1 00:00:06,020 --> 00:00:06,630 Here we go. 2 00:00:07,160 --> 00:00:10,690 So here we are with the last bloating that is known as the metric. 3 00:00:10,800 --> 00:00:13,600 They're a little different from the all we have learned before. 4 00:00:14,000 --> 00:00:17,680 Because with that we can use distinctly the data sets and broke them. 5 00:00:17,870 --> 00:00:24,980 And I have classified them according to point and distribution and figured but now we will move to this 6 00:00:24,980 --> 00:00:25,490 one. 7 00:00:25,490 --> 00:00:27,230 Here we have two data sets. 8 00:00:27,230 --> 00:00:28,710 That is first the tips. 9 00:00:28,730 --> 00:00:36,320 The one we are using in most of the cases you will get this one here we have seven columns in which 10 00:00:36,320 --> 00:00:40,460 we have two numerical columns and four string type columns. 11 00:00:40,460 --> 00:00:42,660 Then we had this on flights. 12 00:00:43,250 --> 00:00:50,210 And if you print the head of that one you will get a simple data set in which we have only truculence 13 00:00:50,390 --> 00:00:54,460 to denoting numerical values one denoting strings. 14 00:00:54,500 --> 00:00:57,980 So this one is a little easier to use here. 15 00:00:57,980 --> 00:01:01,310 You can also use an other dataset but I'm going to use this one. 16 00:01:02,270 --> 00:01:09,240 So first of all if you go to the gallery you will find here we have to solve metric bloat that is first 17 00:01:09,240 --> 00:01:13,390 to the heat map this one second one is the cluster map. 18 00:01:13,620 --> 00:01:20,350 Any payload which is showing values like these here you will notice corresponding values to every particular 19 00:01:20,700 --> 00:01:21,790 through and column. 20 00:01:21,790 --> 00:01:25,460 These are denoting metric dots. 21 00:01:25,660 --> 00:01:29,590 And one more thing they are not known as the plots they are known as the maps. 22 00:01:29,590 --> 00:01:36,940 This thing here any thing that we are going to work with Dedmon require maps instead of plot they are 23 00:01:37,000 --> 00:01:41,080 parameters like color etc are also different that we are going to discuss here. 24 00:01:42,420 --> 00:01:48,780 Hey if you notice we have a bar here which is showing the amplitude with color like light to the color 25 00:01:49,540 --> 00:01:51,950 higher value 606 is the maximum. 26 00:01:51,990 --> 00:01:58,200 And later devalue darker the value lower the amplitude. 27 00:01:58,200 --> 00:02:00,180 So let's just move to this one. 28 00:02:00,460 --> 00:02:03,850 One more thing now we cannot just directly applaud that. 29 00:02:04,050 --> 00:02:12,420 Like if I write Come on S.A. dot heat map and then I provide just like tips. 30 00:02:12,420 --> 00:02:16,960 This will show me at a and if you focus on the Edit here you will find a better. 31 00:02:17,070 --> 00:02:22,260 This is something a little different maybe you will not get a vibe bloating in bloating you will just 32 00:02:22,260 --> 00:02:29,610 get syntax errors then you write something unnecessary like this thing here syntax ETA you will get 33 00:02:29,610 --> 00:02:37,280 value add a but not the type that type something when we have used different kinds of data from that 34 00:02:37,490 --> 00:02:38,800 one that is required there. 35 00:02:39,120 --> 00:02:46,450 And here these datasets are required to be changed in metric dataset. 36 00:02:46,470 --> 00:02:52,110 After that we can use these with the heat maps and based on the conversion we have two methods. 37 00:02:52,200 --> 00:02:53,790 There is first one water. 38 00:02:53,880 --> 00:02:59,260 Second one is known as the pivot method both of which we are going to discuss here. 39 00:02:59,280 --> 00:03:04,260 First one is this year you are a simple one but not used. 40 00:03:04,350 --> 00:03:11,320 This one is something like if I have tips and I make this one do so that it will be different from that 41 00:03:11,320 --> 00:03:17,170 one you just need to write the original one that is tips don't seawater Francis. 