1 00:00:00,600 --> 00:00:01,800 Hello, dear friends. 2 00:00:02,070 --> 00:00:05,880 So this is the lesson that we're going to learn some other data types in Blyton. 3 00:00:06,570 --> 00:00:07,350 So let's start. 4 00:00:09,910 --> 00:00:15,910 As you remember, we talked about the data type concept in Python in some of our previous lessons. 5 00:00:16,750 --> 00:00:19,750 We've also talked about the concepts of strings and numbers. 6 00:00:20,860 --> 00:00:25,030 Now we're going to dive a little deeper and examine the list data type in Python. 7 00:00:25,630 --> 00:00:33,580 But before we talk about the concept of list, we also need to understand the concept of sequences. 8 00:00:34,720 --> 00:00:40,990 So what are sequences the most basic data structure in Python is sequences. 9 00:00:41,980 --> 00:00:47,380 Each element of a sequence is assigned a number, its position or index. 10 00:00:48,250 --> 00:00:49,840 The first index is zero. 11 00:00:50,470 --> 00:00:51,910 The second index is one. 12 00:00:52,000 --> 00:00:52,510 And so on. 13 00:00:53,440 --> 00:00:56,380 So Python has six built in types of sequences. 14 00:00:57,310 --> 00:00:58,960 And we already know one of them. 15 00:00:59,380 --> 00:01:00,340 Do you remember which one? 16 00:01:01,330 --> 00:01:02,770 Yep, strings. 17 00:01:04,120 --> 00:01:07,840 And the other most common ones are lists, tuples and dictionaries. 18 00:01:08,710 --> 00:01:13,270 Now, there are certain things that you can do with all sequence types. 19 00:01:14,580 --> 00:01:21,330 So these operations will include indexing, slicing, adding, multiplying and checking for membership. 20 00:01:23,050 --> 00:01:29,710 In addition, Python has some built in functions for finding the length of a sequence and for finding 21 00:01:29,710 --> 00:01:32,590 it largest and smallest elements. 22 00:01:33,520 --> 00:01:37,360 So we're going to talk about all of these operations a bit later in the course. 23 00:01:38,380 --> 00:01:41,980 Right now, we want to talk about the list concept in Python. 24 00:01:42,310 --> 00:01:42,640 Right. 25 00:01:43,540 --> 00:01:46,990 So what is this list that you speak of? 26 00:01:48,250 --> 00:01:52,120 So the list is the most versatile data type available in Python. 27 00:01:52,750 --> 00:01:59,980 And it can be written as a list of comma separated values or items between square brackets. 28 00:02:01,240 --> 00:02:08,470 An important thing to know about a list is that items in a list don't need to be of the same type. 29 00:02:09,280 --> 00:02:10,240 What? 30 00:02:11,230 --> 00:02:13,090 So how do we create a list? 31 00:02:14,150 --> 00:02:18,230 Well, it just so happens that creating a list is one of the simplest things you can do. 32 00:02:18,260 --> 00:02:23,540 It's as simple as putting different comma separated values between square brackets. 33 00:02:24,770 --> 00:02:31,910 Lists typically store homogenous data that is values of the same data type. 34 00:02:33,200 --> 00:02:38,330 So, for example, let's define a variable named my list minus equals. 35 00:02:41,770 --> 00:02:43,840 One, two, three, four, five, six, seven, eight. 36 00:02:49,370 --> 00:02:51,920 So we created our variable, now let's check IDs type. 37 00:02:56,920 --> 00:02:59,920 And of course, its type is list so we can move on. 38 00:03:01,980 --> 00:03:05,830 As you can see in this list, all of the elements are numbers. 39 00:03:07,410 --> 00:03:11,820 But we also said that not elements have to be the same type. 40 00:03:13,280 --> 00:03:17,990 So if we define a variable name, my list to my list equals to. 41 00:03:23,020 --> 00:03:23,930 One, two, three. 