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Apply a lambda and function to a DataFrame in Python

Functional programming is the ability to pass functions to do work.
A lambda is a simple, usually one line command you wish to apply.
A function is defined, can accept parameters, can return results.

Consider re-usability! More reusability == do more with less code.

DRY, do not repeat yourself, is a guideline that you should not copy and paste code, because it causes bloat.

lambda x: x + 1 is an example of a lambda that will add 1 to x.
We can apply this lambda to a DataFrame by doing this:

clinicDF.CLOSE_HOUR = clinicDF.CLOSE_HOUR.apply(lambda x: x + 1)

x represents each unit of data within the CLOSE_HOUR column, in this case. It acts as an iteration variable.

To define a function, we start with def:

def foo(bar):
return bar + 10

This is a function named foo, with a parameter named bar. It will return bar + 20

To apply this, we just pass in the name of the function to the DataFrame selection.

clinicDF.CLOSE_HOUR = clinicDF.CLOSE_HOUR.apply(foo)