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**Working with Complex Data Types.** Python UDFs can handle complex data types such as arrays, maps, and structs. This opens the door to more sophisticated data transformations. For instance, imagine you want to parse JSON data stored as a string within a column. You can create a Python UDF that uses the `json` library to parse the string and return a structured data type. This is particularly useful when dealing with semi-structured data. Working with complex data types involves understanding how these data structures are represented in both Python and SQL and how to convert data between them. For instance, consider a scenario where you have a JSON string column, and you want to extract a specific field. You can write a Python UDF to parse this string using the `json` library, and then access the required data. This demonstrates how UDFs can parse and transform more complex data.
