DOC: Improve docstring of Index.delete

[andhikayusup]

• closes DOC: Fix errors in pandas.Index.delete pandanistas/pandanistas_sprint_jakarta2020#13
• tests added / passed
• passes black pandas
• passes git diff upstream/master -u -- "*.py" | flake8 --diff
• whatsnew entry

Output from validate_docstrings.py
################################################################################
####################### Docstring (pandas.Index.delete) #######################
################################################################################

Make new Index with passed location(-s) deleted.

Use array of integer as loc parameter to delete multiple locations.

Parameters

loc : int
Location of item(-s) which will be deleted.

Returns

Index
New Index with passed location(-s) deleted.

See Also

numpy.delete : Delete any rows and column from NumPy array (ndarray).

Examples

idx = pd.Index(['a', 'b', 'c'])
idx.delete(1) # Deleting 'b'
Index(['a', 'c'], dtype='object')
idx = pd.Index(['a', 'b', 'c'])
idx.delete([0, 2])
Index(['b'], dtype='object')

################################################################################
################################## Validation ##################################
################################################################################

[datapythonista]

Looks good, just few minor comments

[datapythonista]

Can you explain this in the parameter description please

[datapythonista]

int or list of int

[datapythonista]

I think you can remove the comment, the example is good enough to be clear that we're deleting b

[pep8speaks]

Hello @andhikayusup! Thanks for updating this PR. We checked the lines you've touched for PEP 8 issues, and found:

There are currently no PEP 8 issues detected in this Pull Request. Cheers! 🍻

Comment last updated at 2020-02-15 12:19:52 UTC

[datapythonista]

Just one comment in a sentence that I think could be improved, but looks good to me.

[datapythonista]

What do you think about the next?

Use a list of locations to delete more than one value at the same time

[andhikayusup]

looks good

[datapythonista]

Thanks!

[simonjayhawkins]

Thanks @andhikayusup