DOC: update the pandas.DataFrame.all 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.all) #######################
################################################################################

Return whether all elements are True over requested axis.

Returns True if all elements along a dataframe
axis are non-zero, not-empty or not-False.
Also note that a series consisting of different data
types returns the first occurence of the non-zero, not-empty
or not-False element.

Parameters
----------
axis : {index (0), columns (1)}
skipna : boolean, default True
    Exclude NA/null values. If an entire row/column is NA, the result
    will be NA.
level : int or level name, default None
    If the axis is a MultiIndex (hierarchical), count along a
    particular level, collapsing into a Series.
bool_only : boolean, default None
    Include only boolean columns. If None, will attempt to use everything,
    then use only boolean data. Not implemented for Series.
**kwargs : any, default None
    Additional keywords have no fect but might be accepted for
    compatibility with numpy.

Returns
-------
all : Series or DataFrame (if level specified)

Examples
--------
First create a pandas dataframe::
    >>> d = {'col1': [True, True], 'col2': [True, False]}
    >>> df = pd.DataFrame(data=d)
    >>> df
       col1   col2
    0  True   True
    1  True  False

Default behaviour checks if column-wise values all return True
    >>> df.all()
    col1     True
    col2    False
    dtype: bool

Adding axis=1 will check row-wise values
    >>> df.all(axis=1)
    0     True
    1    False
    dtype: bool

See also
--------
pandas.DataFrame.any : Checks if one (or more) items return True

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

Errors found:
	Errors in parameters section
		Parameters {'kwargs'} not documented
		Unknown parameters {'**kwargs'}
		Parameter "axis" has no description

```

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.
The axis description is a bug in the string interpollation of %(axis_descr)s
The **kwargs error is a bug in the parameter evaluation 
