1 00:00:06,130 --> 00:00:11,260 Everybody has a go and this is Caleb with Deb's slopes dot com and I am so excited to teach you about 2 00:00:11,260 --> 00:00:14,020 swift transformations in this video. 3 00:00:14,140 --> 00:00:20,050 Basically swift transformations are functions that you can use on various collections and sequence types 4 00:00:20,050 --> 00:00:22,090 to permeate and modify the data. 5 00:00:22,190 --> 00:00:26,440 But in a very Swiftie very kind of compressed elegant way. 6 00:00:26,470 --> 00:00:32,230 So we're going to go ahead and begin by creating a swift playground so penélope an X code and pull the 7 00:00:32,230 --> 00:00:36,740 window over and we're going to click get started with a new playground. 8 00:00:37,070 --> 00:00:40,340 Can't just make a blank playground and I'm going to name it. 9 00:00:40,930 --> 00:00:47,000 Transformers like a popular movie and cartoon franchise. 10 00:00:47,000 --> 00:00:51,220 I'm going to go ahead and pull this off in full screen and I'm actually going to get rid of everything 11 00:00:51,220 --> 00:00:55,870 in here and just import foundation because that's all that we're going to need from the beginning is 12 00:00:55,870 --> 00:00:59,770 the just basic swift library nothing extra fancy. 13 00:01:00,010 --> 00:01:04,930 And so we're going to go ahead and begin by talking about one function. 14 00:01:05,030 --> 00:01:12,130 And it's called Map already and I'm going to copy and a little comment here explaining map and basically 15 00:01:12,130 --> 00:01:19,840 what it does is it returns an array containing the results of mapping the given closure over the sequences 16 00:01:19,930 --> 00:01:20,970 elements. 17 00:01:20,980 --> 00:01:27,040 So this is like a really super compressed very elegant way to do what a for loop might do where it will 18 00:01:27,130 --> 00:01:32,630 iterate through every item in a sequence and it will perform that same function to whatever item is 19 00:01:32,720 --> 00:01:33,790 iterating over. 20 00:01:33,790 --> 00:01:39,250 So for example we're going to create a variable called city names and I'm going to go ahead and give 21 00:01:39,250 --> 00:01:41,590 it a few different names here. 22 00:01:41,620 --> 00:01:46,780 We're going to just go ahead and copy and paste this a couple of times just to make it nice and easy. 23 00:01:47,060 --> 00:01:48,940 And so let's go ahead and just put in. 24 00:01:48,940 --> 00:01:52,240 You know Portland that's where I'm from Will do. 25 00:01:52,240 --> 00:01:55,720 San Luis Obispo San Luis Obispo. 26 00:01:55,720 --> 00:01:56,730 However you say it. 27 00:01:56,980 --> 00:01:59,140 That's where Mark is from. 28 00:01:59,140 --> 00:02:01,540 How about Tampa. 29 00:02:01,570 --> 00:02:05,160 That's where Jacob wishes he was from and these other ones I'll just do. 30 00:02:05,170 --> 00:02:09,050 I don't know Boston in Cupertino because you know Apple. 31 00:02:09,250 --> 00:02:09,990 So there we go. 32 00:02:10,000 --> 00:02:11,730 We've got some city names here. 33 00:02:11,740 --> 00:02:17,820 And here is where we're going to use maps so these are all obviously lowercase city names. 34 00:02:17,830 --> 00:02:22,690 But I want to make sure that every single item in this array is capitalized because obviously the city 35 00:02:22,690 --> 00:02:25,360 name is a proper noun and it should be capitalized. 36 00:02:25,360 --> 00:02:37,000 So let's create an array here call by saying Let capitalized city names equals city names. 37 00:02:37,000 --> 00:02:42,310 And what we're going to do is we're going to call dot map and like it says it returns an array. 38 00:02:42,310 --> 00:02:43,950 So that's why we're using. 