DOC: Improved the docstring of pandas.Series.truncate
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.truncate) ######################
################################################################################

Truncate a DataFrame/Series before/after some index value.

If the axis contains only datetime values,
before/after parameters are converted to datetime values.

Parameters
----------
before : date, string, int
    Truncate all rows before this index value.
after : date, string, int
    Truncate all rows after this index value.
axis : {0 or 'index', 1 or 'columns'}
    Default is stat axis for given data type (0 for Series and
    DataFrames, 1 for Panels).
copy : boolean, default is True,
    Return a copy of the truncated section.

Returns
-------
truncated : type of caller

See Also
--------
DataFrame.truncate : Truncate a DataFrame before/after some index value.
Series.truncate : Truncate a Series before/after some index value.

Examples
--------
>>> df = pd.DataFrame({'A': ['a', 'b', 'c', 'd', 'e'],
...                    'B': ['f', 'g', 'h', 'i', 'j'],
...                    'C': ['k', 'l', 'm', 'n', 'o']},
...                    index=[1, 2, 3, 4, 5])
>>> df.truncate(before=2, after=4)
   A  B  C
2  b  g  l
3  c  h  m
4  d  i  n
>>> df = pd.DataFrame({'A': [1, 2, 3, 4, 5],
...                    'B': [6, 7, 8, 9, 10],
...                    'C': [11, 12, 13, 14, 15]},
...                    index=['a', 'b', 'c', 'd', 'e'])
>>> df.truncate(before='b', after='d')
   A  B   C
b  2  7  12
c  3  8  13
d  4  9  14

The index values in ``truncate`` can be datetimes or string
dates. Note that ``truncate`` assumes a 0 value for any unspecified
date component in a ``DatetimeIndex`` in contrast to slicing which
returns any partially matching dates.

>>> dates = pd.date_range('2016-01-01', '2016-02-01', freq='s')
>>> df = pd.DataFrame(index=dates, data={'A': 1})
>>> df.truncate('2016-01-05', '2016-01-10').tail()
                     A
2016-01-09 23:59:56  1
2016-01-09 23:59:57  1
2016-01-09 23:59:58  1
2016-01-09 23:59:59  1
2016-01-10 00:00:00  1
>>> df.loc['2016-01-05':'2016-01-10', :].tail()
                     A
2016-01-10 23:59:55  1
2016-01-10 23:59:56  1
2016-01-10 23:59:57  1
2016-01-10 23:59:58  1
2016-01-10 23:59:59  1

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

Docstring for "pandas.Series.truncate" correct. :)
```
