DOC: updated the pandas.DataFrame.plot.hexbin 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>`
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Please include the output of the validation script below between the "```" ticks:

```

################################################################################
################### Docstring (pandas.DataFrame.plot.hexbin) ###################
################################################################################

Make hexagonal binning plots.

Make an hexagonal binning plot of *x* versus *y*, where *x*,
*y* are 1-D sequences of the same length, *N*. If *C* is *None*
(the default), this is an histogram of the number of occurrences
of the observations at (x[i],y[i]).

If *C* is specified, specifies values at given coordinates
(x[i],y[i]). These values are accumulated for each hexagonal
bin and then reduced according to *reduce_C_function*, having as default
the numpy's mean function (np.mean). (If *C* is
specified, it must also be a 1-D sequence of the same length
as *x* and *y*.)

Parameters
----------
x : label or position, optional
    Coordinates for x point.
y : label or position, optional
    Coordinates for y point.
C : label or position, optional
    The value at each `(x, y)` point.
reduce_C_function : callable, optional, default `mean`
    Function of one argument that reduces all the values in a bin to
    a single number (e.g. `mean`, `max`, `sum`, `std`).
gridsize : int, optional, default 100
    The number of hexagons in the x-direction.
    The corresponding number of hexagons in the y-direction is chosen
    in a way that the hexagons are approximately regular. Alternatively,
    gridsize can be a tuple with two elements specifying the number of
    hexagons in the x-direction and the y-direction.
kwds : optional
    Keyword arguments to pass on to :py:meth:`pandas.DataFrame.plot`.

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

See Also
--------
matplotlib.pyplot.hexbin : hexagonal binning plot using matplotlib.

Examples
--------

.. plot::
    :context: close-figs

    >>> from  sklearn.datasets import load_iris
    >>> iris = load_iris()
    >>> df = pd.DataFrame(iris.data, columns=iris.feature_names)
    >>> hexbin = df.plot.hexbin(x='sepal length (cm)', y='sepal width (cm)',
    ...                         gridsize=10, cmap='viridis')

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

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


```
thanks to @Renton2017