CODEWITHSUNDEEP
pythonpandas
Vamsi Nimmala
Vamsi Nimmala

Reputation: 507

Convert list of dictionaries in a column to multiple columns in same dataframe

My dataframe has a column with list of dictionaries. How can i convert it into a extented dataframe? The dataframe is as shown.

A       B       C
123    abc    [{"name":"john"},{"age":"28"},{"salary":"50000"}]
345    bcd    [{"name":"alex"},{"age":"38"},{"salary":"40000"}]
567    xyx    [{"name":"Dave"},{"age":"82"},{"salary":"30000"}]

I tried the following

> df1=pd.concat([pd.DataFrame(x) for x
> indf['C']],keys=df['A']).reset_index(level=1, drop=True).reset_index()

The Final output looks like

A       B        name   salary   age
123    abc       john    50000   28
345    bcd       alex    40000   38
567    xyx       Dave    30000   82

Upvotes: 1

Views: 1255

Answers (1)

BENY
BENY

Reputation: 323376

IIUC, flatten your list of dicts to one dict, then we using dataframe constructor , and just need concat back to original df 

from itertools import chain
s=pd.DataFrame([dict(chain(*map(dict.items,x))) for x in df.pop('C').tolist()],index=df.index)
s
  age  name salary
0  28  john  50000
1  38  alex  40000
2  82  Dave  30000
s=pd.concat([df,s],1)
s
     A    B age  name salary
0  123  abc  28  john  50000
1  345  bcd  38  alex  40000
2  567  xyx  82  Dave  30000

Data input : 

df.to_dict()
{'A': {0: 123, 1: 345, 2: 567}, 'B': {0: 'abc', 1: 'bcd', 2: 'xyx'}, 'C': {0: [{'name': 'john'}, {'age': '28'}, {'salary': '50000'}], 1: [{'name': 'alex'}, {'age': '38'}, {'salary': '40000'}], 2: [{'name': 'Dave'}, {'age': '82'}, {'salary': '30000'}]}}

Upvotes: 2

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