Sure, but these ten characters let you treat columns as values and do math on them, which is super intuitive, in my opinion. I've been using Pandas for quite some time and always kinda sucked at it. One day I decided to give this new library Polars a try. Now I can do things I couldn't even dream of with Pandas! And it's fast, too!

I think of `pl.col` as delayed evaluation: I want to do math on the vector of values of this column. But wait, let me just refer to the name of that column and build the expression that I want to compute. Then I hand this expression to Polars and it retrieves the actual values of the columns my expression refers to and executes the operations.

IMO, it would've been great to just do math on strings, like `"Amount" * "Price" - "Losses"`, but programming languages either don't allow math on strings or that math is actually string concatenation, which is not what we want. So we have to wrap the name of the column into some object. This is just an API thing.

As a side note, it's such a pity that there's basically no Polars for the Julia language! There is some wrapper package, but it seems old and unmaintained. I can't seem to properly learn DataFrames.jl for some reason, I always miss Polars when I use Julia.

I've seen people with exactly that frustration use "import polars.col as c" and use c("colname") instead!

Every time:

   import polars as pl
   
   from polars import col, lit

c = pl.col

c.foo + c.bar