pyspark.pandas.Series.to_dict

Series.to_dict(into: Type = <class 'dict'>) → collections.abc.Mapping[source]

Convert Series to {label -> value} dict or dict-like object.

Note

This method should only be used if the resulting pandas DataFrame is expected to be small, as all the data is loaded into the driver’s memory.

Parameters
intoclass, default dict

The collections.abc.Mapping subclass to use as the return object. Can be the actual class or an empty instance of the mapping type you want. If you want a collections.defaultdict, you must pass it initialized.

Returns
collections.abc.Mapping

Key-value representation of Series.

Examples

>>> s = ps.Series([1, 2, 3, 4])
>>> s_dict = s.to_dict()
>>> sorted(s_dict.items())
[(0, 1), (1, 2), (2, 3), (3, 4)]
>>> from collections import OrderedDict, defaultdict
>>> s.to_dict(OrderedDict)
OrderedDict([(0, 1), (1, 2), (2, 3), (3, 4)])
>>> dd = defaultdict(list)
>>> s.to_dict(dd)  
defaultdict(<class 'list'>, {...})