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These are the user uploaded subtitles that are being translated: 1 00:00:06,020 --> 00:00:11,270 One of the powerful features of Excel Pivot tables is that you can group data. 2 00:00:11,480 --> 00:00:13,730 So let's take a look at a quick example. 3 00:00:14,600 --> 00:00:19,490 Now I'm going to start out here just by removing a couple of these rows that we've added, so I'm going 4 00:00:19,490 --> 00:00:22,250 to just remove a count of products. 5 00:00:22,250 --> 00:00:27,980 Let's get rid of that and also average gross sales just so we're left with total gross sales. 6 00:00:28,340 --> 00:00:34,360 Now it might be that instead of having the year filter at the top here, maybe I want to display the 7 00:00:34,360 --> 00:00:36,170 year information in the columns. 8 00:00:36,710 --> 00:00:43,280 So I'm going to grab the year and drag it across two columns so I can now see that information. 9 00:00:43,970 --> 00:00:48,650 So I have my gross sales for 2018 and also for 2019. 10 00:00:49,490 --> 00:00:54,860 Now, when you're working with things like years, this is all based on whatever you have in your pivot 11 00:00:54,890 --> 00:00:55,370 table. 12 00:00:56,060 --> 00:01:02,570 So if I take a look at my data, you can see over here, I've got the date in Column K and then I have 13 00:01:02,570 --> 00:01:06,770 month name and year now because I'm using the year field. 14 00:01:07,070 --> 00:01:10,010 Excel is just using the data that it finds in here. 15 00:01:10,010 --> 00:01:12,380 So 2019 or 2018. 16 00:01:13,040 --> 00:01:17,510 But if I use the date field instead, let me show you what happens. 17 00:01:17,630 --> 00:01:19,190 So let's go back to sheet two. 18 00:01:19,820 --> 00:01:27,050 I'm going to remove the year field, and this time we're going to use the date field instead. 19 00:01:27,860 --> 00:01:32,390 So if I drag that down, two columns notice what automatically happens. 20 00:01:32,390 --> 00:01:35,480 It breaks it down into years and quarters. 21 00:01:36,260 --> 00:01:42,980 Because Excel is recognized that the date that I have in this column is made up of a day, a month and 22 00:01:42,980 --> 00:01:43,380 a year. 23 00:01:43,820 --> 00:01:49,370 And because they're all grouped together under the date field, when you drag that date down, it's 24 00:01:49,370 --> 00:01:51,410 going to automatically split them up for you. 25 00:01:51,710 --> 00:01:54,020 Now notice what that's done to my pivot table. 26 00:01:54,500 --> 00:01:58,100 I now have little plus signs next to 2018 and 2019. 27 00:01:58,100 --> 00:02:00,620 If I click the plus is going to show me the quarters. 28 00:02:00,890 --> 00:02:03,800 If I click the Plus again is going to show me the different months. 29 00:02:04,520 --> 00:02:07,850 Now, the way that this is currently organized is not very easy to read. 30 00:02:08,300 --> 00:02:09,800 So let's backtrack a little bit. 31 00:02:09,800 --> 00:02:13,100 Let's collapses back up again and look at this in a different way. 32 00:02:13,400 --> 00:02:20,330 Now, if you're wondering where the grouping is coming from, if I select the 2018 label, go up to 33 00:02:20,330 --> 00:02:28,580 Pivot Table, Analyze Notice that we have a group section just here, and if I go to group field, it's 34 00:02:28,580 --> 00:02:31,100 showing me how the date field is grouped. 35 00:02:31,670 --> 00:02:34,880 So it's going to include months, quarters and the year. 36 00:02:35,720 --> 00:02:42,320 It's also recognizing the start date, so it's found the first date in my data and also the last date 37 00:02:42,320 --> 00:02:43,130 in my data. 38 00:02:43,940 --> 00:02:49,430 So if I decide that I actually don't want to have months, quarters and years, I'm just interested 39 00:02:49,430 --> 00:02:52,730 in, yeah, I could choose to remove both of these. 