Why Do Changes to a Python List Copy Affect the Original List?

Python: Understanding Reference Copying

When creating a copy of a list in Python, it can be surprising to discover that changes made to the copy also affect the original list. This is because Python uses reference copying, which creates a reference to the original list instead of a separate instance.

To illustrate, let's consider the following code:

org_list = ['y', 'c', 'gdp', 'cap']

copy_list = org_list

copy_list.append('hum')

print(copy_list)
print(org_list)

This code will output:

['y', 'c', 'gdp', 'cap', 'hum']
['y', 'c', 'gdp', 'cap', 'hum']

As we can see, the original list org_list is modified after the copy_list append operation. This is because copy_list is not a separate instance but rather a reference to org_list.

To create an independent copy of the original list, we can use the slicing operator:

copy_list = org_list[:]

This creates a new list that is a copy of org_list. Changes made to copy_list will no longer affect org_list. This approach can also be used to copy other types of variables, such as Pandas DataFrames.

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