1 00:00:00,750 --> 00:00:05,430 In this video, we will divide over the biggest data stream into two parts. 2 00:00:05,820 --> 00:00:12,390 There it is, our X variables, which are our independent variables and variable, which is our target 3 00:00:12,390 --> 00:00:14,190 variable or dependent variable. 4 00:00:14,790 --> 00:00:22,700 You know, that were target variable is collection variable and all the remaining 18 variables, auto 5 00:00:22,710 --> 00:00:24,600 or independent variable. 6 00:00:26,190 --> 00:00:34,380 Since we want all the 18 variables in the world X data frame, we can either rate all the 18 column 7 00:00:34,380 --> 00:00:45,090 names using B.F. and the square record, or we can use B.F. dot block to remove collection variable 8 00:00:45,270 --> 00:00:46,230 from our data frame. 9 00:00:48,380 --> 00:00:51,050 Since removing the election variable is easier. 10 00:00:54,110 --> 00:00:55,420 We'll use lock. 11 00:00:56,040 --> 00:01:01,920 I hope you remember lock from our crash course in lock. 12 00:01:02,040 --> 00:01:07,080 We first have to mention the rules since we want all the rules. 13 00:01:07,500 --> 00:01:09,240 We just have to put a call on symbol. 14 00:01:09,330 --> 00:01:10,830 This means all the rules. 15 00:01:11,700 --> 00:01:21,990 And then after comma, we need to specify the columns we need since we need all the columns except the 16 00:01:21,990 --> 00:01:25,110 collection column will be of columns. 17 00:01:25,830 --> 00:01:28,020 And this should not be equal to collection. 18 00:01:28,590 --> 00:01:29,550 We are saying that. 19 00:01:31,030 --> 00:01:34,060 Get all the columns except the collection. 20 00:01:34,140 --> 00:01:34,440 Call them. 21 00:01:36,490 --> 00:01:39,470 So if we write exequatur, would be, if not lock. 22 00:01:40,420 --> 00:01:42,910 And first, we need to specify the rules. 23 00:01:43,450 --> 00:01:44,290 We need all the rules. 24 00:01:44,320 --> 00:01:48,370 That's why we are we are putting Colen and we don't need collection. 25 00:01:48,640 --> 00:01:53,230 Well, if we run this, we have our equitable. 26 00:01:54,380 --> 00:02:00,710 We can look at the sample of this data frame by using XDR type method. 27 00:02:11,170 --> 00:02:18,790 You can see all lower independent very well out here and our dependent variable that is collection, 28 00:02:18,790 --> 00:02:20,950 we're will not in this data frame. 29 00:02:22,520 --> 00:02:29,780 We can also check the shape of this data frame to confirm that there is no collection of. 30 00:02:35,890 --> 00:02:37,240 Since I would be if. 31 00:02:38,710 --> 00:02:39,940 Had 20 golems. 32 00:02:40,750 --> 00:02:44,930 We have only 19 columns in our X little frame. 33 00:02:46,000 --> 00:02:50,410 Similarly, we will create a separate data frame for our targeted variable, which is why. 34 00:02:51,220 --> 00:02:55,690 And here we are then in the collection are able from our B of frame. 35 00:02:56,080 --> 00:02:57,540 So we will just start D.F.. 36 00:02:57,670 --> 00:03:01,000 And in this square record will mention the column name, which is collection. 37 00:03:03,690 --> 00:03:04,680 We can run this. 38 00:03:07,370 --> 00:03:10,640 And again, we can take the simple of first fibros. 39 00:03:15,990 --> 00:03:18,740 So here we have the sample of our way. 40 00:03:19,020 --> 00:03:22,640 And you can see that we only have one column here. 41 00:03:24,430 --> 00:03:26,760 Is zero one, two, three, four our indexes. 42 00:03:27,060 --> 00:03:32,040 And this forty eight thousand forty three thousand two hundred are the values. 43 00:03:32,350 --> 00:03:34,740 These are our collection values. 44 00:03:36,090 --> 00:03:42,110 We can again use the shape method to get the number of rows of our visitors'. 45 00:03:45,200 --> 00:03:48,320 You can see that the Nemeroff rose. 46 00:03:49,720 --> 00:03:51,230 It's five hundred and six. 47 00:03:52,220 --> 00:03:55,910 Same as our equity will be if we had even. 48 00:03:57,200 --> 00:04:01,890 In the next video, we'll split our data and to test and drain. 49 00:04:01,940 --> 00:04:02,330 But.