1 00:00:01,530 --> 00:00:06,330 In this scenario we will learn how to eliminate distractions from our. 2 00:00:07,530 --> 00:00:14,040 So our friend John is now working as a marketing head and an online matrimonial site. 3 00:00:14,680 --> 00:00:21,700 And he wants to compare the marriage rate for people with different levels of education. 4 00:00:21,810 --> 00:00:24,060 My levels of education. 5 00:00:24,750 --> 00:00:28,440 I mean that someone has cleared high school level. 6 00:00:28,440 --> 00:00:32,190 Someone has done graduation to one out and post graduation. 7 00:00:32,190 --> 00:00:38,040 So what is the mandate for different levels of education. 8 00:00:38,250 --> 00:00:45,270 And he also wants to look at the trend of all the states changing or each of these levels of education 9 00:00:45,390 --> 00:00:46,700 over a period of five years 10 00:00:51,120 --> 00:00:51,850 so. 11 00:00:51,860 --> 00:01:00,330 Collect the data for the different levels of education and for the last five years and plotted into 12 00:01:00,330 --> 00:01:03,570 a cluster column chart. 13 00:01:04,140 --> 00:01:05,750 This is how his chart looks like 14 00:01:09,050 --> 00:01:17,930 the first set of columns is what all of the sample and the other four is what individual category that 15 00:01:17,930 --> 00:01:18,410 is. 16 00:01:18,410 --> 00:01:22,160 This is a set of people who have done less than high school. 17 00:01:23,210 --> 00:01:26,230 This is a set of people who have played high school. 18 00:01:26,420 --> 00:01:35,360 These people have gone to some college and these people have bachelor's or more qualification and the 19 00:01:35,360 --> 00:01:41,010 height of this column is giving us the marriage date or the five year period. 20 00:01:42,710 --> 00:01:51,460 So although by removing the primary x's and gray lines drawn this time has a wider clutter in the graph. 21 00:01:51,530 --> 00:01:55,180 But is this graph clearly communicating the message. 22 00:01:55,250 --> 00:02:03,170 And later we can suggest something to John to make it more plain and precise. 23 00:02:03,170 --> 00:02:04,340 Take some time to think about it. 24 00:02:08,050 --> 00:02:16,000 One thing John would be willing to communicate from this graph is that the marriage date for this set 25 00:02:16,000 --> 00:02:21,120 of people is a little higher than others. 26 00:02:21,120 --> 00:02:24,170 That is there is some exception here. 27 00:02:24,210 --> 00:02:29,350 Others are below 41 or 42 and this one is going up to sixty one. 28 00:02:30,480 --> 00:02:39,330 So this series is having some exceptional values so he may want to highlight this graph which is not 29 00:02:39,330 --> 00:02:41,950 clear from this. 30 00:02:42,630 --> 00:02:53,290 To do that one option is be emphasizing on these blogs and emphasizing on this one so you can clearly 31 00:02:53,290 --> 00:03:00,220 see that this part of the graph is being emphasized and the focus of audience straight away goes to 32 00:03:00,490 --> 00:03:01,560 this colored part 33 00:03:04,380 --> 00:03:10,550 and since the point we want to make is that it is the largest which is very clear from the height of 34 00:03:10,550 --> 00:03:11,120 these but 35 00:03:14,550 --> 00:03:23,940 so one way of eliminating distraction caused by the other bars in a bar chart is to be emphasized them 36 00:03:24,660 --> 00:03:28,760 and highlighting the one that you want to convey the message. 37 00:03:30,680 --> 00:03:36,990 And if you want to go lonely bars like this you can individually select the bars and change the color 38 00:03:36,990 --> 00:03:41,670 to great to be emphasize them and the ones you want to emphasize on. 39 00:03:41,700 --> 00:03:48,690 You can select those bars and danger to color to some bright color like this orange one or bluer black 40 00:03:52,540 --> 00:03:53,920 now. 41 00:03:54,280 --> 00:04:01,170 One other alternative to representing this graph using a bottom floor is to draw a line. 42 00:04:01,170 --> 00:04:01,410 Jack 43 00:04:04,790 --> 00:04:07,970 let me show you a line chart that can be drawn with the same data 44 00:04:12,390 --> 00:04:16,950 so if you remember there are two things John wanted to do. 45 00:04:16,950 --> 00:04:25,740 One is to compare the marriage date of different categories of people and the second thing is to see 46 00:04:25,740 --> 00:04:30,550 the trend of each of these categories over the years. 47 00:04:32,280 --> 00:04:39,200 So by drawing this line chart we have eliminated a number of distractions. 48 00:04:39,390 --> 00:04:46,590 One of the biggest change that we have made is that we have moved from a bar graph to a line graph. 49 00:04:46,830 --> 00:04:51,690 First of all a line glove typically makes it easier for us to see the trend over time. 50 00:04:53,670 --> 00:05:04,080 Secondly when we had 25 bars in the previous graph the same information is being given by four lengths 51 00:05:05,330 --> 00:05:05,660 to. 52 00:05:05,760 --> 00:05:15,060 Clearly we have reduced a lot of clutter so organizing the data in this line graph allows us to use 53 00:05:15,210 --> 00:05:24,330 a single x axis which can be leveraged across all the categories and highlighting the data points like 54 00:05:24,330 --> 00:05:30,600 this helps us compare the performance of each category against the other. 55 00:05:30,630 --> 00:05:37,260 So the two aims of comparing the performance of each category against the other and seeing the trend 56 00:05:37,260 --> 00:05:46,320 of each individual category is clearly met with this small graph which is clean and clutter free. 57 00:05:46,520 --> 00:05:50,500 Drawing this graph is that easy on the x axis. 58 00:05:50,540 --> 00:05:52,220 The winner take the year's 59 00:05:55,300 --> 00:05:59,960 and we will plot these four data series as line jobs. 60 00:06:00,010 --> 00:06:03,930 We will remove all the gray lines the more divide axis. 61 00:06:04,300 --> 00:06:12,550 I laid the end point and give it data labeled manually or you can add data labeled for all the points 62 00:06:12,700 --> 00:06:17,820 and manually remove the ones that you do not want to show. 63 00:06:18,100 --> 00:06:24,010 Then we will add these ligand names as separate text boxes. 64 00:06:24,010 --> 00:06:29,620 We will change the color of those data series which we want to be emphasized. 65 00:06:29,740 --> 00:06:38,500 We will highlight the data series in a bright color which we want the audience to focus on the text 66 00:06:38,740 --> 00:06:46,220 color of the larger names should also match with the color of the plotted lines. 67 00:06:46,270 --> 00:06:50,050 So this is how we create this chart which is free of any distraction.