Fix stubname equal suffix in wide to long function

[tqa236]

• closes BUG: pd.wide_to_long can't handle stubname equal to suffix #46939(Replace xxxx with the GitHub issue number)
• Tests added and passed if fixing a bug or adding a new feature
• All code checks passed.
• Added type annotations to new arguments/methods/functions.
• Added an entry in the latest doc/source/whatsnew/vX.X.X.rst file if fixing a bug or adding a new feature. (Will add after review)

As pandas allows an index in a multiindex and a column to have the same name, I think it's reasonable to allow stubname equal suffix.

However, I think the root cause is in the melt function. It's stated in the docstring that

    value_name : scalar, default 'value'
        Name to use for the 'value' column, can't be an existing column label.

But if value_name == var_name, illogical result is returned. Example:

df = pd.DataFrame(
    {
        "A": {0: "a", 1: "b", 2: "c"},
        "B": {0: 1, 1: 3, 2: 5},
        "C": {0: 2, 1: 4, 2: 6},
    }
)
pd.melt(
    df,
    id_vars=["A"],
    value_vars=["B"],
    var_name="myVarname",
    value_name="myVarname",
)

Result:

I think it's more reasonable to also raise an error if value_name == var_name in melt

[tqa236]

Hi @mroeschke, can you take a look at this PR, please? It should be ready for review.

[datapythonista]

Thanks @tqa236, and sorry for the delay. Not sure if two branches got mixed, seems like half of the changes here are unrelated to the topic of this PR.

[tqa236]

hi @datapythonista, thank you for the review. I also force pushed to the branch because I noticed that you also didn't make any comment on the actual content of the PR. Now this PR should be ready for review.

[datapythonista]

Thanks for the update here @tqa236. The fix you implemented seems a hack, not the proper fix. You should identify what's causing the exception, which seem kind of unrelated, and fix that. Please let me know if you want to have a look more in detail to the actual problem, otherwise we can close this PR.

[tqa236]

thank you for taking a look @datapythonista, unfortunately it's been a year and the context of this issue is no longer fresh in my mind. Let's close this PR.