Stumped. How do I convert my datetime format to an acceptable format for pandas and mplfinance?

Question

I am trying to use various charting packages for ohlc bar charting. Some success but I keep getting stuck on "TypeError: Expect data.index as DatetimeIndex". The samples that I copy work perfectly fine, like this below:

import yfinance as yf
import mplfinance as mpf
symbol = 'AAPL'
df = yf.download(symbol, period='6mo')
mpf.plot(df, type='candle')

which has the following type of index for the df :

DatetimeIndex(['2022-06-30', '2022-07-01', '2022-07-05', '2022-07-06',
               '2022-12-29', '2022-12-30'],
              dtype='datetime64[ns]', name='Date', length=128, freq=None)

So I am trying to get my dataframe index to look the same, with a DatetimeIndex format. My index looks like this:

0       2022-11-09 14:30:00+00:00
1       2022-11-09 14:35:00+00:00
2       2022-11-09 14:40:00+00:00
3       2022-11-09 14:45:00+00:00
4       2022-11-09 14:50:00+00:00
                  ...            
2299    2022-12-21 20:35:00+00:00
2300    2022-12-21 20:40:00+00:00
2301    2022-12-21 20:45:00+00:00
2302    2022-12-21 20:50:00+00:00
2303    2022-12-21 20:55:00+00:00
Name: date, Length: 2304, dtype: object

Note the default integer index on left. I believe that I dont need to format it exactly the same, as long the internal datatype being datetime64 in a DatetimeIndex form.

thanks for any help.

So I tried this ( and whole lot of other ideas)

    df['timestamp'] = pd.to_datetime(df.date)
    new = pd.DataFrame(index=[df.timestamp])

which gives

MultiIndex([('2022-11-09 14:30:00+00:00',),
            ...
            ('2022-12-21 20:55:00+00:00',)],
           names=['timestamp'], length=2304)

as well as this:

 df['timestamp'] = mpl_dates.datestr2num(df.date)

which gives:

MultiIndex([(19305.604166666668,),
            ( 19305.60763888889,),

            (19347.868055555555,),
            (19347.871527777777,)],
           names=['timestamp'], length=2304)

and neither work.

Am I on the right track, and what is the correct way to do this? How do I get rid of the MultiIndex? And how do I get it to be of type DatetimeIndex?

---

responding to the question on source of data, its from IBKR, using API routines and I am storing the data in an intermediary CSV file. It has the following format:

,date,open,high,low,close,volume,barCount,average 0,2022-11-09 14:30:00+00:00,174.44,174.44,173.8,174.05,994,64,174.408 1,2022-11-09 14:35:00+00:00,174.11,174.38,173.58,173.62,160,123,173.95 2,2022-11-09 14:40:00+00:00,173.59,173.6,173.14,173.56,98,73,173.363 3,2022-11-09 14:45:00+00:00,173.55,174.02,173.52,173.96,88,53,173.716

I was reading in with the following: `bars = pd.read_csv(name, header=0, index_col=0, sep=",")