DOC: update the series.dt.weekofyear docstring
Checklist for the pandas documentation sprint (ignore this if you are doing
an unrelated PR):

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

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

```
################################################################################
###################### Docstring (pandas.Series.dt.week)  ######################
################################################################################

The week ordinal of the year.

Return the week ordinal of the year. Note that there can be
counter intuitive edge cases around the yearchange. For example
the first of january could be in week 52 of the previous year.
Monday indicates the start of a new week.

See Also
--------
pandas.Series.dt.week : Identical method.
pandas.Series.dt.weekofyear : Identical method.

Returns
-------
ndarray of integers indicating week

Examples
--------
>>> dates = pd.date_range("2016-12-31", "2017-01-08", freq="D")
>>> s = pd.Series(dates)
>>> pd.DataFrame({'date':s, 'week':s.dt.week, 'day':s.dt.strftime("%A")})
        date  week        day
0 2016-12-31    52   Saturday
1 2017-01-01    52     Sunday
2 2017-01-02     1     Monday
3 2017-01-03     1    Tuesday
4 2017-01-04     1  Wednesday
5 2017-01-05     1   Thursday
6 2017-01-06     1     Friday
7 2017-01-07     1   Saturday
8 2017-01-08     1     Sunday

Note what `series.dt.week` and `series.dt.weekofyear` are the same.

>>> s.dt.week
0    52
1    52
2     1
3     1
4     1
5     1
6     1
7     1
8     1
dtype: int64
>>> s.dt.weekofyear
0    52
1    52
2     1
3     1
4     1
5     1
6     1
7     1
8     1
dtype: int64

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

Docstring for "pandas.Series.dt.week" 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.
Hello @koaning! Thanks for updating the PR.



Cheers ! There are no PEP8 issues in this Pull Request. :beers: 

##### Comment last updated on March 10, 2018 at 21:39 Hours UTC Mhm. Strange, locally I didn't seem to have PEP8 issues. Will check!  @TomAugspurger 

- i made a variable for the docstring 
- i reordered the docstring -> see also is now below returns 
- i added a space after the colon  #mybad 
- i confirmed the html still looks good on my end 

you can see the new output of the validation script below:

```
################################################################################
###################### Docstring (pandas.Series.dt.week)  ######################
################################################################################

The week ordinal of the year.

Return the week ordinal of the year. Note that there can be
counter intuitive edge cases around the yearchange. For example
the first of january could be in week 52 of the previous year.
Monday indicates the start of a new week.

Returns
-------
ndarray of integers indicating the week number

See Also
--------
pandas.Series.dt.week : Identical method.
pandas.Series.dt.weekofyear : Identical method.

Examples
--------
>>> dates = pd.date_range("2016-12-31", "2017-01-08", freq="D")
>>> s = pd.Series(dates)
>>> pd.DataFrame({'dt': s, 'week': s.dt.week, 'day': s.dt.strftime("%A")})
          dt  week        day
0 2016-12-31    52   Saturday
1 2017-01-01    52     Sunday
2 2017-01-02     1     Monday
3 2017-01-03     1    Tuesday
4 2017-01-04     1  Wednesday
5 2017-01-05     1   Thursday
6 2017-01-06     1     Friday
7 2017-01-07     1   Saturday
8 2017-01-08     1     Sunday

Note what `series.dt.week` and `series.dt.weekofyear` are the same.

>>> s.dt.week
0    52
1    52
2     1
3     1
4     1
5     1
6     1
7     1
8     1
dtype: int64
>>> s.dt.weekofyear
0    52
1    52
2     1
3     1
4     1
5     1
6     1
7     1
8     1
dtype: int64

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

Docstring for "pandas.Series.dt.week" correct. :)
``` @TomAugspurger should be good to go now.  General question @TomAugspurger : how do we deal with the fact this is docstring for both DatetimeIndex and Series.dt ? Good question. How about just noting that "This method is available on both Series with datetime values or DatetimeIndex" in the extended summary?

And then both in the example. @TomAugspurger will add that. 

@jorisvandenbossche picking up gitter chat here. 

```
weekofyear = _field_accessor('weekofyear', 'woy', _ weekofyear_doc)
week = weekofyear
```

Do we want both properties to have the same docstring? If so, do we mind the verbose example that explains you could do both?  I think same docstring is fine. Closing as stale. Also, the code this PR is based on does not live there anymore.