42 00:03:17,550 --> 00:03:19,510 Now this dip is converted into metric. 43 00:03:19,740 --> 00:03:26,550 If you print that one you will find a metrics they some drawbacks in this metric like you do not have 44 00:03:26,580 --> 00:03:32,520 all the values like here I have three of the new one so the numerical columns that only present here 45 00:03:32,550 --> 00:03:39,720 but did not contain all the values like here we have only nine values that they are values like something 46 00:03:39,720 --> 00:03:46,110 corresponding Total Total will one day one say sized one because the variation with them self is always 47 00:03:46,110 --> 00:03:54,240 same then we have the tip the total bill and here we have with totally opposite one but the values are 48 00:03:54,240 --> 00:03:54,890 same there. 49 00:03:55,830 --> 00:03:58,640 So that's why it's not use because it lacked the values. 50 00:03:58,680 --> 00:04:02,260 If you do the same with the flight like I have flight. 51 00:04:02,910 --> 00:04:13,740 And this will be flights don't see order princes you will get flight to like this one only four values 52 00:04:14,550 --> 00:04:24,650 but now you can use these values to plot like just use here send don't heat map now you re not required 53 00:04:24,650 --> 00:04:31,470 to explode here because here the map is doing the same thing it's mapping the values now just provide 54 00:04:31,590 --> 00:04:41,070 tips you will get an idea as soon as don't it map so that when I have again done with the tips do original 55 00:04:41,070 --> 00:04:43,390 value converted values tip. 56 00:04:44,050 --> 00:04:50,490 So for that one Navy go here we have the heat map showing all the nine values available in that one 57 00:04:50,850 --> 00:05:02,780 if you do same thing with the flight to just NASA send us don't heat map then the princes and David 58 00:05:02,790 --> 00:05:12,800 go with that one shift and then you will get this one so minting it lacks the values that why we don't 59 00:05:12,800 --> 00:05:13,430 use this one. 60 00:05:13,820 --> 00:05:19,550 But let me show you some of the modification you can do and these modification will be same with the 61 00:05:19,550 --> 00:05:26,320 method to also Lego's DePalma does seem so teaching you that one on a little graph is more easier and 62 00:05:26,330 --> 00:05:34,370 if you notice these two look pretty similar but he has more values he doesn't have and one more thing 63 00:05:34,400 --> 00:05:42,080 if you notice there this one is with the flights the same day as a I'm using but it has only four values 64 00:05:42,110 --> 00:05:49,550 and it has approximately 144 values that is twelve go straight so how do values out there. 65 00:05:49,640 --> 00:05:55,790 So that will is something we can do the second matter but before that here like if you want to have 66 00:05:55,790 --> 00:06:05,000 the values denoting to particular of these boxes like these values when I had to at 115 so you can just 67 00:06:05,000 --> 00:06:13,190 do and not a barometer here and make this one true shift return you will get two values 68 00:06:16,250 --> 00:06:23,210 same with this one you will have the values if you can notice diagonals are 1 1 and the corresponding 69 00:06:23,210 --> 00:06:24,140 values are different. 70 00:06:24,770 --> 00:06:31,130 These are two seeing these two same these two same after that if you need some separation between these 71 00:06:31,130 --> 00:06:38,120 boxes like you did not equate attachment NAND you can just straight line winds make sure you are also 72 00:06:38,120 --> 00:06:52,560 using SDM and make this one then you will get the arrows attributed to let me check out Dedmon soda. 73 00:06:52,590 --> 00:06:57,930 I have made a spelling mistake here that is w I'd be SD. 74 00:06:57,990 --> 00:07:00,150 This one is to. 75 00:07:00,240 --> 00:07:01,670 So sorry for that man. 76 00:07:01,860 --> 00:07:03,930 I got a little mistake while typing. 