Issues with csv double quotes

[snippsat]

Pandas can read table from website with pd.read_html,then no need to do parsing.
Example.

>>> import pandas as pd
...
... df = pd.read_html("https://coinmarketcap.com/currencies/bitcoin/historical-data/?start=20130428&end=20200315")
... df = df[2]

>>> df.head(10)
           Date    Open*     High      Low  Close**       Volume    Market Cap
0  Mar 16, 2020  5385.23  5385.23  4575.36  5014.48  45368026430   91633478850
1  Mar 15, 2020  5201.07  5836.65  5169.28  5392.31  33997889639   98530059890
2  Mar 14, 2020  5573.08  5625.23  5125.07  5200.37  36154506008   95014981944
3  Mar 13, 2020  5017.83  5838.11  4106.98  5563.71  74156772075  101644613038
4  Mar 12, 2020  7913.62  7929.12  4860.35  4970.79  53980357243   90804613601
5  Mar 11, 2020  7910.09  7950.81  7642.81  7911.43  38682762605  144508402671
6  Mar 10, 2020  7922.15  8136.95  7814.76  7909.73  42213940994  144465567734
7  Mar 09, 2020  8111.15  8177.79  7690.10  7923.64  46936995808  144706353758
8  Mar 08, 2020  8908.21  8914.34  8105.25  8108.12  39973102121  148060284561
9  Mar 07, 2020  9121.60  9163.22  8890.74  8909.95  36216930370  162684945903


>>> df.dtypes
Date           object
Open*         float64
High          float64
Low           float64
Close**       float64
Volume          int64
Market Cap      int64
dtype: object


>>> df['High'].max()
20089.0 

Find all types correct except Date,so fix for date would be.

>>> df['Date'] = pd.to_datetime(df['Date'])
>>> df.dtypes
Date          datetime64[ns]
Open*                float64
High                 float64
Low                  float64
Close**              float64
Volume                 int64
Market Cap             int64
dtype: object