39 00:02:44,050 --> 00:02:48,280 We're just going to load it directly into this constant and it's going to return the arrays and we're 40 00:02:48,280 --> 00:02:54,680 going to set a condition or not a condition but a type of modification we want to perform to every item. 41 00:02:54,850 --> 00:02:59,800 So the act to actually use this we can go ahead and use just curly brackets here right after map. 42 00:03:00,010 --> 00:03:06,640 And then in order to access one item we're going to use this symbol here dollar sign zero and what this 43 00:03:06,640 --> 00:03:13,060 is doing this is basically a placeholder variable that the value of each item is going to get set to 44 00:03:13,060 --> 00:03:13,390 this. 45 00:03:13,390 --> 00:03:16,460 With every iteration so the first iteration it's set to Portland. 46 00:03:16,510 --> 00:03:19,000 Second iteration is set to San Luis Obispo. 47 00:03:19,020 --> 00:03:20,000 Third iteration. 48 00:03:20,010 --> 00:03:21,520 Tampa et cetera et cetera. 49 00:03:21,820 --> 00:03:26,230 And because it's set to a string I can call any function that a string can do. 50 00:03:26,230 --> 00:03:33,310 So I'm going to capitalize it by calling dot capitalized and now we have an array that has iterated 51 00:03:33,310 --> 00:03:40,150 over every word in this array and it's going to go ahead and have all of the city names be capitalized. 52 00:03:40,150 --> 00:03:47,080 So if I print capitalized city names you'll see down here we get an array with all of the city names 53 00:03:47,080 --> 00:03:47,950 capitalized. 54 00:03:47,980 --> 00:03:49,120 So cool. 55 00:03:49,210 --> 00:03:54,910 So what it did is it iterated over every item in this array and it returned a new array with the modifications 56 00:03:54,910 --> 00:03:55,460 applied. 57 00:03:55,570 --> 00:03:56,770 That's that's how IMAP works. 58 00:03:56,770 --> 00:03:58,370 It's really really simple. 59 00:03:58,390 --> 00:04:05,350 Now of course that is one thing that we can do a map that's great but there are a lot of other different 60 00:04:05,350 --> 00:04:07,090 ways that we can modify data. 61 00:04:07,090 --> 00:04:09,580 Another one is called flat map. 62 00:04:09,580 --> 00:04:14,020 And so in order to show you that I'm going to paste in this description and let's read it. 63 00:04:14,200 --> 00:04:20,800 It returns an array containing the concatenated results of calling the given transformation with each 64 00:04:20,860 --> 00:04:22,700 element of this sequence. 65 00:04:22,930 --> 00:04:28,750 So what flat map is going to do is it's going to take maybe nested data. 66 00:04:28,750 --> 00:04:34,240 So an array with arrays inside or a dictionary with dictionaries inside and what it's going to do is 67 00:04:34,240 --> 00:04:40,420 it's going to remove one layer of complexity so if there were you know maybe an array with three arrays 68 00:04:40,420 --> 00:04:45,460 inside it would basically pull all the values out of those three arrays and just smoosh them together 69 00:04:45,700 --> 00:04:47,290 into one array. 70 00:04:47,290 --> 00:04:53,380 Now of course this is sort of a specific use case but there are there are very specific benefits to 71 00:04:53,380 --> 00:04:53,890 using it. 72 00:04:53,890 --> 00:04:58,810 So let's go ahead and see how this works we're going to create what I just said is you know a nested 73 00:04:58,810 --> 00:04:59,090 array. 74 00:04:59,080 --> 00:05:03,450 So let's go ahead and say var collections. 75 00:05:04,450 --> 00:05:07,230 And we're going to make a couple of different collections of numbers here. 76 00:05:07,420 --> 00:05:14,320 So let's do you know one two three and then let's not do separate numbers here. 77 00:05:14,320 --> 00:05:15,480 There we go. 78 00:05:15,550 --> 00:05:19,220 And next we're going to go ahead and do another array. 79 00:05:19,900 --> 00:05:28,140 1 5 7 following that we're going to go ahead and do another one. 80 00:05:28,300 --> 00:05:32,800 Let's do 24 Six. 81 00:05:33,160 --> 00:05:35,960 I've done one like seven times so there we go. 82 00:05:36,070 --> 00:05:39,800 So now we have three separate collections in this array. 83 00:05:39,880 --> 00:05:43,570 And we're going to use flat map to squish them down into one single array. 