77 00:07:03,930 --> 00:07:07,880 So there we have the separation in between them. 78 00:07:08,010 --> 00:07:15,940 You can also reduce or make larger deception and if you notice that both sides are decreasing while 79 00:07:15,940 --> 00:07:20,710 you're increasing these like if I have this one 3 under the hand we do not have the boxes. 80 00:07:20,820 --> 00:07:27,480 And if this one is like hundredth again we do not have let me have some value like 50. 81 00:07:27,990 --> 00:07:33,540 So if you notice the box are decreasing the disease that that's the thing here that this seismograph 82 00:07:33,540 --> 00:07:37,950 is not increasing only the values are decreasing. 83 00:07:37,950 --> 00:07:44,040 So make sure you are using a value that will not affect the value these values. 84 00:07:44,040 --> 00:07:49,730 And instead of writing this long thing you can just write LW There denoting language. 85 00:07:51,450 --> 00:07:58,620 You can also make these languages colorful just by line color and provide this one like any value read. 86 00:07:58,860 --> 00:08:00,340 This one is right now. 87 00:08:00,630 --> 00:08:04,870 If you write here blue this one is blue now. 88 00:08:05,310 --> 00:08:09,020 If you write black this one is black no. 89 00:08:09,330 --> 00:08:11,300 So you can modify this graph in any way. 90 00:08:12,150 --> 00:08:15,210 After that if you want to change the color of these values. 91 00:08:15,210 --> 00:08:17,960 So here you going just use color like this one. 92 00:08:17,970 --> 00:08:18,830 And cool there. 93 00:08:18,840 --> 00:08:21,250 If you press shift return you will get added. 94 00:08:21,630 --> 00:08:26,530 Also if you use the palette method you will get the edit because these are not thoughts. 95 00:08:26,550 --> 00:08:27,380 These are maps. 96 00:08:27,420 --> 00:08:35,370 So here we use see map denoting color map shifted and you will get the change you can provide any change 97 00:08:35,370 --> 00:08:36,280 you want to. 98 00:08:36,300 --> 00:08:43,200 I could go on this one so this is about the modification you can do in any graph. 99 00:08:43,230 --> 00:08:44,970 Now let me move to the second method. 100 00:08:45,420 --> 00:08:51,550 So to move all these value so that we can have a look at the head there. 101 00:08:52,860 --> 00:08:54,350 So we go. 102 00:08:54,480 --> 00:08:55,730 Just this one more. 103 00:08:55,890 --> 00:08:59,270 Now this method is known as the fluid method. 104 00:08:59,280 --> 00:09:00,180 This is also simple. 105 00:09:00,180 --> 00:09:05,030 You just need to have this flight to and we are going to a good flight to here now. 106 00:09:05,550 --> 00:09:11,150 You can also do with the tips but I'm going to pay for this one because it has only two columns. 107 00:09:11,160 --> 00:09:18,240 Do you have to specify the columns so go for the simple one and you can also try that one device here. 108 00:09:18,240 --> 00:09:19,290 It will take more time. 109 00:09:19,710 --> 00:09:20,730 So you just need to write 110 00:09:23,480 --> 00:09:26,130 first deflate. 111 00:09:26,420 --> 00:09:29,000 Then we have to the it underscored. 112 00:09:29,090 --> 00:09:31,360 Here we have different options here. 113 00:09:31,400 --> 00:09:33,250 We are going to use a table option there. 114 00:09:33,320 --> 00:09:38,600 You can check out either by googling that one then we need to provide an index. 115 00:09:38,600 --> 00:09:41,440 That's what I'm telling you here that you have to provide the columns. 116 00:09:41,570 --> 00:09:46,930 But here we have only 2 so we are not required to focus on that which one to choose. 117 00:09:46,940 --> 00:09:53,520 So here just provide index that is these rows which are mine. 118 00:09:53,660 --> 00:09:59,300 Then we have the columns E M and the values will be passenger. 