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

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'>, {...})