Why does pandas apply calculate twice

Question

I'm using the apply method on a panda's DataFrame object. When my DataFrame has a single column, it appears that the applied function is being called twice. The questions are why? And, can I stop that behavior?

Code:

import pandas as pd

def mul2(x):
    print ('hello')
    return 2*x

df = pd.DataFrame({'a': [1,2,0.67,1.34]})
df.apply(mul2)

Output:

hello
hello

0  2.00
1  4.00
2  1.34
3  2.68

I'm printing 'hello' from within the function being applied. I know it's being applied twice because 'hello' printed twice. What's more is that if I had two columns, 'hello' prints 3 times. Even more still is when I call applied to just the column 'hello' prints 4 times.

Code:

df.a.apply(mul2)

Output:

hello
hello
hello
hello
0    2.00
1    4.00
2    1.34
3    2.68
Name: a, dtype: float64

Answer 1

This behavior is intended, as an optimization.

See the docs:

In the current implementation apply calls func twice on the first column/row to decide whether it can take a fast or slow code path. This can lead to unexpected behavior if func has side-effects, as they will take effect twice for the first column/row.