DOC: update the DataFrame.eval() 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.eval)  ######################
################################################################################

Evaluate a string describing operations on DataFrame columns.

Operates on columns only, not specific rows or elements.  This allows
`eval` to run arbitrary code, which can make you vulnerable to code
injection if you pass user input to this function.

Parameters
----------
expr : str
    The expression string to evaluate.
inplace : bool, default False
    If the expression contains an assignment, whether to perform the
    operation inplace and mutate the existing DataFrame. Otherwise,
    a new DataFrame is returned.

    .. versionadded:: 0.18.0.
kwargs : dict
    See the documentation for :func:`~pandas.eval` for complete details
    on the keyword arguments accepted by
    :meth:`~pandas.DataFrame.query`.

Returns
-------
ndarray, scalar, or pandas object
    The result of the evaluation.

See Also
--------
DataFrame.query : Evaluates a boolean expression to query the columns
    of a frame.
DataFrame.assign : Can evaluate an expression or function to create new
    values for a column.
pandas.eval : Evaluate a Python expression as a string using various
    backends.

Notes
-----
For more details see the API documentation for :func:`~pandas.eval`.
For detailed examples see :ref:`enhancing performance with eval
<enhancingperf.eval>`.

Examples
--------
>>> df = pd.DataFrame({'A': range(1, 6), 'B': range(10, 0, -2)})
>>> df
   A   B
0  1  10
1  2   8
2  3   6
3  4   4
4  5   2
>>> df.eval('A + B')
0    11
1    10
2     9
3     8
4     7
dtype: int64

Assignment is allowed and by default the original DataFrame is not
modified.

>>> df.eval('C = A + B')
   A   B   C
0  1  10  11
1  2   8  10
2  3   6   9
3  4   4   8
4  5   2   7
>>> df
   A   B
0  1  10
1  2   8
2  3   6
3  4   4
4  5   2

Use inplace=True to modify the original DataFrame.

>>> df.eval('C = A + B', inplace=True)
>>> df
   A   B   C
0  1  10  11
1  2   8  10
2  3   6   9
3  4   4   8
4  5   2   7

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

Docstring for "pandas.DataFrame.eval" correct. :)
```