TST: Testing for mixed int/str Index
- [x] closes #54072 
- [x] [Tests added and passed](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#writing-tests) if fixing a bug or adding a new feature
- [x] All [code checks passed](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#pre-commit).
- [x] Added [type annotations](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#type-hints) to new arguments/methods/functions.
- [x] Added an entry in the latest `doc/source/whatsnew/vX.X.X.rst` file if fixing a bug or adding a new feature.

@xaris96 Can you fix the broken tests and remove all your debug files from this PR please? @datapythonista okay. no problem. i would like to ask about the pr. Do we need to fix the failed tests that already existed to pass the pr? we are new to this and need some guidance :) I think the main idea of the issue is to add the mixed index to the tests, see what it fails, fix the bugs of things that don't work with an index with mix types, and if there are tests that need to be updated, also fix that. Since I think several things will be broken, maybe you can open a first PR with just adding the index with mixed types, then write the failures in a comment to the issue, and then address them in individual PRs. But up to you, whatever you consider it makes things easier. @jbrockmendel anything you'd like to add? @datapythonista  thanks for the advise. it is really helpful! @datapythonista also one more question. is there any problem or do we create a mess if we making changes and update this pr? or this is the common tactic? > @datapythonista also one more question. is there any problem or do we create a mess if we making changes and update this pr? or this is the common tactic?

A PR is mainly a UI for your fork's branch. The usual way of working is to just keep updating your fork's branch, until reviewers are happy and it's merged into the project's main branch. > anything you'd like to add?

seems like a reasonable approach. @mroeschke okay  @datapythonista Hi, I’m encountering an issue with test_rolling_var_numerical_issues, even though I haven't changed anything related to it. It was passing before, but now it's failing. Could you help me understand what might be causing this? @mroeschke Hi.. i also commented above that I’m encountering an issue with test_rolling_var_numerical_issues, even though I haven't changed anything related to it. It was passing before, but now it's failing. Could you help me understand what might be causing this? Thanks for the pull request, but it appears to have gone stale. If interested in continuing, please merge in the main branch, address any review comments and/or failing tests, and we can reopen.