Doc: Update the DatetimeIndex.strftime docstring

[Tushar987]

Checklist for the pandas documentation sprint (ignore this if you are doing
an unrelated PR):

• PR title is "DOC: update the docstring"
• The validation script passes: scripts/validate_docstrings.py <your-function-or-method>
• The PEP8 style check passes: git diff upstream/master -u -- "*.py" | flake8 --diff
• The html version looks good: python doc/make.py --single <your-function-or-method>
• It has been proofread on language by another sprint participant

Please include the output of the validation script below between the "```" ticks:

################################################################################
################## Docstring (pandas.DatetimeIndex.strftime)  ##################
################################################################################

Convert to specified date_format.

Return an array of formatted strings specified by date_format, which
supports the same string format as the python standard library. Details
of the string format can be found in `python string format doc <https://docs.python.org/3/library/datetime.html#strftime-and-strptime-behavior>`__

Parameters
----------
date_format : str
    Date format string (e.g. "%Y-%m-%d").

Returns
-------
numpy.ndarray
    n-dimensional array of formatted strings

See Also
--------
DatetimeIndex.normalize : Return DatetimeIndex with times to midnight.
DatetimeIndex.round : Round the DatetimeIndex to the specified freq.
DatetimeIndex.floor : Floor the DatetimeIndex to the specified freq.

Examples
--------
>>> data = ['2015-05-01 18:47:05.060000','2014-05-01 18:47:05.110000']
>>> df = pd.DataFrame(data, columns=['date'])
>>> df.date = pd.to_datetime(df.date)
>>> df.date[1]
Timestamp('2014-05-01 18:47:05.110000')
>>> df.date[1].strftime('%d-%m-%Y')
'01-05-2014'
>>> df.date[1].strftime('%B %d, %Y, %r')
'May 01, 2014, 06:47:05 PM'

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

Docstring for "pandas.DatetimeIndex.strftime" correct. :)

If the validation script still gives errors, but you think there is a good reason
to deviate in this case (and there are certainly such cases), please state this
explicitly.

Checklist for other PRs (remove this part if you are doing a PR for the pandas documentation sprint):

[jorisvandenbossche]

Thanks for the PR! Added some comments

[jorisvandenbossche]

Maybe mention it is converted to a string?

[jorisvandenbossche]

I would also link to the similar conversion but other way around: to_datetime

[jorisvandenbossche]

The docstring is from DatetimeIndex. Can you update the example to use that? (so eg create an example dataframe with DatetimeIndex with eg pd.date_range)

[jorisvandenbossche]

I would just say "NumPy array" instead of "n-dimensional", as it is always 1D

[jreback]

@jorisvandenbossche separate issue, this should actually return an Index here.

[codecov]

Codecov Report

Merging #20103 into master will decrease coverage by 0.02%.
The diff coverage is n/a.

@@            Coverage Diff             @@
##           master   #20103      +/-   ##
==========================================
- Coverage   91.72%    91.7%   -0.03%     
==========================================
  Files         150      150              
  Lines       49149    49149              
==========================================
- Hits        45083    45071      -12     
- Misses       4066     4078      +12

Flag	Coverage Δ
#multiple	90.08% <ø> (-0.03%)	⬇️
#single	41.85% <ø> (ø)	⬆️

Impacted Files	Coverage Δ
pandas/core/indexes/datetimelike.py	96.7% <ø> (ø)	⬆️
pandas/plotting/_converter.py	65.07% <0%> (-1.74%)	⬇️

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[jreback]

thanks @Tushar987