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You have a DataFrame 'df containing user profile data'. A column named "profile" stores JSON objects with potentially missing fields. These objects might include 'name', 'age', 'location', and 'preferences'. You need to extract the user's name and age. If 'age' is missing, you want to default to 0. Furthermore, you want to filter out any rows where the 'location' field is an empty string. Which combination of Snowpark code snippets will achieve this? (Select all that apply)
Correct Answer: A,B,C
Options A, B and C correctly address the requirements. They extract the name and handle the missing 'age' by defaulting to 0, and filter out rows with an empty string for 'location'. - Option A uses 'nvr to replace NULL 'age' values and ' to filter out empty locations. - Option B uses 'iff to achieve the same age default and sf.lit(")' for filtering. - Option C uses 'coalesce' to default 'age' and 'sf.lengtm to check if the location string has any characters. Option D will filter out all the rows where location is Null and option E uses zeroifnull function which is deprecated, and replaces age which is 0 if column is NULL. and option D wont filer empty string in location