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Classe « DataFrame »

Méthode pandas.DataFrame.from_dict

Signature de la méthode from_dict

def from_dict(data: 'dict', orient: 'FromDictOrient' = 'columns', dtype: 'Dtype | None' = None, columns: 'Axes | None' = None) -> 'DataFrame' 

Description

help(DataFrame.from_dict)

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', 'tight'}, 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'.
    If 'tight', assume a dict with keys ['index', 'columns', 'data',
    'index_names', 'column_names'].

    .. versionadded:: 1.4.0
       'tight' as an allowed value for the ``orient`` argument

dtype : dtype, default None
    Data type to force after DataFrame construction, otherwise infer.
columns : list, default None
    Column labels to use when ``orient='index'``. Raises a ValueError
    if used with ``orient='columns'`` or ``orient='tight'``.

Returns
-------
DataFrame

See Also
--------
DataFrame.from_records : DataFrame from structured ndarray, sequence
    of tuples or dicts, or DataFrame.
DataFrame : DataFrame object creation using constructor.
DataFrame.to_dict : Convert the DataFrame to a dictionary.

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

Specify ``orient='tight'`` to create the DataFrame using a 'tight'
format:

>>> data = {'index': [('a', 'b'), ('a', 'c')],
...         'columns': [('x', 1), ('y', 2)],
...         'data': [[1, 3], [2, 4]],
...         'index_names': ['n1', 'n2'],
...         'column_names': ['z1', 'z2']}
>>> pd.DataFrame.from_dict(data, orient='tight')
z1     x  y
z2     1  2
n1 n2
a  b   1  3
   c   2  4

Vous êtes un professionnel et vous avez besoin d'une formation ? RAG (Retrieval-Augmented Generation)
et Fine Tuning d'un LLM Voir le programme détaillé