84 00:05:43,570 --> 00:05:51,570 So let's go ahead and type Let single collection equals collections dot flat map. 85 00:05:51,830 --> 00:05:52,440 OK. 86 00:05:52,780 --> 00:05:57,190 And what we can do is we can go ahead and just use those curly brackets and that's probably the simplest 87 00:05:57,190 --> 00:05:59,020 way to use flat map. 88 00:05:59,020 --> 00:06:03,130 And what we can actually do is just call a dollar sign 0 and what it's going to do is it's going to 89 00:06:03,130 --> 00:06:07,300 iterate over all those items and it's going to smush them down into a single array. 90 00:06:07,300 --> 00:06:14,010 So if I actually print this you'll see all the values are contained in a single array. 91 00:06:14,020 --> 00:06:15,500 That's pretty cool. 92 00:06:15,500 --> 00:06:22,090 But you know that's great but what if I wanted to do something with the values inside of this. 93 00:06:22,090 --> 00:06:28,420 The neat thing is that using these transformation functions we can actually nest them inside of each 94 00:06:28,420 --> 00:06:36,670 other so whatever happens to this we can actually call map on this and perform an action to modify the 95 00:06:36,670 --> 00:06:37,420 values inside. 96 00:06:37,420 --> 00:06:41,710 So let's say that we want it to return the square of all of these values. 97 00:06:41,710 --> 00:06:44,740 K whatever this value is multiplied by itself. 98 00:06:44,740 --> 00:06:53,180 So I can say let square collection equals collections dot flat map. 99 00:06:53,270 --> 00:06:55,810 OK and what we're going to do is the same thing as before. 100 00:06:55,900 --> 00:06:57,350 Dollar Sign 0. 101 00:06:57,580 --> 00:07:03,820 But instead of just doing that we're going to go ahead and call dot map on this because what it's done 102 00:07:03,820 --> 00:07:05,830 is it's returned an array right. 103 00:07:05,840 --> 00:07:07,120 Of all of the values. 104 00:07:07,240 --> 00:07:10,490 So we're going to take that array and we're going to map it. 105 00:07:10,540 --> 00:07:13,190 We're doing a map inside of a flat map. 106 00:07:13,360 --> 00:07:19,250 So to get each item we're going to go ahead and say Dollar Signs zero times dollar sign zero. 107 00:07:19,390 --> 00:07:24,340 We're taking the first item multiplying it by the first item and returning it to our flat map which 108 00:07:24,340 --> 00:07:26,110 is just an array of all those values. 109 00:07:26,110 --> 00:07:33,280 So if I print this the square collection you'll see that we get the square of every item two times two 110 00:07:33,280 --> 00:07:38,840 is four one times one is one 34 times 34 is one thousand one hundred fifty six. 111 00:07:38,890 --> 00:07:43,990 That is how we can actually link these together by nesting them and we can kind of multiply the values 112 00:07:44,440 --> 00:07:46,900 we did all of this in a single line of code. 113 00:07:46,900 --> 00:07:48,190 That's incredible. 114 00:07:48,190 --> 00:07:53,950 Normally this would take a lot more code and probably a pretty beefy function to get this same functionality. 115 00:07:53,950 --> 00:07:54,610 Pretty cool stuff. 116 00:07:54,610 --> 00:08:01,420 So let's go ahead let's move on to the next transformation which is called Compact map and compact map 117 00:08:01,450 --> 00:08:05,200 actually has one specific use case but it's very very cool. 118 00:08:05,200 --> 00:08:08,200 So let's go ahead and read what it says. 119 00:08:08,410 --> 00:08:15,760 It says right here it returns an array containing all of the non nil results of calling the given transformation. 120 00:08:15,760 --> 00:08:22,840 So this is a fantastic way to verify or I guess return only values that are not nil so let's go ahead 121 00:08:22,840 --> 00:08:26,170 and create an array that can have nil values. 122 00:08:26,170 --> 00:08:30,890 Let random returned names. 123 00:08:31,360 --> 00:08:34,230 And you know let's just pretend this is an array of string. 124 00:08:34,300 --> 00:08:37,200 Let's make it optional there so values can be nil. 125 00:08:37,330 --> 00:08:43,870 And this example would be for maybe if you got you know values pulled down from the Internet and maybe 126 00:08:43,870 --> 00:08:45,510 there was a missing piece of the data. 127 00:08:45,520 --> 00:08:48,640 So we'll say Steve was there. 