, a DataFrame) then the result will be passed
        to :meth:`DataFrame.__getitem__`.

        This method uses the top-level :func:`eval` function to
        evaluate the passed query.

        The :meth:`~pandas.DataFrame.query` method uses a slightly
        modified Python syntax by default. For example, the ``&`` and ``|``
        (bitwise) operators have the precedence of their boolean cousins,
        :keyword:`and` and :keyword:`or`. This *is* syntactically valid Python,
        however the semantics are different.

        You can change the semantics of the expression by passing the keyword
        argument ``parser='python'``. This enforces the same semantics as
        evaluation in Python space. Likewise, you can pass ``engine='python'``
        to evaluate an expression using Python itself as a backend. This is not
        recommended as it is inefficient compared to using ``numexpr`` as the
        engine.

        The :attr:`DataFrame.index` and
        :attr:`DataFrame.columns` attributes of the
        :class:`~pandas.DataFrame` instance are placed in the query namespace
        by default, which allows you to treat both the index and columns of the
        frame as a column in the frame.
        The identifier ``index`` is used for the frame index; you can also
        use the name of the index to identify it in a query. Please note that
        Python keywords may not be used as identifiers.

        For further details and examples see the ``query`` documentation in
        :ref:`indexing <indexing.query>`.

        *Backtick quoted variables*

        Backtick quoted variables are parsed as literal Python code and
        are converted internally to a Python valid identifier.
        This can lead to the following problems.

        During parsing a number of disallowed characters inside the backtick
        quoted string are replaced by strings that are allowed as a Python identifier.
        These characters include all operators in Python, the space character, the
        question mark, the exclamation mark, the dollar sign, and the euro sign.
        For other characters that fall outside the ASCII range (U+0001..U+007F)
        and those that are not further specified in PEP 3131,
        the query parser will raise an error.
        This excludes whitespace different than the space character,
        but also the hashtag (as it is used for comments) and the backtick
        itself (backtick can also not be escaped).

        In a special case, quotes that make a pair around a backtick can
        confuse the parser.
        For example, ```it's` > `that's``` will raise an error,
        as it forms a quoted string (``'s > `that'``) with a backtick inside.

        See also the Python documentation about lexical analysis
        (https://docs.python.org/3/reference/lexical_analysis.html)
        in combination with the source code in :mod:`pandas.core.computation.parsing`.

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

        The previous expression is equivalent to

        >>> df[df.A > df.B]
           A  B  C C
        4  5  2    6

        For columns with spaces in their name, you can use backtick quoting.

        >>> df.query('B == `C C`')
           A   B  C C
        0  1  10   10

        The previous expression is equivalent to

        >>> df[df.B == df['C C']]
           A   B  C C
        0  1  10   10
        r½