["python","pandas","dataframe","timezone","timestamp-with-timezone"]
How to remove timezone from a Timestamp column in pandas

I read Pandas change timezone for forex DataFrame but I'd like to make the time column of my dataframe timezone naive for interoperability with an sqlite3 database. The data in my pandas dataframe is already converted to UTC data, but I do not want to have to maintain this UTC timezone information in the database. Given a sample of the data derived from other sources, it looks like this: print(type(testdata)) print(testdata) print(testdata.applymap(type)) gives: <class 'pandas.core.frame.DataFrame'> time navd88_ft station_id new 0 2018-03-07 01:31:02+00:00 -0.030332 13 5 1 2018-03-07 01:21:02+00:00 -0.121653 13 5 2 2018-03-07 01:26:02+00:00 -0.072945 13 5 3 2018-03-07 01:16:02+00:00 -0.139917 13 5 4 2018-03-07 01:11:02+00:00 -0.152085 13 5 time navd88_ft station_id \ 0 <class 'pandas._libs.tslib.Timestamp'> <class 'float'> <class 'int'> 1 <class 'pandas._libs.tslib.Timestamp'> <class 'float'> <class 'int'> 2 <class 'pandas._libs.tslib.Timestamp'> <class 'float'> <class 'int'> 3 <class 'pandas._libs.tslib.Timestamp'> <class 'float'> <class 'int'> 4 <class 'pandas._libs.tslib.Timestamp'> <class 'float'> <class 'int'> new 0 <class 'int'> 1 <class 'int'> 2 <class 'int'> 3 <class 'int'> 4 <class 'int'> but newstamp = testdata['time'].tz_convert(None) gives an eventual error: TypeError: index is not a valid DatetimeIndex or PeriodIndex What do I do to replace the column with a timezone naive timestamp?
The column must be a datetime dtype, for example after using pd.to_datetime. Then, you can use tz_localize to change the time zone, a naive timestamp corresponds to time zone None: testdata['time'].dt.tz_localize(None) Unless the column is an index (DatetimeIndex), the .dt accessor must be used to access pandas datetime functions.