DOC: update Rolling.std 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.core.window.Rolling.std) ##################
################################################################################

Calculate rolling standard deviation.

Normalized by N-1 by default. This can be changed using the ddof argument.

Parameters
----------
ddof : int, default 1
    Delta Degrees of Freedom.  The divisor used in calculations
    is ``N - ddof``, where ``N`` represents the number of elements.
args
    Under Review.
kwargs
    Under Review.

Returns
-------
Series or DataFrame
    Returned object type is determined by the caller of the rolling
    calculation

See Also
--------
Series.rolling : Calling object with Series data
DataFrame.rolling : Calling object with DataFrames
Series.std : Equivalent method for Series
DataFrame.std : Equivalent method for DataFrame
numpy.std : Equivalent method for Numpy array

Notes
-----
A minimum of 1 periods is required for the rolling calculation.

Examples
--------
The below example will show a rolling example

>>> s = pd.Series((5,5,5,5,6,7,9,10,5,5,5,5))
>>> s.rolling(3).std(1)
0          NaN
1          NaN
2     0.000000
3     0.000000
4     0.577350
5     1.000000
6     1.527525
7     1.527525
8     2.645751
9     2.886751
10    0.000000
11    0.000000
dtype: float64

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

Errors found:
        Errors in parameters section
                Parameter "args" has no type
                Parameter "kwargs" has no type

################################################################################
################# Docstring (pandas.core.window.Expanding.std) #################
################################################################################

Calculate expanding standard deviation.

Normalized by N-1 by default. This can be changed using the ddof argument.

Parameters
----------
ddof : int, default 1
    Delta Degrees of Freedom.  The divisor used in calculations
    is ``N - ddof``, where ``N`` represents the number of elements.
args
    Under Review.
kwargs
    Under Review.

Returns
-------
Series or DataFrame
    Returned object type is determined by the caller of the expanding
    calculation

See Also
--------
Series.expanding : Calling object with Series data
DataFrame.expanding : Calling object with DataFrames
Series.std : Equivalent method for Series
DataFrame.std : Equivalent method for DataFrame
numpy.std : Equivalent method for Numpy array

Notes
-----
A minimum of 1 periods is required for the rolling calculation.

Examples
--------
The below example will show a rolling example

>>> s = pd.Series((5,5,5,5,6,7,9,10,5,5,5,5))
>>> s.rolling(3).std(1)
0          NaN
1          NaN
2     0.000000
3     0.000000
4     0.577350
5     1.000000
6     1.527525
7     1.527525
8     2.645751
9     2.886751
10    0.000000
11    0.000000
dtype: float64

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

Errors found:
        Errors in parameters section
                Parameter "args" has no type
                Parameter "kwargs" has no type
```

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.
