DOC: update the pandas.DataFrame.plot.hist 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.DataFrame.plot.hist) ####################
################################################################################

Draw one histogram of the DataFrame's Series using matplotlib.

A histogram is a representation of the distribution of data.
This function groups the values of all given Series in the DataFrame
into bins, and draws all bins in only one matplotlib.AxesSubplot. This
is useful when the DataFrame's Series are in a similar scale.

Parameters
----------
by : str
    Column in the DataFrame to group by.
bins : int, default 10
    Number of histogram bins to be used.
**kwds : optional
    Parameters to pass on to :meth:`pandas.DataFrame.plot`.

Returns
-------
axes : matplotlib.AxesSubplot or np.array of them

See Also
--------
:meth:`pandas.DataFrame.hist` : Draw histograms per DataFrame's Series.
:meth:`pandas.Series.hist` : Draw a histogram with Series' data.

Examples
--------

When using values between 0 and 3, calling hist() with bins = 3 will
create three bins: one that groups values between 0 and 1, another
for values between 1 and 2, and another for values between 2 and 3.
We use alpha parameter to be able to see overlapping columns.

.. plot::
    :context: close-figs

    >>> df = pd.DataFrame({
    ...     'length': [ 1.5, 0.5, 1.2, 0.9, 3],
    ...     'width': [ 0.7, 0.2, 0.15, 0.2,  1.1]
    ...     }, index= ['pig', 'rabbit', 'duck', 'chicken', 'horse'])
    >>> hist = df.plot.hist(bins = 3, xticks = range(4), alpha = 0.5)

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

Docstring for "pandas.DataFrame.plot.hist" correct. :)


```