128 00:08:48,760 --> 00:08:52,960 Maybe this guy wasn't so his name was nyl wasn't in the data. 129 00:08:53,060 --> 00:08:56,760 Bob let's put a. 130 00:08:57,100 --> 00:09:00,980 There we go Bob then Larry. 131 00:09:02,470 --> 00:09:07,540 And finally we'll just say the last guy was also missing so he's nil. 132 00:09:07,900 --> 00:09:12,380 You know maybe this was some some sports game or an event or something. 133 00:09:12,460 --> 00:09:18,220 And so now that we have an array that has some nil values we can call compact map to get an array that 134 00:09:18,310 --> 00:09:20,380 only includes the non-nil values. 135 00:09:20,380 --> 00:09:21,030 Check it out. 136 00:09:21,190 --> 00:09:25,700 Let valid data equals random return names. 137 00:09:25,720 --> 00:09:32,890 Compact map and using the little syntax here with the curly brackets. 138 00:09:32,890 --> 00:09:34,180 I can just return. 139 00:09:34,180 --> 00:09:38,980 Dollar Signs 0 and what it's going to do is it's going to map over all of the events all of the items 140 00:09:38,980 --> 00:09:39,550 rather. 141 00:09:39,790 --> 00:09:44,650 And if it's non-nil it's going to return it and appended to this new array valid data. 142 00:09:44,740 --> 00:09:46,460 If it is nil it's going to just ignore it. 143 00:09:46,510 --> 00:09:47,350 Skip over it. 144 00:09:47,350 --> 00:09:54,220 So if I print out valid data you'll see down here it'll print out only the valid data which is just 145 00:09:54,220 --> 00:10:00,250 the coolest thing I could see this being really useful particularly when pulling down data from an API 146 00:10:00,250 --> 00:10:00,700 online. 147 00:10:00,700 --> 00:10:02,470 Maybe you're not sure if there's going to be data. 148 00:10:02,470 --> 00:10:07,750 Something could come back as nil and if it is is using compact math is a really great way to prevent 149 00:10:07,750 --> 00:10:09,430 your app from crashing. 150 00:10:09,430 --> 00:10:14,830 So as you can see Steve Bob and Larry are the ones that are returned the values have been ignored. 151 00:10:14,830 --> 00:10:16,990 This is so cool so so helpful. 152 00:10:16,990 --> 00:10:22,750 So that is how compact app works the point of it is to return an array with all of the non-nil values 153 00:10:22,990 --> 00:10:24,610 so so helpful. 154 00:10:24,760 --> 00:10:26,980 We've got about two more that we're going to look at. 155 00:10:26,980 --> 00:10:31,690 One is filter and the other one is called reduce and filter is pretty straightforward. 156 00:10:31,690 --> 00:10:37,060 It does exactly what it sounds like it's going to go ahead and return an array containing in order the 157 00:10:37,060 --> 00:10:40,220 elements of a sequence that satisfy a given predicate. 158 00:10:40,360 --> 00:10:44,140 So it's going to basically return values that meet a certain condition. 159 00:10:44,140 --> 00:10:51,350 So first of all I'm going to create an array full of numbers so let's just say let digits OK. 160 00:10:51,580 --> 00:10:55,740 And that's going to be an array and we're just going to make one 30. 161 00:10:55,960 --> 00:10:59,740 I'm just going to put random numbers here. 162 00:11:03,760 --> 00:11:04,340 There we go. 163 00:11:04,420 --> 00:11:04,670 OK. 164 00:11:04,690 --> 00:11:06,310 Bunch of random numbers. 165 00:11:06,400 --> 00:11:08,140 Some are even some are odd. 166 00:11:08,170 --> 00:11:09,120 Lots of different things here. 167 00:11:09,130 --> 00:11:13,900 But what we're going to do is we're going to use a filter to basically filter out any values that are 168 00:11:13,900 --> 00:11:14,790 not even. 169 00:11:14,890 --> 00:11:22,690 So our array here is going to be called even digits and filtering out the even numbers in an array is 170 00:11:22,690 --> 00:11:25,400 actually one of the first programming challenges a lot of people do. 171 00:11:25,450 --> 00:11:28,000 And this would be a super easy way to do it if you knew about this. 172 00:11:28,000 --> 00:11:31,510 So if you call digits reduce 173 00:11:35,010 --> 00:11:41,760 if you call digits