cudf.DataFrame.from_dict#

classmethod DataFrame.from_dict(data: dict, orient: str = 'columns', dtype: Dtype | None = None, columns: list | None = None) → DataFrame#

Construct DataFrame from dict of array-like or dicts. Creates DataFrame object from dictionary by columns or by index allowing dtype specification.

Parameters:

datadict: 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’].
dtypedtype, default None: Data type to force, otherwise infer.
columnslist, 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:

>>> import cudf
>>> data = {'col_1': [3, 2, 1, 0], 'col_2': ['a', 'b', 'c', 'd']}
>>> cudf.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': [10, 11, 12, 13]}
>>> cudf.DataFrame.from_dict(data, orient='index')
        0   1   2   3
row_1   3   2   1   0
row_2  10  11  12  13

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

>>> cudf.DataFrame.from_dict(data, orient='index',
...                          columns=['A', 'B', 'C', 'D'])
        A   B   C   D
row_1   3   2   1   0
row_2  10  11  12  13

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']}
>>> cudf.DataFrame.from_dict(data, orient='tight')
z1     x  y
z2     1  2
n1 n2
a  b   1  3
   c   2  4