 Now in the last video we started talking about the idea of array wise operations The entire idea is that if I say for example had Two arrays and I wanted to for example add the elements at their corresponding spaces together I could just do that Python or numpy Just has in the back end built What to do when it sees an array plus an array and it's perfectly fine with that And that's where we're getting things like this kind of output Now this actually expands. It's not just our mathematical operations that we can do this with But it also works in our comparison operations And really you could experiment with all of the different types see what they do in this case You can tell that if we're doing a comparison of if Array one is greater than a two it says oh well Let me look at each element and do that same greater than comparison and I'll tell you if it's In this case true or false But what happens if I want to see if my two arrays are Say for example equal in that case that becomes a bit more difficult now if I came in and I'll actually just shrink this down a little bit Back to Just a single-dimensional Array we should see that this is going to be false, right there One is not the same as ten etc. So I shouldn't see any problems here. I See a problem now. This is not going to crash the program specifically But as you can see it is starting to freak out a little bit. It's like hey, you know You can't do comparisons in the future So as NumPy is working you may not you know whenever you watch this video you may not be allowed to do what I'm attempting to do here So how do I make a comparison? This is where we get into the idea of array wise operations The entire idea here is now if I wanted to do an operation that Just is about the entire array not the elements of the array. I need to access these Functions that Python has our numpy has built for itself. So in this case, let's say I wanted to do a comparison of x and y Now we've already seen array by itself But as you can already see, you know if spiders being generous with me there is an array underscore equal and That Asks for two arrays a you know it's saying it's a one and a two My case it would be x and y. I do the same kind of comparison now What's happening is what I am effectively doing is I'm going to take my x array and my y array And I'm passing them to some function that Python or numpy has built in the background It's you know, and then it will do the for comparison And if it stays true the entire time, then this is a an equal array now again in our case We should not see that we should see a false We see a false no error message La da da and same kind of thing if I just came in and did a comparison on One-to-one so in this case x and y. Let's see what happens here They are now in fact true And so there are tons of these operations that we can work off of so say for example This is a comparison of the element variation versus the Array version operation. So if I came in and did x times y and just to space this out a little bit If I did x times y again, that is an element wise operation. It's going to go through each element and Multiply it by its corresponding element. So in our case we see one four nine sixteen twenty five However, you know, that may not be what you're going for you may be wanting to Produce something like a dot product well in that case I'll come in in P and the same kind of thing you can already see where some of these commands are coming in and you know If you're really feeling froggy, I'm not gonna go over each one of these in a video. That's weird, but specifically ah Look at that. Wouldn't you know it? There is a dot Function that numpy has in it where I pass in an x and a y and it will do I Don't have an extra parentheses there it will do The dot product so in this case it does the multiplication. So it takes the twenty five sixteen nine Four one adds them all together and it should give you twenty up a fifty five You