filter and then use the curly brackets there what we can actually do is we can set 174 00:11:41,790 --> 00:11:46,800 a condition inside these brackets and this condition is going to be what determines whether a number 175 00:11:46,800 --> 00:11:47,550 stays or not. 176 00:11:47,560 --> 00:11:54,060 So Dollar Signs 0 if the number right member this is our placeholder variable that's when the values 177 00:11:54,060 --> 00:12:01,470 are iterating through it's being set for every value if that number Madieu low to which the Doulos symbol 178 00:12:01,470 --> 00:12:04,540 basically divides and then gives you the remainder. 179 00:12:04,590 --> 00:12:11,910 So if the remainder is 0 then you know that it's an even number right because it can be evenly divided. 180 00:12:12,120 --> 00:12:14,280 And as you can see it ran through nine times. 181 00:12:14,280 --> 00:12:21,570 And if we print out even digits we should get an array that only contains even digits just like that. 182 00:12:21,570 --> 00:12:24,890 So we filtered the array for the condition that we want. 183 00:12:24,930 --> 00:12:27,910 And you can do this with many more things not just numbers. 184 00:12:28,020 --> 00:12:32,820 I can do this with strings I could do this with names and just for an example I'm going to copy and 185 00:12:32,820 --> 00:12:39,600 paste an example in here just for time's sake I don't want to make sure this video stays concise but 186 00:12:39,600 --> 00:12:42,360 if I had an array of names like so. 187 00:12:42,540 --> 00:12:50,550 Caleb Steve Stanley Mark Maximus Ilan I went ahead and I said names not filter and I checked to see 188 00:12:50,550 --> 00:12:57,210 the first character in every item and if it's s a capital S then it goes ahead and it adds it to the 189 00:12:57,510 --> 00:12:58,600 names array. 190 00:12:58,740 --> 00:13:02,860 And as you can see when it prints out only Steve and Stanley were remaining. 191 00:13:02,880 --> 00:13:07,950 So on one line I did what would normally take a few lines of code in a for loop. 192 00:13:07,950 --> 00:13:12,600 So very very cool stuff super efficient way to filter through data. 193 00:13:12,690 --> 00:13:17,460 We have one last transformation function to check out and it is called reduce. 194 00:13:17,640 --> 00:13:23,040 And let me paste in the definition here so that you can see what it is reduce reduce it returns the 195 00:13:23,040 --> 00:13:27,920 result of combining the elements of the sequence using the given closure. 196 00:13:28,080 --> 00:13:34,110 So what we can do is we can basically take a bunch of values in an array of the same type we can call 197 00:13:34,110 --> 00:13:40,680 reduce and what it's going to do is it's going to smush them down or I guess perform a calculation on 198 00:13:40,680 --> 00:13:46,570 them and we can either say you know plus or minus multiply divide things like that. 199 00:13:46,830 --> 00:13:54,090 And so what we're going to do first is just create maybe an array of values like so and I'm going to 200 00:13:54,090 --> 00:13:58,100 make these doubles so I'm going to include some decimal points at the end. 201 00:13:58,200 --> 00:14:01,830 And so let's just do three point zero 4.7. 202 00:14:01,890 --> 00:14:04,570 Twelve point sixty five. 203 00:14:04,590 --> 00:14:11,110 How about an own nine point twelve and one eighty seven point nine. 204 00:14:11,480 --> 00:14:13,170 So we have a bunch of values here. 205 00:14:13,170 --> 00:14:17,400 They are the inferred type of double. 206 00:14:17,640 --> 00:14:20,820 And what we're going to do with these values is we're going to add them together. 207 00:14:20,970 --> 00:14:27,150 So if we say let some equals values not reduce. 208 00:14:27,150 --> 00:14:32,810 And notice here that it asks for an initial result and then next partial result. 209 00:14:33,000 --> 00:14:36,530 Things like that that is the actual technical closure. 210 00:14:36,540 --> 00:14:42,480 But there's an easier way to use it where the ending item is going to be the operator we want to apply 211 00:14:42,570 --> 00:14:43,630 to the reduction. 