119 00:09:59,300 --> 00:10:02,610 So here we have the month. 120 00:10:02,750 --> 00:10:05,140 Then we have the columns. 121 00:10:05,150 --> 00:10:09,830 That is CIOL You add minus. 122 00:10:09,860 --> 00:10:11,850 And this one is going to be easier. 123 00:10:13,490 --> 00:10:14,870 Then we have the values 124 00:10:17,440 --> 00:10:25,450 these are like the passengers one thing and they and I need to tell you make sure you are writing these 125 00:10:25,450 --> 00:10:28,420 in quotes so she is done. 126 00:10:28,900 --> 00:10:31,720 Now here we have the data in the metallic form. 127 00:10:32,080 --> 00:10:37,150 And if you bring that one like flight two you will get the data in metric form. 128 00:10:37,190 --> 00:10:38,680 Here we have the e months. 129 00:10:38,740 --> 00:10:42,570 These are years months and the values. 130 00:10:42,730 --> 00:10:46,090 You can also do the same thing with the dips. 131 00:10:46,120 --> 00:10:50,710 You just need to have data like if I have a store this one 132 00:10:53,770 --> 00:11:01,540 then we have dips and then don't be it technical in this one. 133 00:11:01,540 --> 00:11:06,800 Come on C and come on we did just jeans this one like you need to do. 134 00:11:06,800 --> 00:11:08,330 The total bill 135 00:11:11,290 --> 00:11:23,560 and this one like a day we had the sun and then this one day and the values must be a little different. 136 00:11:23,580 --> 00:11:26,750 Let me have the raw data. 137 00:11:27,570 --> 00:11:33,490 This one day and this one totally shifted on that one. 138 00:11:33,510 --> 00:11:35,040 And if you run the dips to 139 00:11:37,820 --> 00:11:44,940 Saudi note at the rate that we have displayed here this is the reason I have not used the tips because 140 00:11:44,940 --> 00:11:47,530 in most of the values there you will get. 141 00:11:48,240 --> 00:11:54,030 And the reason for that is it may be possible that with the values of so many total below in any size 142 00:11:54,260 --> 00:11:59,820 you do not have any particular day value of something like that. 143 00:12:00,310 --> 00:12:01,660 So definitely some tips. 144 00:12:01,660 --> 00:12:05,790 And if you want to use these sorts of flights and if you want to use tips you can also go with that 145 00:12:05,790 --> 00:12:07,420 one. 146 00:12:07,660 --> 00:12:12,760 Now here we have flights to this data and you can just do no S.A. dot. 147 00:12:14,950 --> 00:12:27,010 So the heat map heat map and then this data flights to and flight day we go here we have the same map 148 00:12:27,520 --> 00:12:28,330 as the sun. 149 00:12:28,390 --> 00:12:36,210 If you notice here you can have the same barometers there like elder blues equal to one. 150 00:12:36,280 --> 00:12:42,520 And let me have the color is equal to go. 151 00:12:42,640 --> 00:12:44,760 There we go. 152 00:12:44,790 --> 00:12:51,350 Here we have this one so you can modify the heat map in the way you want to. 153 00:12:51,360 --> 00:12:54,810 So this is about the heat maps how you can change the data. 154 00:12:55,230 --> 00:12:57,260 So make sure you have converted the data. 155 00:12:57,270 --> 00:13:02,550 Otherwise you will get added and make sure you are using proper kind of data so that you will not get 156 00:13:02,550 --> 00:13:07,560 any empty values if you use this one with tips too. 157 00:13:07,590 --> 00:13:11,220 Like here we have tips to use their tips too. 158 00:13:11,220 --> 00:13:11,520 Yes. 159 00:13:11,510 --> 00:13:17,100 That is and shifted on that one you will get something like that. 160 00:13:17,380 --> 00:13:19,170 Because of missing values. 