2017年12月25日月曜日

[Python] 関数のヘルプ

関数の使い方を忘れた際には help 関数を用いることができます.
以下は,前回の投稿で用いた query 関数の使い方を調べてみた結果です.
>>> help(sample_df.query)

Help on method query in module pandas.core.frame:

query(expr, inplace=False, **kwargs) method of pandas.core.frame.DataFrame instance
    Query the columns of a DataFrame with a boolean expression.
    
    Parameters
    ----------
    expr : string
        The query string to evaluate.  You can refer to variables
        in the environment by prefixing them with an '@' character like
        ``@a + b``.
    inplace : bool
        Whether the query should modify the data in place or return
        a modified copy
    
        .. versionadded:: 0.18.0
    
    kwargs : dict
        See the documentation for :func:`pandas.eval` for complete details
        on the keyword arguments accepted by :meth:`DataFrame.query`.
    
    Returns
    -------
    q : DataFrame
    
    See Also
    --------
    pandas.eval
    DataFrame.eval
    
    Notes
    -----
    The result of the evaluation of this expression is first passed to
    :attr:`DataFrame.loc` and if that fails because of a
    multidimensional key (e.g., a DataFrame) then the result will be passed
    to :meth:`DataFrame.__getitem__`.
    
    This method uses the top-level :func:`pandas.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>`.
    
    Examples
    --------
    >>> df = pd.DataFrame(np.random.randn(10, 2), columns=list('ab'))
    >>> df.query('a > b')
    >>> df[df.a > df.b]  # same result as the previous expression
~

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