I have a pandas dataframe with numerous columns, one of which is the time in GPS time, like such:

How would I go about converting this to datetime or UTC within Python?

CodePudding user response：

You can use the Pandas .to_datetime() method to do this conversion!

>>> df = pd.DataFrame({"dates": [1635751985, 1635751985, 1635751986]})
>>> df
        dates
0  1635751985
1  1635751985
2  1635751986
>>> pd.to_datetime(df["dates"], unit="s")
0   2021-11-01 07:33:05
1   2021-11-01 07:33:05
2   2021-11-01 07:33:06
Name: dates, dtype: datetime64[ns]

Note that this conversion is from your integer values to storing the values as datetime64[ns]
Once converted, you can control how they're displayed with .dt.strftime() (see How to change the datetime format in Pandas )

CodePudding user response：

This format is called Unix timestamp.

You can convert it to a datetime object like this:

from datetime import datetime

dt = datetime.fromtimestamp(1635751985)

By default, the object will be in your local timezone.

If you want UTC, you can use the pytz library:

from pytz import timezone

dt = datetime.fromtimestamp(1635751985, timezone('UTC'))