42 00:03:23,960 --> 00:03:25,050 Apple, banana. 43 00:03:25,120 --> 00:03:27,370 15, 25 A. B.. 44 00:03:27,790 --> 00:03:28,840 Thirteen point five. 45 00:03:37,500 --> 00:03:39,150 So we created our variable. 46 00:03:39,180 --> 00:03:40,560 Now let's check it's type. 47 00:03:41,840 --> 00:03:42,800 And the type. 48 00:03:48,320 --> 00:03:49,340 Is also a list. 49 00:03:50,270 --> 00:03:51,260 So let's move on. 50 00:03:52,130 --> 00:03:55,100 And as you can see in this list, different types of data were stored. 51 00:03:55,310 --> 00:03:58,220 Such lists are called heterogenous lists. 52 00:03:59,290 --> 00:04:05,680 So we can also define a list in and on their list, such as my list and score three equals. 53 00:04:09,310 --> 00:04:10,060 One, two, three. 54 00:04:11,410 --> 00:04:12,550 One, two, three. 55 00:04:12,580 --> 00:04:13,570 Apple, banana. 56 00:04:16,450 --> 00:04:17,230 Apple, banana. 57 00:04:21,400 --> 00:04:24,550 Now, of course, this type of list is called a nested list. 58 00:04:25,510 --> 00:04:28,000 So if you want to, we can check this one's data type. 59 00:04:33,940 --> 00:04:40,000 And as you can see, it's also a list, so the lists elements are mutable. 60 00:04:40,630 --> 00:04:43,330 It means that their elements can be modified. 61 00:04:44,330 --> 00:04:46,550 So that gives you all kinds of fun, huh? 62 00:04:47,510 --> 00:04:52,050 Now, unlike list, some sequences are immutable. 63 00:04:52,130 --> 00:04:56,090 So that means they can't be modified like tuples. 64 00:04:57,900 --> 00:04:59,370 What are troubles? 65 00:05:00,930 --> 00:05:03,480 Well, they are temples are also sequences. 66 00:05:04,260 --> 00:05:12,180 They are really similar to a list, but their biggest difference is that they cannot be changed. 67 00:05:12,390 --> 00:05:14,310 So we call them immutable. 68 00:05:14,850 --> 00:05:15,570 And why is it? 69 00:05:16,590 --> 00:05:23,670 Well, when we need immutable data in our program, such as a config file or something else, tuples 70 00:05:23,850 --> 00:05:26,400 give us the opportunity to be able to write that. 71 00:05:27,300 --> 00:05:28,860 So then how do we create a tuple? 72 00:05:30,010 --> 00:05:36,700 While creating a table is as simple as putting different comma separated values, and optionally we 73 00:05:36,700 --> 00:05:40,570 can put these commas everyday values between parentheses also. 74 00:05:42,140 --> 00:05:43,730 So now let's see how to create a temple. 75 00:05:44,850 --> 00:05:47,130 We will define a variable named My Temple. 76 00:05:52,640 --> 00:05:54,230 One, two, three, four, five, six, seven, eight. 77 00:05:56,740 --> 00:06:00,070 So we create our variable, let's check its type. 78 00:06:03,990 --> 00:06:06,570 So this tape is indeed a table, so move on. 79 00:06:08,640 --> 00:06:12,300 And as you can see in this table, all elements are numbers. 80 00:06:13,550 --> 00:06:19,760 But now you also remember that I said that not all elements have to be the same type. 81 00:06:20,420 --> 00:06:23,030 So we can define a variable named might double to. 82 00:06:28,040 --> 00:06:31,190 Might hold two equals one, two, three, apple, banana. 83 00:06:33,730 --> 00:06:34,810 13 PTFI. 84 00:06:36,160 --> 00:06:37,900 A B, thirteen point five. 85 00:06:41,200 --> 00:06:43,070 All right, great, so we created our variable. 86 00:06:43,090 --> 00:06:44,110 Let's check it's type. 87 00:06:48,840 --> 00:06:51,840 This type is also a tuple so we can move on. 88 00:06:53,100 --> 00:06:57,060 And as you can see in this table, different types of data were stored. 