Classe « DataFrame »

Méthode pandas.DataFrame.from_records

Signature de la méthode from_records

def from_records(data, index=None, exclude=None, columns=None, coerce_float=False, nrows=None) -> 'DataFrame' 

Description

from_records.__doc__

        Convert structured or record ndarray to DataFrame.

        Creates a DataFrame object from a structured ndarray, sequence of
        tuples or dicts, or DataFrame.

        Parameters
        ----------
        data : structured ndarray, sequence of tuples or dicts, or DataFrame
            Structured input data.
        index : str, list of fields, array-like
            Field of array to use as the index, alternately a specific set of
            input labels to use.
        exclude : sequence, default None
            Columns or fields to exclude.
        columns : sequence, default None
            Column names to use. If the passed data do not have names
            associated with them, this argument provides names for the
            columns. Otherwise this argument indicates the order of the columns
            in the result (any names not found in the data will become all-NA
            columns).
        coerce_float : bool, default False
            Attempt to convert values of non-string, non-numeric objects (like
            decimal.Decimal) to floating point, useful for SQL result sets.
        nrows : int, default None
            Number of rows to read if data is an iterator.

        Returns
        -------
        DataFrame

        See Also
        --------
        DataFrame.from_dict : DataFrame from dict of array-like or dicts.
        DataFrame : DataFrame object creation using constructor.

        Examples
        --------
        Data can be provided as a structured ndarray:

        >>> data = np.array([(3, 'a'), (2, 'b'), (1, 'c'), (0, 'd')],
        ...                 dtype=[('col_1', 'i4'), ('col_2', 'U1')])
        >>> pd.DataFrame.from_records(data)
           col_1 col_2
        0      3     a
        1      2     b
        2      1     c
        3      0     d

        Data can be provided as a list of dicts:

        >>> data = [{'col_1': 3, 'col_2': 'a'},
        ...         {'col_1': 2, 'col_2': 'b'},
        ...         {'col_1': 1, 'col_2': 'c'},
        ...         {'col_1': 0, 'col_2': 'd'}]
        >>> pd.DataFrame.from_records(data)
           col_1 col_2
        0      3     a
        1      2     b
        2      1     c
        3      0     d

        Data can be provided as a list of tuples with corresponding columns:

        >>> data = [(3, 'a'), (2, 'b'), (1, 'c'), (0, 'd')]
        >>> pd.DataFrame.from_records(data, columns=['col_1', 'col_2'])
           col_1 col_2
        0      3     a
        1      2     b
        2      1     c
        3      0     d