161 00:13:20,020 --> 00:13:27,130 So make sure you are using the proper data and am again focusing on the tips because I need to show 162 00:13:27,130 --> 00:13:31,060 you that what happens when you use improper kind of data. 163 00:13:31,060 --> 00:13:32,940 Now here we have the heat map. 164 00:13:33,070 --> 00:13:38,850 After that we are done with this one move to second one that is cluster map. 165 00:13:39,610 --> 00:13:43,500 So these are the cluster maps and very easy to use. 166 00:13:43,540 --> 00:13:45,640 You just need to first convert the data. 167 00:13:45,680 --> 00:13:49,250 Like here we have the data converted and then used it. 168 00:13:49,360 --> 00:13:58,500 David S.A. don't just cluster a map here instead of heat map and provide the data flight to. 169 00:13:59,560 --> 00:14:03,450 And then we have shifted down we get this one. 170 00:14:04,180 --> 00:14:05,160 This one is a little loud. 171 00:14:05,160 --> 00:14:10,470 Let me change the color that is see map there. 172 00:14:10,600 --> 00:14:12,580 And this one called 173 00:14:15,310 --> 00:14:19,800 so here we have this one now a little view or that how it's working. 174 00:14:19,810 --> 00:14:26,770 Like if you notice on the basic note these thing if you notice this line it's divided into two segments 175 00:14:26,990 --> 00:14:32,810 net is these six and d six and there's a difference in both. 176 00:14:32,950 --> 00:14:36,010 Like these are light and these are darker. 177 00:14:36,010 --> 00:14:39,230 Then we have this line it's again divided into two parts. 178 00:14:39,460 --> 00:14:45,220 This one and this one it can be divided in like something this one instead of this one we have this 179 00:14:45,220 --> 00:14:48,640 light on so that the four lines will be lighter and one is darker. 180 00:14:48,790 --> 00:14:54,280 But in that case the separation is like here we have two here we have four the submission will always 181 00:14:54,280 --> 00:15:00,050 been paid of two and maybe the different one but all will be the same. 182 00:15:00,070 --> 00:15:06,100 So that's why this light blues here this light blues here and separated by a dark one here we have this 183 00:15:06,100 --> 00:15:13,240 one dark and this one a little darker than this one is a little light but they all are darker than this 184 00:15:13,240 --> 00:15:14,170 one. 185 00:15:14,170 --> 00:15:21,100 So I hope you got the idea that what I want to see here that these lines are dividing the values according 186 00:15:21,100 --> 00:15:27,250 to their amplitude or any variation like here we are using the values. 187 00:15:27,430 --> 00:15:36,140 So they are using the amplitude to divide the lines and if you notice here we have 1949 Navy Hymn nineteen 188 00:15:36,140 --> 00:15:38,860 forty nine then followed by 50 51 52. 189 00:15:39,200 --> 00:15:47,810 But here we have 50 men 53 54 51 52 59 60 57 something randomly. 190 00:15:48,110 --> 00:15:54,440 That's because if you notice on the graph we have darker values here in the last that are 1960 here 191 00:15:54,480 --> 00:15:57,880 but we have these darker at this point. 192 00:15:57,980 --> 00:16:03,420 That's why that is because if this one is here then this ambition is not visible properly. 193 00:16:03,830 --> 00:16:05,740 So that's why we have these roots. 194 00:16:05,810 --> 00:16:08,170 They are just used to separate values in different forms. 195 00:16:08,180 --> 00:16:14,340 And this one is also less used because it's a little less efficient because of this thing. 196 00:16:14,390 --> 00:16:17,180 Columns are separated randomly. 197 00:16:17,180 --> 00:16:22,360 Here we have also the bar showing the values amplitude according to the colors. 198 00:16:22,400 --> 00:16:24,370 So this is all about the metric dots. 199 00:16:24,500 --> 00:16:25,600 I hope you got the idea. 200 00:16:25,700 --> 00:16:26,840 And they're very easy to use. 201 00:16:26,840 --> 00:16:33,190 Just you need to convert the data into metric type and then just go with the flow right hate medal plus 202 00:16:33,190 --> 00:16:35,490 to map and provided better images. 203 00:16:35,510 --> 00:16:36,380 So thanks for watching. 204 00:16:36,380 --> 00:16:37,170 We're done with this. 205 00:16:37,490 --> 00:16:38,740 And it's in the next video.