Can't configure read_csv correctly when headers are on different lines of csv

I had a script that worked fine in PyCharm until I uninstalled/reinstalled Anaconda. Now I'm getting all kinds of errors.

One of them I've isolated to a read_csv that's not reading as I expected.

The formatted csv looks like this:

The raw .csv file looks like this:

Price,Adj Close,Close,High,Low,Open,VolumeTicker,^BVSP,^BVSP,^BVSP,^BVSP,^BVSP,^BVSPDate,,,,,,,2014-01-02,50341.0,50341.0,51656.0,50246.0,51522.0,34763002014-01-03,50981.0,50981.0,50981.0,50269.0,50348.0,73604002014-01-06,50974.0,50974.0,51002.0,50451.0,50980.0,37278002014-01-07,50430.0,50430.0,51478.0,50429.0,50982.0,3339500

My question: How should I read_csv if I want the dataframe to have a datetime index called 'Date' (where the text I want to use in the first column, third row) and columns called Adj Close, Close, High, Low, Open, Volume (which are in the first row, columns 2-7)

Is there any way I can do it in one line, or do I need to read using the first row as headers, then rename Price to Date?

What I want the df to look like is:

I'm using this code, which works, but it seems clumsy. Is there a simpler way?

idx_df = pd.read_csv(            f'{data_folder}/INDEX_{idx_code}.csv',            header=None,            skiprows=3,  #  data starts on row 4            names=['Date', 'Adj Close', 'Close', 'High', 'Low', 'Open', 'Volume'],            index_col='Date'        )        idx_df.index = pd.to_datetime(idx_df.index, errors='coerce')  # Try this to remove error