40 00:02:53,270 --> 00:02:53,630 Click on. 41 00:02:53,630 --> 00:02:54,260 Okay. 42 00:02:54,500 --> 00:03:00,590 And now I don't have those little plus signs, and I can't drill down to see the day in the month information. 43 00:03:01,250 --> 00:03:04,780 So just be aware of that because I know it catches some people off guard. 44 00:03:04,790 --> 00:03:09,770 They think they have one field, they drag it down to the columns and it suddenly splits up into three 45 00:03:09,770 --> 00:03:10,730 separate fields. 46 00:03:11,390 --> 00:03:14,600 That is how Excel handles things like dates. 47 00:03:15,090 --> 00:03:18,200 Now, similarly, we can do the reverse of that as well. 48 00:03:18,620 --> 00:03:22,040 We can create our own groups in our pivot table data. 49 00:03:22,310 --> 00:03:27,590 So for this example, I'm actually going to switch the country and the product around. 50 00:03:27,590 --> 00:03:30,740 So let's drag country above product. 51 00:03:31,160 --> 00:03:35,090 Now, maybe these products are part of different ranges. 52 00:03:35,660 --> 00:03:44,450 So maybe Burlington and Kensington are the premium range luxe and Mandarin are the luxury range, and 53 00:03:44,450 --> 00:03:47,450 Royal Oak and Vermont are the standard range. 54 00:03:48,020 --> 00:03:54,380 Now I can reflect that in my pivot table, even though I don't have that information in my data source 55 00:03:54,710 --> 00:03:56,990 and we can use grouping to help us do that. 56 00:03:57,860 --> 00:04:04,430 So what I'm going to do is select Burlington and Kensington up to Pivot Table Analyze, and then I can 57 00:04:04,430 --> 00:04:06,200 say group selection. 58 00:04:07,310 --> 00:04:12,800 It gives me a name of Group one if you want to edit this group name, so it's a bit more meaningful, 59 00:04:12,800 --> 00:04:17,390 you need to click on the field and press the f two key on your keyboard. 60 00:04:17,930 --> 00:04:21,140 That's then going to allow you to go in and change the group name. 61 00:04:22,160 --> 00:04:32,300 So this is the premium range and enter now I'm going to select the luxury range, and the Mandarin range 62 00:04:32,630 --> 00:04:33,920 lets group selection. 63 00:04:34,100 --> 00:04:42,650 I now have another Group F two to edit and this is the luxury range. 64 00:04:43,550 --> 00:04:46,820 And then my final range is Royal Oak and Vermont. 65 00:04:47,030 --> 00:04:48,590 Let's group this selection. 66 00:04:49,100 --> 00:04:51,020 Click on the cell F2. 67 00:04:51,440 --> 00:04:54,770 This is going to be the standard range. 68 00:04:55,790 --> 00:05:02,750 So very quickly I've managed to divide up and add a bit of structure into my data and also include grouping 69 00:05:02,750 --> 00:05:05,260 that wasn't present in the original source data. 70 00:05:06,350 --> 00:05:10,790 It might also be at this point that you look at your data the way it's being displayed and you might 71 00:05:10,790 --> 00:05:15,650 think to yourself, actually, you know, while I want these subtitles out of the way at the top of 72 00:05:15,650 --> 00:05:19,770 the group and I think I'm actually going to do that, let's go back to subtitles. 73 00:05:19,790 --> 00:05:21,350 Show at top of group. 74 00:05:22,460 --> 00:05:24,200 So that makes it a little bit clearer. 75 00:05:24,740 --> 00:05:32,000 So the takeaways from this lesson are to just be aware of that automatic grouping and modify accordingly. 76 00:05:32,300 --> 00:05:38,240 And also be aware of the fact that you can create your own groups to separate up or add structure to 77 00:05:38,240 --> 00:05:38,870 your data. 7754

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