Loops like you're 5: A loop is a way to tell the computer to do something specific repeatedly. For instance, if you were a (human) computer and I told you to walk to the end of the street and back until you have done so three times; this is a loop. It's a specific instruction done repeatedly. Loops don't always have an end. If I told you (as a computer) to walk to the end of the street and back until I tell you to stop; if suddenly I decide to move to France while you're walking back and forth, this is an example of a potential infinite loop. I may come back to visit and tell you to stop. You may keep going until you keel over. Nested loops like you're 5: If a loop is a set of specific instructions done repeatedly, what happens if you put a loop in a loop? Well, one of those loops has to finish entirely before the other can continue again. If I told you to walk down to the end of the street 3 times and back, but when you get halfway back, stop and touch your nose 5 times before you start again; this is a nested loop. You may say to yourself "but wait, I can touch my nose while I'm walking, why do I need to stop?" and you would be right, but what we need to realize about computers is that because of how they work, they can only do one thing at a time. (see below before any objections) Computers work in steps. Do A, then do B, then do C. Loops allow us to say "but do X over and over again." You may then say "but how come I can browse reddit, listen to music, and download stuff at the same time on my computer?" and this moves into the concepts of concurrency, or in simpler terms, making the computer do lots of different things at the same time. Things like this exist because we may want a loop to be indefinite, or to end when we tell it to end. Lots of things in the computer world depend on infinite loops, including browsing Reddit (for server side web services, some web browsing features) and video games (rendering and game logic loops). This is where concurrency and asynchronous operations come into play, but this is beginning to get out of the scope of the question, so I'll stop it here (unless you're interested). tl;dr More on reddit.com

Let’s take a bit of a diversion and talk about the basics of Big O notation. It’s a way of measuring how long your code will take to run. Here are a few of the key examples: O(n) - linear time - Loops are the classic example. For each extra input you have to run the loop one more time. O(n) solutions are typically pretty good, but if you have a ton of inputs they will start to slow down. Also, beware linear time solutions when you could have used something constant time (e.g. using arr.find(...) instead of obj[...]). O(logn) - log time - A binary search is the classic example. Every time you double the inputs you only add one more iteration. This is the holy grail of algorithms. Phds get paid big bucks to come up with logarithmic solutions to problems that used to be linear. O(n^2) - quadratic (or exponential) time - I usually lump quadratic (n squared) together with exponential (n to any power) because they are just different flavors of bad. A nested loop is the classic example, however, just because you have a loop in a loop does not mean you have O(n^2). Iterations have to double with each input. For example say you have an array of numbers and want to check if any is equal to any of the others. The naive O(n^2) solution would be to use a nested loop through the entire array for each element in the array. With 1000 numbers, you would need to run 1000^2 or one million iterations. At a certain point you will just crash your web browser. Okay, there is plenty more to learn about Big O and algorithms in general, but I wanted to give you a quick background so we can talk about how it impacts your problem. You have been told “nested loops are bad”, but what people really mean is “O(n^2) solutions are bad”. In your case, you have a 2d (or more) array. But if when you add a new input it's just one new element to one sub-array (as opposed to one new element to every sub-array), then what you are talking about is linear time. The nested loops are just an artifact of how you organized your data. One new input adds one more iteration, so we are talking O(n). (As others have said though, it might still be worth simplifying your data structure if it makes your code more clear and readable) More on reddit.com

Nested loops are fine. Similarly with if statements, you probably want to avoid unecessary nested loops as it might make the code hard to read but in the case that you're simply iterating something, I think its still quite readable. More on reddit.com

You could try splitting things out into functions to avoid nesting too deep in loops. More on reddit.com