Numpy Arrays

Quick reference

• 00:05 Okay, in this video, I want to talk about NumPy arrays.
• 00:08 So first off, I've got a couple of just regular Python lists here.
• 00:12 And a list is an array, Python just calls them lists, right, but
• 00:16 they're basically arrays.
• 00:17 And if you're familiar with Python,
• 00:19 you're familiar with something like these basic lists.
• 00:21 So here we have a list called names, has items John, Mary, Tim and Jill.
• 00:25 And if we print out one of those items, we can call names and
• 00:31 then say we want John, we could print the 0th item,
• 00:35 because list as you probably know are numbered and they start with 0, 1, 2, 3.
• 00:43 So if we want this one, it's the 0th item, so we can run this and boom,
• 00:47 it's John, if we want Tim, that's the 0, 1, 2, the second item, Tim.
• 00:53 And these are strings of text, but with lists,
• 00:57 you can use numbers too, so here we can print out numbers.
• 01:01 And let's say we want this one right here,
• 01:05 this is the 0, 1, one if the first item, boom 192.
• 01:10 And likewise, we could call the third item, that's 56.
• 01:15 So those are Python lists, basically, they're arrays.
• 01:18 And we're probably familiar with those if we've done any python programming.
• 01:22 NumPy arrays are basically the same, they're just written in NumPy,
• 01:26 which makes them much, much faster.
• 01:29 It makes them able to handle large amounts of data much,
• 01:32 much faster than a regular Python list.
• 01:35 And to create a NumPy array, we just go np.array and this is a function,
• 01:40 and inside of here, we can pass whatever we want.
• 01:43 So if we want 41, 192, 3, and 56,
• 01:47 we can Shift+Enter to run this and we have an array with these things in it.
• 01:54 And really, when you get right down to it, that's all there is to this, NumPy arrays.
• 01:59 Now we can do all kinds of very, very cool things to these NumPy arrays.
• 02:05 And that's what we're going to be doing in the next few videos, we'll learn
• 02:07 about operations and functions and things like that and what we can do with them.
• 02:10 But basically, it just comes down to this, they're big, they're just big arrays,
• 02:15 very much like a Python list, and that's what you want to think of them as.
• 02:18 Now, there are basically two types of arrays we want to really focus on,
• 02:22 one is called a vector and the other is called a matrix.
• 02:25 And the difference between the two are dimensions.
• 02:29 So this is a single dimension, this is just one sort of list,
• 02:33 one array inside of our NumPy array, that's just 1-dimensional.
• 02:38 That's a vector array, one dimensional arrays are vector arrays.
• 02:42 2-dimensional or above more than 1-dimension,
• 02:45 multi- dimensional are called matrices, matrix, right?
• 02:50 That's sort of what we're doing here, linear Algebra,
• 02:52 this is what this all deals with.
• 02:53 So like I said, we'll get into all this in more detail going forward, but
• 02:57 we could just create one real quick np.array.
• 03:00 And then inside of here, we can have multiple, multiple vectors,
• 03:06 I guess you would call them, right?
• 03:08 So inside of here, we could go 1, 2, 3, and inside of this one,
• 03:14 we could have 4 or 5, 6, and inside of this one we could have 7, 8, 9.
• 03:19 And when we run this we could see this is now a multi-dimensional array,
• 03:24 there are many dimensions, right?
• 03:26 If we just run this one up here like we just did, there's just one line here,
• 03:30 right, that's one dimension, it's one set of brackets, right?
• 03:35 Inside of here, we have multiple sets of brackets, multiple dimensions, and
• 03:40 this is a matrix array versus a vector.
• 03:42 So just remember vector versus matrix.
• 03:44 At this point, that's all I really want you to remember about this, that and
• 03:48 that these deal with numbers, they're arrays, they handle large amounts of data.
• 03:53 They do it faster than Python lists, which is interesting,
• 03:57 but we don't really care at this point, we just need to know from now on,
• 04:00 we're going to be using NumPy arrays for just about everything.
• 04:04 So that's really all there is to NumPy arrays right now, I mean,
• 04:08 obviously, we're going to learn a lot more about them going forward.
• 04:10 But that's all I wanted to talk about in this video, in the next video,
• 04:14 we'll start to learn about NumPy array operations, doing things to these numbers,
• 04:19 and that'll be in the next video.

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