python - 访问 Pandas 专栏的最快方法

Question

我对访问 pandas 列的各种方式之间的性能差异感到困惑。

In [1]: df = pd.DataFrame([[1,1,1],[2,2,2]],columns=['a','b','c'])

In [2]: %timeit df['a']
The slowest run took 75.37 times longer than the fastest. This could
mean that an intermediate result is being cached.
100000 loops, best of 3: 3.12 µs per loop

In [3]: %timeit df.a
The slowest run took 5.14 times longer than the fastest. This could
mean that an intermediate result is being cached.
100000 loops, best of 3: 6.59 µs per loop

In [4]: %timeit df.loc[:,'a']
10000 loops, best of 3: 55 µs per loop

我知道最后一个变体比较慢，因为它可以设置值，而不仅仅是访问值。但为什么 df.a 比 df['a'] 慢？无论缓存的中间结果如何，这似乎都是正确的。

Answer 1

Here是一个链接，解释了 . 访问和 [] 访问之间的区别。

另请查看文档中这些运算符的行为

getitem (对于 [])和 getattr (对于 .)方法。

. 似乎通过函数调用访问该列，因此比作为字典键值访问的 [] 花费的时间更少