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Pandas Series: to_dict() function

Series-to_dict() function

The to_dict() function is used to convert Series to {label -> value} dict or dict-like object.

Syntax:

Series.to_dict(self, into=<class 'dict'>)
Pandas Series: str.to_dict() function

Parameters:

Name Description Type/Default Value Required / Optional
into 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. class, default dict Required

Returns: collections.abc.Mapping
Key-value representation of Series.

Example:

Python-Pandas Code:

import numpy as np
import pandas as pd
s = pd.Series([2, 3, 4, 5])
s.to_dict()

Output:

{0: 2, 1: 3, 2: 4, 3: 5}

Python-Pandas Code:

import numpy as np
import pandas as pd
s = pd.Series([2, 3, 4, 5])
from collections import OrderedDict, defaultdict
s.to_dict(OrderedDict)

Output:

OrderedDict([(0, 2), (1, 3), (2, 4), (3, 5)])
Pandas Series: str.to_dict() function

Python-Pandas Code:

import numpy as np
import pandas as pd
s = pd.Series([2, 3, 4, 5])
from collections import OrderedDict, defaultdict
dd = defaultdict(list)
s.to_dict(dd)

Output:

defaultdict(list, {0: 2, 1: 3, 2: 4, 3: 5})

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