PySpark how to write and execute a UDF

PySpark has many built in capabilities to transform and manipulate data. However there are still times when the built in capabilities do not cover a specific use case and you must write a user defined function (UDF). UDFs allow you to write your own function, register the function with the spark session, and then perform that function on a given column or set of columns. There are multiple ways to write a UDF and this article will cover registering (i) a PySpark UDF and (ii) a pandas UDF that is vectorized

This problem will work with a fake basketball dataset that can be used for monitoring the probability a team is favored to win. The probability a team is going to win is tracked every single second for every single game of an entire basketball season. The following code shows how to create a mock of that dataset

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