I need to read a CSV file in Pandas which has data in the following format (double 'double quotes' for one of the fields)

```
"column1","column2","column3","column4"
"10",""AB"","ABCD","abcd"
"11",""CD,E"","CDEF","abcd"
"12",""WER"","DEF,31","abcd"

```

I expect the correctly parsed dataframe to be like

```
column1  column2  column3   column4
10       AB       ABCD      abcd
11       "CD,E"   CDEF      abcd
12       WER      "DEF,31"  abcd

```

I tried using 

```
df= pd.read_csv('sample.txt',quotechar='""', quoting=csv.QUOTE_ALL)

```

and

```
df= pd.read_csv('sample.txt',quotechar='"', quoting=csv.QUOTE_ALL)

```

but getting

```
TypeError: "quotechar" must be a 1-character string

```

and

```
pandas.errors.ParserError: Error tokenizing data. C error: Expected 4 fields in line 3, saw 5

```

Is there a way for me to read this file as is without having to preprocess and remove the double 'double quotes' in the data? 

When `column2` has no commas, I'm able to read the data with some extra quotes which I can replace in further processing steps. I'm having parsing problems only when `column2` is having a comma.