We now do the exact same thing for each piece of user JSON data. We call apply on the user series, running the unpack_user_json function, which takes a JSON user object and transforms it into a list of its fields, which we can then inject into a brand new DataFrame, user_df. After that, we'll join user_df back with df, like we did with campaign_df:
#11def unpack_user_json(user): # very optimistic as well, expects user objects # to have all attributes user = json.loads(user.strip()) return [ user['username'], user['email'], user['name'], user['gender'], user['age'], user['address'], ]user_data = df['user'].apply(unpack_user_json)user_cols = [ 'username', 'email', 'name', 'gender', 'age', 'address']user_df = DataFrame( ...
