CODEWITHSUNDEEP
pythonpandasdataframe
Night Walker
Night Walker

Reputation: 21260

Dataframe columns to key value dictionary pair

I have following DataFrame 

                       product             count
Id                                          
175                    '409'                41
175                    '407'                 8
175                    '0.5L'                4
175                    '1.5L'                4
177                    'SCHWEPPES'           6
177                    'TONIC 1L'           4

How I can transform it to following list of dictionaries:

[{'409':41,'407':8, '0.5L':4, '1.5L':4}, 
 {'SCHWEPPES':6, 'TONIC 1L':4}]

Thanks a lot for help.

Upvotes: 1

Views: 1839

Answers (2)

BENY
BENY

Reputation: 323226

Seems like you need groupby the index 

df.groupby(level='Id').apply(lambda x : x.set_index('product').T.to_dict(orient='records'))
Out[124]: 
Id
175    [{''409'': 41, ''407'': 8, ''0.5L'': 4, ''1.5L...
177                 [{''SCHWEPPES'': 6, ''TONIC1L'': 4}]
dtype: object

Output as list

df.groupby(level='Id').apply(lambda x : x.set_index('product').T.to_dict(orient='records')).tolist()
Out[128]: 
[[{"'0.5L'": 4, "'1.5L'": 4, "'407'": 8, "'409'": 41}],
 [{"'SCHWEPPES'": 6, "'TONIC1L'": 4}]]

Making a flat list 

ll=df.groupby(level='Id').apply(lambda x : x.set_index('product').T.to_dict(orient='records')).tolist()


import operator
import functools
functools.reduce(operator.concat, ll)

Out[130]: 
[{"'0.5L'": 4, "'1.5L'": 4, "'407'": 8, "'409'": 41},
 {"'SCHWEPPES'": 6, "'TONIC1L'": 4}]

Upvotes: 1

MaxU - stand with Ukraine
MaxU - stand with Ukraine

Reputation: 210832

In [14]: df.set_index('product').T.to_dict('r')
Out[14]: [{'0.5L': 4, '1.5L': 4, '407': 8, '409': 41, 'SCHWEPPES': 6, 'TONIC 1L': 4}]

Upvotes: 4

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