Foop | A For-loop-like debugging GAME | Code Inspection library

Background

I have a table and one of the column contains data that looks like this:

I have heard its a conventional practice to store program dependent files in /usr/share/application-folder in linux. So I'm trying to do it in my c program in a function called load_interface_files() for example. I am not sure if this is a good practice or not, I've heard about creating configuration files for this kind of issues.

Anyways, here's the the code I wrote to make a directory in /usr/share.

I'm trying to understand what's the execution complexity of the iloc function in pandas. I read the following Stack Exchange thread (Pandas DataFrame search is linear time or constant time?) that:

"accessing single row by index (index is sorted and unique) should have runtime O(m) where m << n_rows"

mentioning that iloc runs on O(m) time. What is m (linear, log, constant,...)?

Some experiments I ran:

I dont know if the title is the best, but its what I got.

What I am looking for is to find the best matches (based on minimum distance) for all values in the first column WITHOUT having duplicate matches in the second column. For instance, given the following dataframe:

Swift 5, on XCode 11.2.1. I've programmed in Java forever, and am only moderately skilled in Swift at this point, so some of my understanding is colored by Java idioms.

Suppose we provide a protocol, or possibly a pseudo-abstract class, which can be implemented in a separate module. Then the programmer passes a reference to their class back to code in the first module, which instantiates their class. Now, in Java this was difficult because you couldn't make any guarantees what initializers/static methods a subclass would define. However, in Swift, you can. This is neat. EXCEPT, I haven't yet found a way to use them. What I'd expect would be that you could have code like e.g.