datetime pandas python timezone type-conversion

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

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

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