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# pandas.DataFrame.from_dict

classmethod DataFrame.from_dict(data, orient='columns', dtype=None, columns=None)

  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’].

      Added in version 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