DOC: Improved the docstring of pandas.Series.filter
State: closed

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.filter) #######################
################################################################################

Subset rows or columns of dataframe according to labels in
the specified index.

Note that this routine does not filter a dataframe on its
contents. The filter is applied to the labels of the index.

Parameters
----------
items : list-like
    List of info axis to restrict to (must not all be present).
like : string
    Keep info axis where "arg in col == True".
regex : string (regular expression)
    Keep info axis with re.search(regex, col) == True.
axis : int or string axis name
    The axis to filter on.  By default this is the info axis,
    'index' for Series, 'columns' for DataFrame.

Returns
-------
same type as input object

Examples
--------
>>> df = pd.DataFrame(np.array(([1,2,3],[4,5,6])),
...                   index=['mouse', 'rabbit'],
...                   columns=['one', 'two', 'three'])

>>> # select columns by name
>>> df.filter(items=['one', 'three'])
         one  three
mouse     1      3
rabbit    4      6

>>> # select columns by regular expression
>>> df.filter(regex='e$', axis=1)
         one  three
mouse     1      3
rabbit    4      6

>>> # select rows containing 'bbi'
>>> df.filter(like='bbi', axis=0)
         one  two  three
rabbit    4    5      6

See Also
--------
pandas.DataFrame.loc : Purely label-location based indexer for selection by label.

Notes
-----
The ``items``, ``like``, and ``regex`` parameters are
enforced to be mutually exclusive.

``axis`` defaults to the info axis that is used when indexing
with ``[]``.

################################################################################
################################## Validation ##################################
################################################################################

Docstring for "pandas.Series.filter" 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

Comments:
Hello @ottiP! Thanks for updating the PR.



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

##### Comment last updated on July 07, 2018 at 14:47 Hours UTC
# [Codecov](https://codecov.io/gh/pandas-dev/pandas/pull/20148?src=pr&el=h1) Report
> :exclamation: No coverage uploaded for pull request base (`master@dcbf8b5`). [Click here to learn what that means](https://docs.codecov.io/docs/error-reference#section-missing-base-commit).
> The diff coverage is `n/a`.

[![Impacted file tree graph](https://codecov.io/gh/pandas-dev/pandas/pull/20148/graphs/tree.svg?token=eZ4WkYLtcO&height=150&width=650&src=pr)](https://codecov.io/gh/pandas-dev/pandas/pull/20148?src=pr&el=tree)

```diff
@@            Coverage Diff            @@
##             master   #20148   +/-   ##
=========================================
  Coverage          ?   91.95%           
=========================================
  Files             ?      160           
  Lines             ?    49817           
  Branches          ?        0           
=========================================
  Hits              ?    45810           
  Misses            ?     4007           
  Partials          ?        0
```

| Flag | Coverage Δ | |
|---|---|---|
| #multiple | `90.33% <ø> (?)` | |
| #single | `42.08% <ø> (?)` | |

| [Impacted Files](https://codecov.io/gh/pandas-dev/pandas/pull/20148?src=pr&el=tree) | Coverage Δ | |
|---|---|---|
| [pandas/core/generic.py](https://codecov.io/gh/pandas-dev/pandas/pull/20148/diff?src=pr&el=tree#diff-cGFuZGFzL2NvcmUvZ2VuZXJpYy5weQ==) | `96.45% <ø> (ø)` | |

------

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> **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/20148?src=pr&el=footer). Last update [dcbf8b5...1708c15](https://codecov.io/gh/pandas-dev/pandas/pull/20148?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).

@datapythonista if you want to merge this on green.
thanks @ottiP !