How To Expand A Df By Different Dict As Columns?

I have a df with different dicts as entries in a column, in my case column 'information'. I would like to expand the df by all possible dict.keys(), something like that: import pan

Solution 1:

Another approach would be using pandas.DataFrame.from_records:

import pandas as pd

new = pd.DataFrame.from_records(df.pop('information').apply(lambda x: {} if pd.isna(x) else x))
new = pd.concat([df, new], 1)
print(new)

Output:

   cost  id        name  amount   color  shape
0     1   1      banana     NaN  yellow  curve
1     2   2       apple     NaN     red    NaN
2     2   3      orange     NaN     NaN  round
3    10   4  strawberry   500.0     NaN    NaN
4     4   5       toast     NaN     NaN    NaN

Solution 2:

You can use:

d = {k: {} if v != v else v for k, v in df.pop('information').items()}
df1 = pd.DataFrame.from_dict(d, orient='index')
df = pd.concat([df, df1], axis=1)
print(df)
   id        name  cost  shape   color  amount
0   1      banana     1  curve  yellow     NaN
1   2       apple     2    NaN     red     NaN
2   3      orange     2  round     NaN     NaN
3   4  strawberry    10    NaN     NaN   500.0
4   5       toast     4    NaN     NaN     NaN