = ts.to_pydatetime()

This returns a datetime object:

datetime.datetime(2023, 1, 1, 0, 0)

We can manipulate the datetime object as needed to extract the year, date,month and modify the date format as needed

Convert timestamp Series to a list of Python datetimes

import pandas as pd
time_stamps = pd.Series(pd.date_range(start='01/01/22', end = '01/02/22', freq='6H'))

This will return the following Pandas Series:

0   2022-01-01 00:00:00
1   2022-01-01 06:00:00
2   2022-01-01 12:00:00
3   2022-01-01 18:00:00
4   2022-01-02 00:00:00
dtype: datetime64[ns]

If we look at one of the series rows, we’ll see it’s a Timestamp object:


Will return:

Timestamp('2022-01-01 00:00:00')

We can obviously convert the Timestamp individually, but we would prefer to instead convert the entire Series to a list of Python Datetimes using a list comprehension:

dt_lst= [element.to_pydatetime() for element in list(time_stamps)]

Convert a DataFrame column of timestamps to dates

#create a DataFrame
times = pd.DataFrame (time_stamps, columns=['time_ts']) 
times['time_dt'] = pd.to_datetime(times['time_ts'])

Here’s our result:

02022-01-01 00:00:002022-01-01
12022-01-01 06:00:002022-01-01
22022-01-01 12:00:002022-01-01
32022-01-01 18:00:002022-01-01
42022-01-02 00:00:002022-01-02

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