[Python] confusion on re-assigning pandas columns after modification with apply

Let us assume we have this dataframe:

df = pd.DataFrame.from_dict({1:{"a": 10, "b":20, "c":30}, 2:{"a":100, "b":200, "c":300}}, orient="index")

Further, let us assume I want to apply a function to each row that adds 1 to the values in columns a and b

def add(x):
return x["a"] +1, x["b"] +1


Now, if I use the apply function to mod and overwrite the columns twice, some values are flipped:

>>> df.loc[:, ["a", "b"]] = df[["a", "b"]].apply(lambda x: add(x), axis=1)
>>> df
a b c
1 11 101 30
2 21 201 300
>>>
>>> df.loc[:, ["a", "b"]] = df[["a", "b"]].apply(lambda x: add(x), axis=1)
>>> df
a b c
1 12 22 30
2 102 202 300
>>>


Could somebody explain to me why b1 and a2 get flipped?

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