Read Nested JSON with pandas.io.json

[palo173]

You can access only some columns of df using:

new_df = df[['Data.Code', 'Data.DateFrom', 'Data.Address']]

- But what about column Data.Address? There is lot of information in one column but not separetly. Instead of {'Street': 'Okružní', 'City': 'Sezimovo Ústí', 'PostCode': '39102'} I want only 2 separate columns Street and City

- And prefix of column is not only Data.xyz but for examlpe Data.snapshots.DateFrom or Data.snapshots.Address.Street etc.

- And it is not better use "df = pd_json.json_normalize" for reading and assigning to "df" only columns which I want, not all columns?

I think this part of code is necessary to modify, but I do not how

df = pd_json.json_normalize(fin, 
                        record_path=['Data','snapshots'],
                        record_prefix = 'Data.',
                        errors = 'ignore'
                        )