212 00:14:43,800 --> 00:14:48,450 So we'll say plus we want to add everything and initial result is where we started. 213 00:14:48,460 --> 00:14:49,590 Are we starting at zero. 214 00:14:49,590 --> 00:14:55,290 Are we starting at 100 and this is helpful for maybe if you know in your app a player has a certain 215 00:14:55,350 --> 00:15:00,240 score and we're going to start at their score and then add up all of the points they scored or maybe 216 00:15:00,240 --> 00:15:02,520 all the bonuses they scored during a round of play. 217 00:15:02,520 --> 00:15:08,700 So you could pass in the initial result and then add any additional values that have been appended during 218 00:15:08,790 --> 00:15:09,840 a session of game play. 219 00:15:09,840 --> 00:15:10,950 That's just one example. 220 00:15:10,950 --> 00:15:14,120 So the initial result zero point zero. 221 00:15:14,220 --> 00:15:18,180 And if you check it out over here it prints out to seventeen point three seven. 222 00:15:18,270 --> 00:15:20,940 If you were to add this up on a calculator you'd find the same thing. 223 00:15:20,940 --> 00:15:22,610 So pretty cool stuff. 224 00:15:22,650 --> 00:15:26,190 If I were to start maybe at 100 maybe that's where my user started. 225 00:15:26,190 --> 00:15:31,040 You'll see that it changes to 3:17 because it adds 100 to the beginning score. 226 00:15:31,260 --> 00:15:32,840 Pretty cool stuff. 227 00:15:32,880 --> 00:15:36,920 Now of course you can do subtract and it'll basically start at zero. 228 00:15:36,920 --> 00:15:39,660 Then subtract all these so we end up with negative. 229 00:15:39,750 --> 00:15:41,600 We could do multiply. 230 00:15:41,940 --> 00:15:46,170 And of course since 0 multiplied by anything is zero that's what we get. 231 00:15:46,170 --> 00:15:52,140 But if we did something like one for instance we get a massive number because it multiplies everything. 232 00:15:52,320 --> 00:15:54,600 This altogether multiplied by 1. 233 00:15:54,600 --> 00:15:58,550 So I believe actually what it's doing is it's taking one times three. 234 00:15:58,560 --> 00:16:03,000 So that's three times four than times 12 then times nine times 187. 235 00:16:03,000 --> 00:16:09,360 So it's doing that or at Torrid Tivoli but that's how reduce works at smashers an array down into a 236 00:16:09,360 --> 00:16:11,010 singular value. 237 00:16:11,010 --> 00:16:12,030 Pretty cool stuff. 238 00:16:12,150 --> 00:16:14,130 But you can do it with more than just numbers. 239 00:16:14,130 --> 00:16:16,260 You can actually do it with strings as well. 240 00:16:16,410 --> 00:16:19,960 And you're probably wondering why would we want to ever reduce strings. 241 00:16:20,130 --> 00:16:23,330 Well maybe you have a bunch of chunks of strings and you want to add them together. 242 00:16:23,430 --> 00:16:23,670 OK. 243 00:16:23,760 --> 00:16:24,890 Just like this. 244 00:16:24,900 --> 00:16:29,870 My name is Caleb and I am a developer and then a period at the end. 245 00:16:29,910 --> 00:16:36,940 Now if I started this I could say hey take the Chunk's this string then reduce them into a single item 246 00:16:37,270 --> 00:16:38,520 but add this at the beginning. 247 00:16:38,520 --> 00:16:39,990 This is the starting value. 248 00:16:40,240 --> 00:16:41,560 And I'm saying you know to add. 249 00:16:41,560 --> 00:16:46,050 So what we end up with as you can see here is developer bio. 250 00:16:46,060 --> 00:16:48,370 My name is Caleb and I am a developer period. 251 00:16:48,580 --> 00:16:53,100 So what it did is it smushed the chunks together into one single sentence. 252 00:16:53,110 --> 00:16:54,040 It's pretty awesome. 253 00:16:54,230 --> 00:16:55,830 Super duper easy. 254 00:16:56,140 --> 00:16:58,780 And you know what I'm going to give you a bonus one here right at the end. 255 00:16:58,790 --> 00:17:03,450 There's another transformation that I was going to exclude but it is pretty cool. 256 00:17:03,610 --> 00:17:10,600 It's called Ziph and what it does is it creates a sequence of pairs K built out of two underlying sequences. 