Pandas DataFrame as an Argument to a Function - Python

Question

Suppose a Pandas DataFrame is passed to a function as an argument. Then, does Python implicitly copy that DataFrame or is the actual DataFrame being passed in?

Hence, if I perform operations on the DataFrame within the function, will I be changing the original (because the references are still intact)?

I just want to know whether or not I should make a Deep Copy of my DataFrame before passing it into a function and operating on it.

pretty good answer here: stackoverflow.com/questions/38895768/… — JohnE
– JohnE, Commented Dec 3, 2020 at 3:47

smci · Accepted Answer · 2022-02-12 23:12:41Z

19

If a function parameter is a mutable object (e.g. a DataFrame), then any changes you make in the function will be applied to the object.

E.g.

In [200]: df = pd.DataFrame({1:[1,2,3]})

In [201]: df
Out[201]:
   1
0  1
1  2
2  3

In [202]: def f(frame):
     ...:     frame['new'] = 'a'
     ...:

In [203]: f(df)

In [204]: df
Out[204]:
   1 new
0  1   a
1  2   a
2  3   a

See this article for a good explanation on how Python passes function parameters.

edited Feb 12, 2022 at 23:12

smci

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answered Jul 17, 2018 at 23:30

aydow

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3 Comments

Paul H Over a year ago

dataframes are mutable, not immutable

David Johns Over a year ago

@PaulH maybe op said DataFrame is an example of not immutable (=mutable) objects

smci Over a year ago

@ DavidJohns: the way that's written is very ambiguous e.g. "If arg is not a bear (e.g. a a koala). Much clearer to say If it's a mutable object..."

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