DOC: update the aggregate 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"
- [ ] 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>`
- [ ] 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.aggregate) ####################
################################################################################

Aggregate using one or multiple operations along the specified axis.

.. versionadded:: 0.20.0

Parameters
----------
func : function, string, dictionary, or list of string/functions
    Function to use for aggregating the data. If a function, must either
    work when passed a DataFrame or when passed to DataFrame.apply. For
    a DataFrame, can pass a dict, if the keys are DataFrame column names.

    Accepted combinations are:

    - string function name.
    - function.
    - list of functions.
    - dict of column names -> functions (or list of functions).
axis : {0 or 'index', 1 or 'columns'}, default 0
    - 0 or 'index': apply function to each column.
    - 1 or 'columns': apply function to each row.
args
    Optional positional arguments to pass to the function.
kwargs
    Optional keyword arguments to pass to the function.

Returns
-------
aggregated : DataFrame

Notes
-----
`agg` is an alias for `aggregate`. Use the alias.

Notes
-----
The default behavior of aggregating over the axis 0 is different from
`numpy` functions `mean`/`median`/`prod`/`sum`/`std`/`var`, where the
default is to compute the aggregation of the flattened array (e.g.,
`numpy.mean(arr_2d)` as opposed to `numpy.mean(arr_2d, axis=0)`).

`agg` is an alias for `aggregate`. Use the alias.

Examples
--------

>>> df = df = pd.DataFrame([[1,2,3],
...                         [4,5,6],
...                         [7,8,9],
...                         [np.nan, np.nan, np.nan]],
...                        columns=['A', 'B', 'C'])

Aggregate these functions across all columns

>>> df.aggregate(['sum', 'min'])
        A     B     C
sum  12.0  15.0  18.0
min   1.0   2.0   3.0

Different aggregations per column

>>> df.aggregate({'A' : ['sum', 'min'], 'B' : ['min', 'max']})
        A    B
max   NaN  8.0
min   1.0  2.0
sum  12.0  NaN

See also
--------
pandas.DataFrame.apply : Perform any type of operations.
pandas.DataFrame.transform : Perform transformation type operations.
pandas.DataFrame.groupby.aggregate : Perform aggregation type operations
    over groups.
pandas.DataFrame.resample.aggregate : Perform aggregation type operations
    over resampled bins.
pandas.DataFrame.rolling.aggregate : Perform aggregation type operations
    over rolling window.

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

Errors found:
	Errors in parameters section
		Parameter "axis" description should start with capital letter
		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.

- args and kwargs have no type
- axis : {0 or 'index', 1 or 'columns'}, default 0

This PR has been made in collaboration with @rochamatcomp

Question to reviewers: we have added to the docstring the parameter `axis` because this is appropriate for DataFrame. However this dosctring is generic (shared with Series, groupby, window and resample) and the parameter `axis` is wrong for them (for Series the parameter has only one possible value). What should be the right way to fix this?
