Classe « DataFrame »

Méthode pandas.DataFrame.from_dict

Signature de la méthode from_dict

def from_dict(data, orient='columns', dtype=None, columns=None) -> 'DataFrame' 

Description

from_dict.__doc__

        Construct DataFrame from dict of array-like or dicts.

        Creates DataFrame object from dictionary by columns or by index
        allowing dtype specification.

        Parameters
        ----------
        data : dict
            Of the form {field : array-like} or {field : dict}.
        orient : {'columns', 'index'}, default 'columns'
            The "orientation" of the data. If the keys of the passed dict
            should be the columns of the resulting DataFrame, pass 'columns'
            (default). Otherwise if the keys should be rows, pass 'index'.
        dtype : dtype, default None
            Data type to force, otherwise infer.
        columns : list, default None
            Column labels to use when ``orient='index'``. Raises a ValueError
            if used with ``orient='columns'``.

        Returns
        -------
        DataFrame

        See Also
        --------
        DataFrame.from_records : DataFrame from structured ndarray, sequence
            of tuples or dicts, or DataFrame.
        DataFrame : DataFrame object creation using constructor.

        Examples
        --------
        By default the keys of the dict become the DataFrame columns:

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

        Specify ``orient='index'`` to create the DataFrame using dictionary
        keys as rows:

        >>> data = {'row_1': [3, 2, 1, 0], 'row_2': ['a', 'b', 'c', 'd']}
        >>> pd.DataFrame.from_dict(data, orient='index')
               0  1  2  3
        row_1  3  2  1  0
        row_2  a  b  c  d

        When using the 'index' orientation, the column names can be
        specified manually:

        >>> pd.DataFrame.from_dict(data, orient='index',
        ...                        columns=['A', 'B', 'C', 'D'])
               A  B  C  D
        row_1  3  2  1  0
        row_2  a  b  c  d