hard20 pts · first answer countspythonpandas

A helper that changes the caller's data

After calling add_tax(df), the original df has a new column too. Why, and what is the clean fix?

def add_tax(d):
    d["tax"] = d["amount"] * 0.05
    return d

A.pandas copies arguments, so this cannot happenB.The return statement copies d back into dfC.Copy-on-Write makes every argument a viewD.d is the same object as df; use return d.assign(tax=...)

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A helper that changes the caller's data

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