Pandas DataFrame 作为函数的参数 - Python
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Pandas DataFrame as an Argument to a Function - Python
提问by WhiteDillPickle
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?
假设 Pandas DataFrame 作为参数传递给函数。那么，Python 是隐式复制该 DataFrame 还是传入的实际 DataFrame？
Hence, if I perform operations on the DataFrame within the function, will I be changing the original (because the references are still intact)?
因此，如果我在函数内对 DataFrame 执行操作，我是否会更改原始数据（因为引用仍然完整）？
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.
我只想知道在将数据帧传递给函数并对其进行操作之前，是否应该对其进行深度复制。
回答by aydow
If a function parameter is not an immutable object (e.g. a DataFrame), then any changes you make in the function will be applied to the object.
如果函数参数不是不可变对象（例如 a DataFrame），则您在函数中所做的任何更改都将应用于该对象。
E.g.
例如
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 thisarticle for a good explanation on how Python passes function parameters.
请参阅此文章对Python的传递函数参数一个很好的解释。
