It's not weird, it's wrong:

    In [1]: "a    string     r".split(" ")
    Out[1]: ['a', '', '', '', 'string', '', '', '', '', 'r']

    In [2]: "a    string     r".split()
    Out[2]: ['a', 'string', 'r']

In their case though that wouldn't have been a problem as each word was split on a single space.

Split without argument is equivalent to:

    >>> filter(None, " quick   hack for  split".split(" "))
    ['quick', 'hack', 'for', 'split']

Yeah, or re.split(r'\s+', ...), or something - the issue here is that you need to know about this.

From the comment a few levels up I understood that the code which used the str.split with " " argument didn't signify that someone who written it knew about its semantics. If he did and it was really what was intended then ofc it's completely ok, but if not, it can easily lead to bugs.

For example, if the user is required to input several ints separated with whitespace, this:

    map(int, input_str.split())

will rise only in expected cases, while this:

    map(int, input_str.split(" "))

can lead to rejecting correct input just because someone pressed space twice. It's very frustrating for the user, too, because whitespace are hard to spot visually.

So, I don't know if this qualifies as antipattern, but I think if I saw .split(" ") instead of .split() in the code I'd at the very least expect the comment explaining why it's used.

I don't mean to be pedantic, but a list (I am assuming df is a list) requires an int.

(That sentence I wrote about using hashable types need not apply, sorry!)

If you ran that code, you would get this error:

    TypeError: list indices must be integers, not list

That's a pandas dataframe (idiomatically denoted df), not a list. It has funky slicing properties, and he's selecting columns of the dataframe in a perfectly valid way.