Update : In DataFrame Class, Columns should not contain duplicate val…
Also updated the Docstring.(#12991)
Hello @MohakGangwani! Thanks for opening this PR. We checked the lines you've touched for [PEP 8](https://www.python.org/dev/peps/pep-0008) issues, and found:

* In the file [`pandas/core/frame.py`](https://github.com/pandas-dev/pandas/blob/ba0c4d7e2101a09bb97d7be08c698119c5d08c27/pandas/core/frame.py):

> [Line 360:70](https://github.com/pandas-dev/pandas/blob/ba0c4d7e2101a09bb97d7be08c698119c5d08c27/pandas/core/frame.py#L360): [W291](https://duckduckgo.com/?q=pep8%20W291) trailing whitespace
> [Line 447:1](https://github.com/pandas-dev/pandas/blob/ba0c4d7e2101a09bb97d7be08c698119c5d08c27/pandas/core/frame.py#L447): [W293](https://duckduckgo.com/?q=pep8%20W293) blank line contains whitespace
> [Line 448:9](https://github.com/pandas-dev/pandas/blob/ba0c4d7e2101a09bb97d7be08c698119c5d08c27/pandas/core/frame.py#L448): [E265](https://duckduckgo.com/?q=pep8%20E265) block comment should start with '# '
> [Line 449:20](https://github.com/pandas-dev/pandas/blob/ba0c4d7e2101a09bb97d7be08c698119c5d08c27/pandas/core/frame.py#L449): [E711](https://duckduckgo.com/?q=pep8%20E711) comparison to None should be 'if cond is not None:'

 I don't think this is addressing the original issue. DataFrames can have columns with duplicate labels, the problem is when trying to modify only one. Wouldn't it be better if pandas didn't allow us to have duplicate column names ? Having columns with same name would rather create confusion for us.
Plus, this may avoid the issue #12991 > Wouldn't it be better if pandas didn't allow us to have duplicate column names ? Having columns with same name would rather create confusion for us.
> Plus, this may avoid the issue #12991

Probably yes, there's a WIP PR about not allowing duplicate labels https://github.com/pandas-dev/pandas/pull/28394 Thanks @MohakGangwani

AFAICT, #28394 would already address the issue of optionally disallowing duplicate column labels. Suddenly raising an exception without any prior warning wouldn't be good form - furthermore, you would need to add tests for this new behaviour.

Closing for now then as this looks like it's inactive and probably not the solution pandas would want to go with