feat(docs/api-standards): fix placeholders in api_standards.rst

[shephinphilip]

PR Description

I have addressed issue #22792, which involved correcting placeholders in the documentation located at https://unify.ai/docs/ivy/overview/related_work/api_standards.html.

Related Issue

Close #22792

Checklist

• Corrected the placeholders in the documentation.
• Verified that the content accurately reflects the changes made.
• Checked the documentation for any additional issues or inconsistencies.

Socials:

N/A

[github-actions]

Thanks for contributing to Ivy! 😊👏
Here are some of the important points from our Contributing Guidelines 📝:
1. Feel free to ignore the run_tests (1), run_tests (2), … jobs, and only look at the display_test_results job. 👀 It contains the following two sections:
- Combined Test Results: This shows the results of all the ivy tests that ran on the PR. ✔️
- New Failures Introduced: This lists the tests that are passing on main, but fail on the PR Fork. Please try to make sure that there are no such tests. 💪
2. The lint / Check formatting / check-formatting tests check for the formatting of your code. 📜 If it fails, please check the exact error message in the logs and fix the same. ⚠️🔧
3. Finally, the test-docstrings / run-docstring-tests check for the changes made in docstrings of the functions. This may be skipped, as well. 📚
Happy coding! 🎉👨‍💻

[shephinphilip]

@YushaArif99 , Could You please review this pull request.

[YushaArif99]

Hi @shephinphilip

Apologies for the delay in review. Have been a little swamped with work recently and so haven't had the time to review any PRs 😅

Have left a comment below. Could you kindly look into it. Thanks 🙂

[shephinphilip]

@YushaArif99

Is this okay ? like this

Framework	Functions Defined in Array API Standard
NumPy	all, any, argmax, argmin, around, clip, cumprod, cumsum, max,
	mean, min, prod, round, std, sum, var
-------------	------------------------------------------------------------------
TensorFlow	cast, clip_by_value, equal, greater, greater_equal, less,
	less_equal, maximum, minimum, not_equal, ones_like, reshape,
	sum
-------------	------------------------------------------------------------------
PyTorch	abs, add, mean, max, min, pow, sum
_____________	__________________________________________________________________

Note: Instead of Pandas, it's recommended to utilize deep learning frameworks such as JAX or PaddlePaddle. The functions listed in this table are not defined in the Array API Standard but are part of the Functional API of these frameworks.

[vedpatwardhan]

lgtm! Feel free to merge the PR, thanks @Ishticode @shephinphilip 😄