DOC: update the Series.between docstring
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.between)  ######################
################################################################################

Return boolean Series equivalent to left <= series <= right.

This function returns a boolean vector containing `True` wherever the
corresponding Series element is between the boundary values `left` and
`right`. NA values are treated as `False`.

Parameters
----------
left : scalar
    Left boundary.
right : scalar
    Right boundary.
inclusive : bool, default True
    Include boundaries.

Returns
-------
is_between : Series

Examples
--------

>>> s = pd.Series([2, 0, 4, 8, np.nan])

Boundary values are included by default:

>>> s.between(1, 4)
0     True
1    False
2     True
3    False
4    False
dtype: bool

With `inclusive` set to `False` boundary values are excluded:

>>> s.between(1, 4, inclusive=False)
0     True
1    False
2    False
3    False
4    False
dtype: bool

`left` and `right` can be any scalar value:

>>> s = pd.Series(['Alice', 'Bob', 'Carol', 'Eve'])
>>> s.between('Anna', 'Daniel')
0    False
1     True
2     True
3    False
dtype: bool

See Also
--------
DataFrame.query : Query the columns of a frame with a boolean
    expression.

################################################################################
################################## Validation ##################################
################################################################################

Docstring for "pandas.Series.between" correct. :)
```

Labels:

Comments:
Hello @mrw34! Thanks for updating the PR.



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

##### Comment last updated on March 24, 2018 at 07:57 Hours UTC
# [Codecov](https://codecov.io/gh/pandas-dev/pandas/pull/20443?src=pr&el=h1) Report
> Merging [#20443](https://codecov.io/gh/pandas-dev/pandas/pull/20443?src=pr&el=desc) into [master](https://codecov.io/gh/pandas-dev/pandas/commit/cdfce2b0ad99f7faad57cc5247cf33aab5725bed?src=pr&el=desc) will **increase** coverage by `0.02%`.
> The diff coverage is `n/a`.

[![Impacted file tree graph](https://codecov.io/gh/pandas-dev/pandas/pull/20443/graphs/tree.svg?token=eZ4WkYLtcO&width=650&height=150&src=pr)](https://codecov.io/gh/pandas-dev/pandas/pull/20443?src=pr&el=tree)

```diff
@@            Coverage Diff             @@
##           master   #20443      +/-   ##
==========================================
+ Coverage   91.82%   91.85%   +0.02%     
==========================================
  Files         152      152              
  Lines       49248    49231      -17     
==========================================
- Hits        45222    45220       -2     
+ Misses       4026     4011      -15
```

| Flag | Coverage Δ | |
|---|---|---|
| #multiple | `90.23% <ø> (+0.02%)` | :arrow_up: |
| #single | `41.83% <ø> (-0.06%)` | :arrow_down: |

| [Impacted Files](https://codecov.io/gh/pandas-dev/pandas/pull/20443?src=pr&el=tree) | Coverage Δ | |
|---|---|---|
| [pandas/core/series.py](https://codecov.io/gh/pandas-dev/pandas/pull/20443/diff?src=pr&el=tree#diff-cGFuZGFzL2NvcmUvc2VyaWVzLnB5) | `93.84% <ø> (ø)` | :arrow_up: |
| [pandas/core/arrays/base.py](https://codecov.io/gh/pandas-dev/pandas/pull/20443/diff?src=pr&el=tree#diff-cGFuZGFzL2NvcmUvYXJyYXlzL2Jhc2UucHk=) | `83.33% <0%> (-0.82%)` | :arrow_down: |
| [pandas/core/algorithms.py](https://codecov.io/gh/pandas-dev/pandas/pull/20443/diff?src=pr&el=tree#diff-cGFuZGFzL2NvcmUvYWxnb3JpdGhtcy5weQ==) | `94.29% <0%> (-0.07%)` | :arrow_down: |
| [pandas/core/base.py](https://codecov.io/gh/pandas-dev/pandas/pull/20443/diff?src=pr&el=tree#diff-cGFuZGFzL2NvcmUvYmFzZS5weQ==) | `96.78% <0%> (-0.01%)` | :arrow_down: |
| [pandas/core/indexes/base.py](https://codecov.io/gh/pandas-dev/pandas/pull/20443/diff?src=pr&el=tree#diff-cGFuZGFzL2NvcmUvaW5kZXhlcy9iYXNlLnB5) | `96.68% <0%> (-0.01%)` | :arrow_down: |
| [pandas/core/frame.py](https://codecov.io/gh/pandas-dev/pandas/pull/20443/diff?src=pr&el=tree#diff-cGFuZGFzL2NvcmUvZnJhbWUucHk=) | `97.18% <0%> (-0.01%)` | :arrow_down: |
| [pandas/core/generic.py](https://codecov.io/gh/pandas-dev/pandas/pull/20443/diff?src=pr&el=tree#diff-cGFuZGFzL2NvcmUvZ2VuZXJpYy5weQ==) | `95.85% <0%> (ø)` | :arrow_up: |
| [pandas/core/indexes/period.py](https://codecov.io/gh/pandas-dev/pandas/pull/20443/diff?src=pr&el=tree#diff-cGFuZGFzL2NvcmUvaW5kZXhlcy9wZXJpb2QucHk=) | `92.61% <0%> (ø)` | :arrow_up: |
| [pandas/core/reshape/reshape.py](https://codecov.io/gh/pandas-dev/pandas/pull/20443/diff?src=pr&el=tree#diff-cGFuZGFzL2NvcmUvcmVzaGFwZS9yZXNoYXBlLnB5) | `100% <0%> (ø)` | :arrow_up: |
| ... and [6 more](https://codecov.io/gh/pandas-dev/pandas/pull/20443/diff?src=pr&el=tree-more) | |

------

[Continue to review full report at Codecov](https://codecov.io/gh/pandas-dev/pandas/pull/20443?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/20443?src=pr&el=footer). Last update [cdfce2b...b3c44da](https://codecov.io/gh/pandas-dev/pandas/pull/20443?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).

@datapythonista Thanks Marc! Hopefully looking better now...
Thanks @mrw34