Pandas Accept index in addition to list for set_index

Running this code generates an error, since columns are now considered an Index and not a list. I'm not sure if the error that gets raised (set_index ends up asking for an index that is the entire length of the data frame) is actually by design. In this case, it was a bit unintuitive to figure out how to catch, since Index objects and python lists often work so similarly.

import string
import pandas as pd

data1 = 'x'*5 + 'y'*5
data2 = string.lowercase[:5]*2
data3 = range(10)
data_dict = {'Cat': list(data1), 'SubCat': list(data2), 'Vals':data3}
df = pd.DataFrame(data_dict)
ordered_df = df[['Cat', 'SubCat', 'Vals']]

correct_df = ordered_df.reset_index([x for x in ordered_df.columns[:2]])
error_df = ordered_df.set_index(ordered_df.columns[:2])

Comment From: jreback

So you want this?

In [23]: ordered_df.set_index(list(ordered_df.columns[:2]))
Out[23]: 
            Vals
Cat SubCat      
x   a          0
    b          1
    c          2
    d          3
    e          4
y   a          5
    b          6
    c          7
    d          8
    e          9

yeh, its a pretty trivial change. want to take a go at it. Appears innocuous.

Comment From: jreback

change here to not is_list_like(...)

Comment From: michaelbilow

Yep, exactly.

Comment From: StephenKappel

It's valid to pass an Index or row labels to set_index with the expected behavior of that index becoming the index. So, to achieve the desired behavior, I am opening a PR that only treats an index like a list of column labels when the index is not the same length as the DataFrame. This should avoid breaking the existing behavior while making ordered_df.set_index(ordered_df.columns[:2]) possible in most cases.

Comment From: hundredrab

Hi, can I take a go at this?

Comment From: szabi

I came across what is essentially the same issue in 2023: I wanted to pass an instance of typing.Collection (specifically a tuple) fully expect it to work, going by the documentation:

keys : label or array-like or list of labels/arrays This parameter can be either a single column key, a single array of the same length as the calling DataFrame, or a list containing an arbitrary combination of column keys and arrays. Here, "array" encompasses :class:Series, :class:Index, np.ndarray, and instances of :class:~collections.abc.Iterator.

The check in https://github.com/pandas-dev/pandas/blob/01693d64fe7b4335c327d62c5a5861f07c98f8c9/pandas/core/frame.py#L5787-L5788 is too restrictive.

It seems to be a simple one-liner. However, in 2015 not is_list_like(...) but that does not seem to be part of common.py any more. Would the correct course of action in 2023 be to use if not isinstance(keys, Collection) from typing? Or ist is_list_like the way to go (import from where?)

Pinging @jreback