89 00:06:58,080 --> 00:07:01,050 Such doubles are called heterogenous doubles. 90 00:07:02,510 --> 00:07:09,830 Now we can also define a table in another table, just like in lists such as my table three equals. 91 00:07:11,570 --> 00:07:13,010 One, two, three, one, two, three. 92 00:07:15,950 --> 00:07:17,240 Apple, banana. 93 00:07:20,800 --> 00:07:22,060 Apple, banana. 94 00:07:24,860 --> 00:07:28,670 So this type of list is, remember, called in nested list. 95 00:07:29,420 --> 00:07:31,610 And if you want, we can check this one's datatype. 96 00:07:39,810 --> 00:07:41,830 And as you can see, it's also a tuple. 97 00:07:44,080 --> 00:07:47,710 So far, almost everything is the same as a list, right? 98 00:07:49,230 --> 00:07:51,180 And I hear what you're saying. 99 00:07:51,620 --> 00:07:57,900 Well, I didn't see any difference between listen double's and my young apprentice. 100 00:07:59,160 --> 00:08:06,240 We will see all the differences between the lists and tuples when we start to use operators and methods. 101 00:08:07,010 --> 00:08:07,530 Hmm. 102 00:08:08,400 --> 00:08:09,570 Now let's continue. 103 00:08:10,410 --> 00:08:15,060 What if we want to create a trouble with one element? 104 00:08:16,110 --> 00:08:17,520 So let's define a variable name. 105 00:08:17,520 --> 00:08:20,250 My table for my double for equals. 106 00:08:22,380 --> 00:08:26,820 Five, we create our variable and let's check IDs type. 107 00:08:30,650 --> 00:08:33,680 Was its type, is it? 108 00:08:34,070 --> 00:08:34,820 But why? 109 00:08:35,270 --> 00:08:36,500 Everything looks fine. 110 00:08:36,850 --> 00:08:38,990 But why does our variable datatype. 111 00:08:39,020 --> 00:08:39,320 Why? 112 00:08:39,320 --> 00:08:40,390 Why is it end? 113 00:08:41,670 --> 00:08:43,430 Are the reasons very simple? 114 00:08:44,150 --> 00:08:49,400 Previously, when we defined a tuple, we use the expression comma separated values. 115 00:08:50,060 --> 00:08:55,040 So if we want to create a table with one element, we always use a comma. 116 00:08:55,520 --> 00:08:56,120 Let's try it. 117 00:08:57,230 --> 00:08:59,990 So we define a variable named my tuple five. 118 00:09:00,290 --> 00:09:01,820 My tuple five equals. 119 00:09:05,180 --> 00:09:09,080 Five comma, and we create our variable. 120 00:09:09,350 --> 00:09:10,430 So let's check it's type. 121 00:09:17,280 --> 00:09:20,460 Oh, thank God it's Tapo. 122 00:09:21,390 --> 00:09:26,130 OK, so now if everything seems OK, we can continue with another datatype. 123 00:09:26,370 --> 00:09:27,810 It's called Dictionaries, Yohana. 124 00:09:28,290 --> 00:09:29,100 OK, follow me. 125 00:09:31,170 --> 00:09:32,670 So what are dictionaries here? 126 00:09:33,750 --> 00:09:37,770 So dictionaries are data set that behaves just like real life dictionaries. 127 00:09:38,430 --> 00:09:43,530 But this data set is inherently different from any data set that we've ever seen here before. 128 00:09:44,310 --> 00:09:48,450 Each element in the dictionary is kept as key and value. 129 00:09:49,500 --> 00:09:50,580 So what is the key? 130 00:09:51,690 --> 00:09:54,330 Well, let's think about an English dictionary in real life. 131 00:09:54,870 --> 00:09:58,020 We choose a word in English, for example, decrees. 132 00:09:59,080 --> 00:10:06,820 In the English dictionary, decrease means make or become smaller or fewer in size amount, intensity 133 00:10:06,820 --> 00:10:07,570 or degree. 134 00:10:08,380 --> 00:10:10,930 So here decrease is our key. 135 00:10:11,980 --> 00:10:14,200 And this part is our value. 136 00:10:15,730 --> 00:10:16,150 Clear. 