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Pandas DataFrame | to_dict method

Pandas
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Documentation
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DataFrame
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Type Conversion
schedule Jul 1, 2022
Last updated
local_offer PythonPandas
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Pandas DataFrame.to_dict(~) method converts the DataFrame to a Python dictionary or list of dictionaries.

Parameters

1. orient | string | optional

The rule by which to perform the conversion.

When orient="dict" (default):

{
column_1:
index_1: value_1
index_2: value_2
column_2:
...
}

When orient="list":

{
column_1: [value_1, value_2, ...]
column_2: [...]
...
}

When orient="series":

{
column_1: Series(value_1, value_2, ...)
column_2: Series(...)
...
}

When orient="split":

{
"index": [index_1, index_2, ...]
"columns": [column_1, column_2, ...]
"data": [value_1, value_2, ...]
}

When orient="records":

[
{
column_1: value_1
column_2: value_2
...
},{
column_1: value_6
...
},
...
]

When orient="index":

{
index_1: {
column_1: value
column_2: value
...
},
index_2: {
column_6 ...
},
...
}

2. into | class | optional

The collections.abc.Mapping subclass or its instance. This is useful when, instead of the standard Python dict, you want to convert to another type of dictionary such as collections.defaultdict.

Return Value

Depending on the specified orient and into, the return type will vary.

Examples

Consider the following DataFrame:

df = pd.DataFrame({"A":[2,3],"B":[4,5]}, index=["a","b"])
df
A B
a 2 4
b 3 5

Specifying orient

dict

df.to_dict()
{'A': {'a': 2, 'b': 3}, 'B': {'a': 4, 'b': 5}}

list

df.to_dict(orient="list")
{'A': [2, 3], 'B': [4, 5]}

series

df.to_dict(orient="series")
{'A': a 2
b 3
Name: A, dtype: int64,
'B': a 4
b 5
Name: B, dtype: int64}

For your reference, we show the df here again:

df
A B
a 2 4
b 3 5

split

df.to_dict(orient="split")
{'index': ['a', 'b'], 'columns': ['A', 'B'], 'data': [[2, 4], [3, 5]]}

records

df.to_dict(orient="records")
[{'A': 2, 'B': 4}, {'A': 3, 'B': 5}]

index

df.to_dict(orient="index")
{'a': {'A': 2, 'B': 4}, 'b': {'A': 3, 'B': 5}}

Initialising an ordered dictionary

To initialise an ordered dictionary using its class definition:

from collections import OrderedDict
df.to_dict(into=OrderedDict)
OrderedDict([('A', OrderedDict([('a', 2), ('b', 3)])),
('B', OrderedDict([('a', 4), ('b', 5)]))])

Initialising an defaultdict

Unlike ordered dictionaries, the defaultdict must be initialised before we pass it into to_dict(~):

from collections import defaultdict
my_default_dict = defaultdict(list)
df.to_dict(into=my_default_dict)
defaultdict(list,
{'A': defaultdict(list, {'a': 2, 'b': 3}),
'B': defaultdict(list, {'a': 4, 'b': 5})})
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Published by Isshin Inada
Edited by 0 others
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