BUG: escapechar option of to_csv method does not function properly. 
- [x] I have checked that this issue has not already been reported.

- [x] I have confirmed this bug exists on the latest version of pandas.

- [ ] (optional) I have confirmed this bug exists on the master branch of pandas.

---


#### Code Sample, a copy-pastable example

```python
t = pd.DataFrame({0:['"key":"value"'],  1:['mno,'],  2:['abc\\'],  3:['ijk']})
print(t)
#               0     1     2    3
#0  "key":"value"  mno,  abc\  ijk
t.to_csv('test.csv', header=None, escapechar='\\')
# cat test.csv
# 0,"""key"":""value""","mno,","abc\",ijk
t = pd.read_csv('test.csv', header=None, escapechar='\\')
```

#### Problem description

The `read_csv` cannot parse the file, and produce an `ParseError`
```sh
....ParserError: Error tokenizing data. C error: EOF inside string starting at row 0
```
This is because the third column with value `"abc\"`, in which the `\` is a normal character in the string, is not handled properly. With `escapechar='\\'` set for `to_csv`, the value  `abc\` is quoted in the output `test.csv` file as:
```
0,"""key"":""value""","mno,","abc\",ijk
```
As a result the escapechar can be parsed as normal character if we read it by using `read_csv` without  `escapechar='\\'` . **However, this is not compatible with `read_csv` with  `escapechar='\\'` , as it will render the `\"` as a single normal character `"`, thus the quoting pair of this column is missing the end quote char, and hence the above error occurs.**  

#### Expected Output

When writing file with`to_csv`, the `\` specified as escapechar should be rendered as `\\` in the output file, instead of quote the whole string with quotechar `"..."`. In this way, the meaning of `escapechar` option  in `to_csv` and `read_csv` would be consistent, i.e., if we write with `escapechar` , the we read with `escapechar` ( otherwise the `\\`  is read as two normal characters, without error occuring).

#### Output of ``pd.show_versions()``

<details>

python           : 3.7.6.final.0
python-bits      : 64
OS               : Windows
OS-release       : 10
pandas           : 1.0.3
numpy            : 1.18.1
pytz             : 2019.3
dateutil         : 2.8.1

</details>