137 00:10:16,720 --> 00:10:18,100 OK, so now let's move on. 138 00:10:18,850 --> 00:10:20,230 How do we create a dictionary? 139 00:10:21,250 --> 00:10:25,810 So each key is separated from its value by a colon. 140 00:10:27,070 --> 00:10:33,910 The items are separated by commas, and the whole thing is enclosed in curly braces. 141 00:10:35,230 --> 00:10:42,310 Such as we define a variable named my DECT, so my dick equals zero, colon zero. 142 00:10:44,480 --> 00:10:46,070 One, Colin, one. 143 00:10:48,430 --> 00:10:49,960 To call in to. 144 00:10:52,450 --> 00:10:53,620 Three call and three. 145 00:10:55,530 --> 00:10:57,150 For Colin, for. 146 00:11:00,070 --> 00:11:01,870 Five, Colin, five. 147 00:11:03,060 --> 00:11:04,260 So let's check the data type. 148 00:11:09,590 --> 00:11:14,270 Look at that, you see, our variable's datatype is DECT, which means dictionary. 149 00:11:15,290 --> 00:11:18,200 And what if we wanted to find an empty dictionary? 150 00:11:18,830 --> 00:11:19,610 Oh, it's so simple. 151 00:11:20,660 --> 00:11:25,520 The dictionary, without any items, is written with just two curly braces like this. 152 00:11:28,260 --> 00:11:29,460 So let's check the datatype. 153 00:11:38,590 --> 00:11:42,940 Keys are unique within a dictionary, while values may not be. 154 00:11:43,510 --> 00:11:47,380 For example, we define a variable named mine dict, too. 155 00:11:48,310 --> 00:11:56,590 So in this dictionary, keys are the name of months and the values are the numbers of days in the corresponding 156 00:11:56,590 --> 00:11:56,860 month. 157 00:11:59,450 --> 00:12:03,170 OK, my dick two equals Jan Gowland, 31. 158 00:12:05,700 --> 00:12:07,440 February Collen 28. 159 00:12:09,610 --> 00:12:11,050 March Quillin, 31. 160 00:12:17,880 --> 00:12:18,990 So let's check the datatype. 161 00:12:25,330 --> 00:12:26,410 It's also a dictionary. 162 00:12:27,190 --> 00:12:30,550 And as you can see, different keys can have the same value. 163 00:12:31,940 --> 00:12:35,870 Now, I wonder if we want to enter more than one entry per key. 164 00:12:37,010 --> 00:12:39,140 We define a variable named Mindich three. 165 00:12:44,210 --> 00:12:47,390 Mind EC3 equals name Golin John. 166 00:12:49,930 --> 00:12:52,240 Comma, surname, Colin Doe. 167 00:12:54,930 --> 00:12:58,170 Cummer job Colan unemployed. 168 00:13:01,750 --> 00:13:05,200 KOMMA job Colan, software developer. 169 00:13:11,760 --> 00:13:12,870 So let's check the date of time. 170 00:13:22,100 --> 00:13:23,120 It's also a dictionary. 171 00:13:23,990 --> 00:13:30,350 And as you can see, we duplicated the key named John and gave it to different values. 172 00:13:31,100 --> 00:13:33,200 But what value did it take? 173 00:13:34,010 --> 00:13:38,330 As Jack, print my DECT three job. 174 00:13:49,730 --> 00:13:50,330 Colon. 175 00:13:51,610 --> 00:13:54,070 Karma, my DECT three job. 176 00:14:06,320 --> 00:14:08,630 And the result is software developer. 177 00:14:09,620 --> 00:14:15,200 So that means when duplicate keys encountered during the assignment, the last assignment went. 178 00:14:16,820 --> 00:14:19,070 The values of a dictionary can be of any type. 179 00:14:19,430 --> 00:14:25,220 But the keys must be of an immutable data type, such as strings, numbers or tables. 180 00:14:26,830 --> 00:14:30,100 For example, will define a variable named mine dict for. 181 00:14:34,110 --> 00:14:37,860 My date for equals name Bentley. 182 00:14:41,480 --> 00:14:42,110 Model. 183 00:14:43,270 --> 00:14:44,350 Brooklands. 184 00:14:47,930 --> 00:14:48,710 Yea. 185 00:14:50,070 --> 00:14:51,330 1997. 186 00:14:52,770 --> 00:14:53,040 All right. 