Doc: Update the DatetimeIndex.strftime docstring
State: closed

Checklist for the pandas documentation sprint (ignore this if you are doing
an unrelated PR):

- [ ] PR title is "DOC: update the <your-function-or-method> 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):

Labels:
name: Docs
name: Datetime
description: Datetime data dtype

Comments:
# [Codecov](https://codecov.io/gh/pandas-dev/pandas/pull/20103?src=pr&el=h1) Report
> Merging [#20103](https://codecov.io/gh/pandas-dev/pandas/pull/20103?src=pr&el=desc) into [master](https://codecov.io/gh/pandas-dev/pandas/commit/4131149fa9ac1d6d4a405589a1c6e63187db0662?src=pr&el=desc) will **decrease** coverage by `0.02%`.
> The diff coverage is `n/a`.

[![Impacted file tree graph](https://codecov.io/gh/pandas-dev/pandas/pull/20103/graphs/tree.svg?width=650&height=150&src=pr&token=eZ4WkYLtcO)](https://codecov.io/gh/pandas-dev/pandas/pull/20103?src=pr&el=tree)

```diff
@@            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%)` | :arrow_down: |
| #single | `41.85% <ø> (ø)` | :arrow_up: |

| [Impacted Files](https://codecov.io/gh/pandas-dev/pandas/pull/20103?src=pr&el=tree) | Coverage Δ | |
|---|---|---|
| [pandas/core/indexes/datetimelike.py](https://codecov.io/gh/pandas-dev/pandas/pull/20103/diff?src=pr&el=tree#diff-cGFuZGFzL2NvcmUvaW5kZXhlcy9kYXRldGltZWxpa2UucHk=) | `96.7% <ø> (ø)` | :arrow_up: |
| [pandas/plotting/\_converter.py](https://codecov.io/gh/pandas-dev/pandas/pull/20103/diff?src=pr&el=tree#diff-cGFuZGFzL3Bsb3R0aW5nL19jb252ZXJ0ZXIucHk=) | `65.07% <0%> (-1.74%)` | :arrow_down: |

------

[Continue to review full report at Codecov](https://codecov.io/gh/pandas-dev/pandas/pull/20103?src=pr&el=continue).
> **Legend** - [Click here to learn more](https://docs.codecov.io/docs/codecov-delta)
> `Δ = absolute <relative> (impact)`, `ø = not affected`, `? = missing data`
> Powered by [Codecov](https://codecov.io/gh/pandas-dev/pandas/pull/20103?src=pr&el=footer). Last update [4131149...8decfa7](https://codecov.io/gh/pandas-dev/pandas/pull/20103?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).

thanks @Tushar987