Convert dictionary values inside a column of a Dataframe to new separate columns

Question

I have a csv file, and I have put it in a pandas dataframe:

no	data
1	{"age": "30", "sex": "male"}
2	{"age": "26", "sex": "female"}

I would like to create two new columns named 'age' and 'sex' (the dict. keys), then drop the original column so that it looks like this:

no	age	sex
1	30	male
2	26	female

How can I create those two new columns automatically using data from the dictionaries inside of the column 'data'?

So data is a dictionary or a string? – Dani Mesejo Jul 25 '22 at 15:21 — Dani Mesejo, Jul 25 '22 at 15:21
Use `json_normalize`, see duplicate – mozway Jul 25 '22 at 15:21 — mozway, Jul 25 '22 at 15:21

score 0 · Answer 1 · answered Jul 25 '22 at 15:18

We need to convert the dict like column to dict with ast

import ast
df = df.join(df.data.apply(lambda x : pd.Series(ast.literal_eval(x))))
df
Out[69]: 
   no                            data age     sex
0   1    {"age": "30", "sex": "male"}  30    male
1   2  {"age": "26", "sex": "female"}  26  female

Convert dictionary values inside a column of a Dataframe to new separate columns

1 Answers1