python pandas dataframe, is it pass-by-value or pass-by-reference

Question

If I pass a dataframe to a function and modify it inside the function, is it pass-by-value or pass-by-reference?

I run the following code

a = pd.Data         


        

Answer 1

Python is neither pass by value nor pass by reference. It is pass by assignment.

Supporting reference, the Python FAQ: https://docs.python.org/3/faq/programming.html#how-do-i-write-a-function-with-output-parameters-call-by-reference

IOW:

1. If you pass an immutable value, changes to it do not change its value in the caller - because you are rebinding the name to a new object.
2. If you pass a mutable value, changes made in the called function, also change the value in the caller, so long as you do not rebind that name to a new object. If you reassign the variable, creating a new object, that change and subsequent changes to the name are not seen in the caller.

So if you pass a list, and change its 0th value, that change is seen in both the called and the caller. But if you reassign the list with a new list, this change is lost. But if you slice the list and replace that with a new list, that change is seen in both the called and the caller.

EG:

def change_it(list_):
    # This change would be seen in the caller if we left it alone
    list_[0] = 28

    # This change is also seen in the caller, and replaces the above
    # change
    list_[:] = [1, 2]

    # This change is not seen in the caller.
    # If this were pass by reference, this change too would be seen in
    # caller.
    list_ = [3, 4]

thing = [10, 20]
change_it(thing)
# here, thing is [1, 2]

If you're a C fan, you can think of this as passing a pointer by value - not a pointer to a pointer to a value, just a pointer to a value.

HTH.