How can I convert my datetime column in pandas all to the same timezone

Question

I have a dataframe with a DataTime column (with Timezone in different formats). It appears like timezone is UTC but I want to convert the column to pd.to_datetime and that is failing. That is problem #1. Since that fails I cannot do any datetime operations on the time period such as group the column by date / figure out the days / group by hour of the day and so on. Here's my dataframe df_res

    DateTime
    2017-11-02 19:49:28-07:00
    2017-11-27 07:32:22-08:00
    2017-12-27 17:01:15-08:00

OUTPUT for the command

      df_res["DateTime"] = df_res["DateTime"].dt.tz_convert('America/New_York')

AttributeError: Can only use .dt accessor with datetimelike values

WHen I convert to datetime

   df_res['DateTime'] = pd.to_datetime(df_res['DateTime'])

ValueError: Tz-aware datetime.datetime cannot be converted to datetime64 unless utc=True

I feel I am going around in circles. I need to convert the column to datetime in order to perform operations & in order to do that I need to have them all the same timezone but I cannot have the same timezone unless it is a datetime object so how can I best approach this. I did refer to previous postings but they seem to convert to datetime as easily as possible:

Convert datetime columns to a different timezone pandas Convert pandas timezone-aware DateTimeIndex to naive timestamp, but in certain timezone

Answer 1

I think that it is not necessary to apply lambdas:

df_res['DateTime'] = pd.to_datetime(df_res['DateTime'], utc=True)

documentation: https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.to_datetime.html

Answer 2

You can check this:

df = pd.DataFrame({
    'time': [
        '2017-11-02 19:49:28-08:00', 
        '2017-11-27 07:32:22-07:00', 
        '2017-12-27 17:01:15-07:00'
    ]
})

df['time'] = pd.to_datetime(df['time'])

df['time'].apply(lambda x: pd.to_datetime(x).tz_localize('US/Eastern'))

0   2017-11-03 03:49:28-04:00
1   2017-11-27 14:32:22-05:00
2   2017-12-28 00:01:15-05:00
Name: time, dtype: datetime64[ns, US/Eastern]