187 00:14:53,130 --> 00:14:57,960 Oh, that's a really nice car, but that's not the point when we run this code. 188 00:14:58,200 --> 00:14:59,460 Python gives us an error. 189 00:14:59,820 --> 00:15:00,270 Why? 190 00:15:00,480 --> 00:15:03,660 It says uncatchable type list. 191 00:15:05,000 --> 00:15:05,360 Wow. 192 00:15:06,710 --> 00:15:07,760 Never mind about that. 193 00:15:08,330 --> 00:15:10,580 The values of a dictionary can be of any type. 194 00:15:10,970 --> 00:15:14,270 But the keys must be of an immutable data type. 195 00:15:14,630 --> 00:15:17,210 This was the general outline of dictionaries. 196 00:15:17,780 --> 00:15:18,710 Let's continue for now. 197 00:15:20,710 --> 00:15:26,470 So now I got to introduce you to our final data type, which is called sets. 198 00:15:27,190 --> 00:15:30,100 So what our sets and why didn't you tell me about this before? 199 00:15:31,120 --> 00:15:37,240 So our sets are closely linked to the concept of sets, which we know for mathematics. 200 00:15:37,240 --> 00:15:37,540 Right. 201 00:15:38,800 --> 00:15:42,250 Also, this data type has all the properties of sets in map. 202 00:15:43,120 --> 00:15:46,150 That is to say, the intersection, Joy. 203 00:15:47,310 --> 00:15:48,990 So what's the difference? 204 00:15:49,980 --> 00:15:55,740 Well, the difference that we know from sets in mathematics also apply to sets in Python. 205 00:15:56,910 --> 00:15:58,200 So how do we create a set? 206 00:15:59,300 --> 00:16:04,340 Creating a said is as simple as putting different comma separated values between curly brackets. 207 00:16:05,330 --> 00:16:07,430 We define a variable named my set. 208 00:16:07,880 --> 00:16:08,150 All right. 209 00:16:08,150 --> 00:16:10,490 So Micelle equals one, two, three, four, five. 210 00:16:15,710 --> 00:16:16,940 And we create our variable. 211 00:16:17,090 --> 00:16:18,080 Let's check IDs type. 212 00:16:20,760 --> 00:16:21,810 It's Tiber's set. 213 00:16:23,200 --> 00:16:24,770 Now let's define another variable. 214 00:16:24,920 --> 00:16:26,170 They might set two. 215 00:16:28,240 --> 00:16:32,140 I said two equals A, B, C, D and E. 216 00:16:39,790 --> 00:16:41,020 And we create our variable. 217 00:16:41,170 --> 00:16:42,160 Let's check IDs type. 218 00:16:48,520 --> 00:16:49,570 It's type of set. 219 00:16:52,420 --> 00:16:53,710 Now, why do we need to use it? 220 00:16:54,610 --> 00:16:58,930 Because yet, as in math, our data set that whole. 221 00:16:59,140 --> 00:17:00,670 Only one of each element. 222 00:17:01,270 --> 00:17:07,240 So this means that when the set is created, the duplicate element is automatically eliminated. 223 00:17:08,320 --> 00:17:09,820 All right, so let me show you an example. 224 00:17:11,000 --> 00:17:14,330 So here we will define a variable named my set free. 225 00:17:14,990 --> 00:17:21,980 I said three equals one to two, three, three, three, four, four, five. 226 00:17:24,120 --> 00:17:26,880 Now, when we run this code, our sets been created. 227 00:17:27,390 --> 00:17:28,220 Now let's check it. 228 00:17:28,350 --> 00:17:29,190 I set three. 229 00:17:30,550 --> 00:17:33,550 And look at that, the repeating elements have been eliminated. 230 00:17:35,050 --> 00:17:40,150 So in this lesson, we learned the rest of the important data types in Python and how to define them 231 00:17:40,780 --> 00:17:46,810 in the next lesson, we will learn the useful data types of operations and methods in Python. 232 00:17:47,590 --> 00:17:49,360 So I'll see you in that next lesson. 233 00:17:50,080 --> 00:17:53,170 Review what you need to know and have a nice day.