This is what 0-based indexing looks like in data analysis:
>In order to read a csv in that doesn't have a header and for only certain columns you need to pass params header=None and usecols=[3,6] for the 4th and 7th columns:
>Call the columns the 4th and 7th is as arbitrary as calling them the 3rd and the 6th.
No, that's their ordinal position, and how 8 billion non-programmers would refer them as in any everyday setting.
That's also how programmers would refer to them if it wasn't for a historical accident.
What's more, that's also how programmers refer to them when they talk between then and not to the machine ("check the 3rd column" not "check the column at the index of 2").
It's not arbitrary. It's English. In the list [apple, orange, tree] which element is orange? It's the second element.
I have taught Python quite a bit, and I have gotten good at explaining 0 based indexing and slicing based on it. When I switched to Julia there was nothing to explain. And my code has about as many +/- 1s as before...
Just because it is our common convention in lay conversation doesn’t mean it isn’t “arbitrary”.
These spoken language conventions developed before there was an established name for “zero” or even a concept that “nothing” could be a number per se.
For similar reasons, we have no zero cards in our decks, no zero faces on a dice, no zero hour on our clocks, no zero year in our calendar, no zeroth floors in our buildings, East Asian babies are born with age one year, etc.
It’s only by another set of historical accidents that we have a proper 0 in our method of writing down whole numbers. Thankfully that one was of obvious enough benefit that it became widely adopted.
In (North?) America. In Europe, there's a ground floor (zero), then first floor (1), etc. Basement is -1 (etc.).
A European friend of mine arrived at college in the USA, and was assigned a room on the first floor of the dorm. She then asked the housing office whether there was a lift, because she had quite some heavy luggage, earning some rather amused looks :-)
The base level doesn't need to have a floor, it's just ground. Once you add a floor you are on the first floor above ground. Really your condescending tone as if all the mathematicians that prefer to work with 1 indexing are just incompetent is grating.
I'm happy to be writing
```
for i in 1:n
func!(a[i])
end
```
to iterate over an object of length n. Or split an array as a[1:m], b[m+1:n]. Slicing semantics which are far more prevalent in my code (and the code I read) than index arithmetic, are truly vastly simplified by 1 based indexing of Julia compared to the 0 based numpy conventions. We simply no longer code in the world that Dijkstra argued for, and I have not seen anybody give a clear argument that is actually rooted in maths and contemporary programming.
I genuinely thought that the Python convention was brilliant, and that 1-based indexing in Julia would suck. It turned out not to be the case.
Sorry, that last bit of my comment was gratuitous.
I am legitimately (mildly) curious about the history of the different naming conventions for floors of buildings though.
> The base level doesn't need to have a floor, it's just ground. Once you add a floor you are on the first floor above ground.
Yes, my point is this is an example where the European 0-based indexing system makes more sense (in my opinion) than the American 1-based indexing system. I speculate that whoever started calling the ground floor the “first floor” hadn’t really put much thought into how well that would generalize to large buildings with many floors including some underground.
Similarly, whoever decided the calendar should start at year 1 AD with the prior year as 1 BC hadn’t really considered that it might be nice to do arithmetic with intervals of years across the boundary.
There are many standard mathematical formulas which are clarified by indexing from 0. But nobody can switch because the 1-indexed version is culturally fixed. Most of the rest of the time the 0-indexed vs. 1-indexed versions makes basically no difference. It is rare that the 1-indexed version is notably nicer.
> Or split an array as a[1:m], a[m+1:n]
Yes, I find it substantially clearer to write this split as a[:m], a[m:]. Particularly when dealing with e.g. parsing serialized structured data. But also when writing numerical code. Carrying the extra 1s around just adds clutter, and forces me to add and subtract 1s all over the place; reasoning about it adds mental overhead, and extra bugs sneak in. (At least when writing Matlab code; I haven’t spent much time with Julia.)
The 12 on a clock is a compromise to match between a 1-indexing oral culture and natural 0-indexing use case (which came from the Sumerians who had a better number system).
I don’t know the history of reported ages of Western babies.
The equivalent of `a = b[:n]` is `a = b[1:n]`. And I don't think you can get around admitting that there is a fundamental ambiguity in the spoken statement "Take a look at the fourth column!" in a zero-based index system. You always need a follow-up question to clarify whether you mean "everyday informal speech fourth" or "zero-index fourth."
>In order to read a csv in that doesn't have a header and for only certain columns you need to pass params header=None and usecols=[3,6] for the 4th and 7th columns:
https://stackoverflow.com/questions/29287224/pandas-read-in-...
Just reading that hurts me.