257 00:17:10,600 --> 00:17:14,290 So what it's going to do is it's going to take two separate sequences and smoosh them together into 258 00:17:14,290 --> 00:17:15,850 something that's a little more usable. 259 00:17:15,850 --> 00:17:19,290 So I'm going to paste an example here for time's sake. 260 00:17:19,380 --> 00:17:22,750 And so that'll show you actually how Zipp works. 261 00:17:22,810 --> 00:17:28,570 But basically I made an array here of name data and then an array of badge number data. 262 00:17:28,570 --> 00:17:35,680 Maybe this is an employee database Berrys number is this genos number is this divans number is this. 263 00:17:35,890 --> 00:17:43,030 And what I can do is I can call zip now zip is a bit different because it is a function that we're calling 264 00:17:43,030 --> 00:17:48,340 and we're not actually able to call it on one item right because it zips 2 together. 265 00:17:48,460 --> 00:17:53,020 But it is a transformation because it works in the same exact ways it's transforming data into a new 266 00:17:53,020 --> 00:17:54,080 data type. 267 00:17:54,130 --> 00:18:01,510 And so basically when you call Zipp you'll notice it'll except let me show you here it'll accept let 268 00:18:01,510 --> 00:18:03,220 me try this here zip. 269 00:18:03,220 --> 00:18:03,940 There we go. 270 00:18:03,970 --> 00:18:06,430 It accepts two separate sequences right. 271 00:18:06,430 --> 00:18:08,650 An array a dictionary things like that. 272 00:18:08,710 --> 00:18:18,100 And so I can pass in the name data like you saw before and the badge number data and what ends up happening 273 00:18:18,250 --> 00:18:24,790 is we get an array of tuples or tuples However you say it and they're linked together so Barry is now 274 00:18:24,790 --> 00:18:26,200 linked with his ID badge. 275 00:18:26,200 --> 00:18:28,570 Gina is now linked with her ID badge. 276 00:18:28,570 --> 00:18:31,440 And so this is a really great way to access that. 277 00:18:31,450 --> 00:18:38,430 And let's say that we wanted to access you know Barrie's information so I could say print zipped results. 278 00:18:38,860 --> 00:18:45,090 And maybe I want to go into the first item here which is Barry of course and you can see it here. 279 00:18:45,100 --> 00:18:49,900 Now let's say that I wanted to access you know his name could call DOT 0 and that gets the first item 280 00:18:50,200 --> 00:18:52,700 as you can see on the screen here it prints out Barry. 281 00:18:52,720 --> 00:18:55,590 Same thing for his ID badge one. 282 00:18:55,870 --> 00:18:57,190 And there's his ID badge. 283 00:18:57,190 --> 00:18:57,820 Pretty cool stuff. 284 00:18:57,820 --> 00:18:59,770 So that is how zip works. 285 00:18:59,770 --> 00:19:00,920 But guys this is it. 286 00:19:00,940 --> 00:19:03,400 This is transformations we have learned a lot. 287 00:19:03,430 --> 00:19:05,600 Lots of really cool stuff here. 288 00:19:05,710 --> 00:19:07,320 We learned about math. 289 00:19:07,570 --> 00:19:14,950 We learned about flat map compact map filter reduce and zip and all of these allow you to really really 290 00:19:14,950 --> 00:19:19,560 really make your code more compact and a little more efficient even. 291 00:19:19,690 --> 00:19:25,060 We also learned about nesting various transformations inside other transformations to achieve you know 292 00:19:25,060 --> 00:19:29,700 the intended result that we wanted which was to modify the values after squishing them together. 293 00:19:29,740 --> 00:19:35,380 You know from a flat map we could have done you know a map and then a filter where we map the values 294 00:19:35,410 --> 00:19:37,960 and then we filter them based on a certain condition. 295 00:19:37,960 --> 00:19:43,510 The possibilities are basically endless and it's amazing that all of this can be fit onto one single 296 00:19:43,510 --> 00:19:43,840 line. 297 00:19:43,840 --> 00:19:45,270 Very very cool stuff. 298 00:19:45,280 --> 00:19:46,630 Thank you so much for tuning in. 299 00:19:46,630 --> 00:19:49,300 And this has been a quick video on swift transformations.