How to convert TZ-format string with pandas?-CodePudding

Here is my original dataframe:

        creationDate

0       2022-06-02T12:41:47.498Z
1       2022-06-02T12:45:13.994Z
2       2022-06-02T12:58:57.684Z
3       2022-06-02T13:24:59.379Z
4       2022-06-02T13:29:57.304Z

I want to transform it this way:

        creationDate

0       2022-06-02
1       2022-06-02
2       2022-06-02
3       2022-06-02
4       2022-06-02

Here is what I do:

df["creationDate"] = pd.to_datetime(df["creationDate"]).dt.strftime("%Y-%m-%d")

Or:

df["creationDate"] = df["creationDate"].apply(lambda x: x[:10])

Which is working.

But, I feel like there is another easier way.

How would you do it?

CodePudding user response：

I would suggest sticking with the first option. For the second option, you can use

df["creationDate"].str[:10]

instead. I don't think there are any better solutions.

CodePudding user response：

Your first method is the right way for me, however you can use:

>>> pd.to_datetime(df['creationDate']).dt.date
0    2022-06-02
1    2022-06-02
2    2022-06-02
3    2022-06-02
4    2022-06-02
Name: creationDate, dtype: object  # <- not a datetime64 but a string

If you want to keep the column as DatetimeIndex, use:

>>> pd.to_datetime(df['creationDate']).dt.tz_localize(None).dt.normalize()
0   2022-06-02
1   2022-06-02
2   2022-06-02
3   2022-06-02
4   2022-06-02
Name: creationDate, dtype: datetime64[ns]  # <- now you have a real datetime

As you have iso format date, you have the timezone so remove it (localize) then reset the time part (normalize).