1 00:00:00,560 --> 00:00:05,226 A geographic chart is a map where data can be plotted at different locations 2 00:00:05,226 --> 00:00:06,420 around the world. 3 00:00:07,470 --> 00:00:12,445 It represents the data as a map to give a more accurate insight into the locations 4 00:00:12,445 --> 00:00:13,270 of the data. 5 00:00:14,790 --> 00:00:17,517 Google Sheets provides us with many options for 6 00:00:17,517 --> 00:00:20,980 creating visualizations from spreadsheets. 7 00:00:20,980 --> 00:00:23,581 If you're working with geographic data, 8 00:00:23,581 --> 00:00:28,360 you may be interested in creating a geographic chart, or geo chart for short. 9 00:00:29,600 --> 00:00:32,849 Keep in mind that this data chart is interactive and 10 00:00:32,849 --> 00:00:37,539 there are limitations to how much customization options can be tweaked, 11 00:00:37,539 --> 00:00:40,820 compared to the other types of charts. 12 00:00:40,820 --> 00:00:45,112 Let's learn more about Brazil and the other South American countries. 13 00:00:45,112 --> 00:00:49,057 Brazil has the largest population, and earlier we found out 14 00:00:49,057 --> 00:00:53,864 that there's a moderate correlation between population and total GDP. 15 00:00:53,864 --> 00:00:55,900 But what about the per capita GDP? 16 00:00:56,980 --> 00:00:58,838 Brazil has the largest economy, 17 00:00:58,838 --> 00:01:01,830 does that mean it also has the largest per capita GDP? 18 00:01:03,000 --> 00:01:06,060 Looking at our data, the answer is no. 19 00:01:06,060 --> 00:01:10,498 What we can do is we can plot out all of our data points on a map to gain insights 20 00:01:10,498 --> 00:01:13,680 about all the different countries in South America. 21 00:01:15,350 --> 00:01:18,460 For this analysis, we'll make two geo charts. 22 00:01:19,840 --> 00:01:25,756 First, I'll map out the GDP per capita for each country in South America. 23 00:01:25,756 --> 00:01:28,430 I'll select column A for country. 24 00:01:30,590 --> 00:01:35,144 And while holding down command or control, column D for GDP per capita. 25 00:01:37,642 --> 00:01:39,022 When I insert my chart, 26 00:01:39,022 --> 00:01:42,820 I'm going to choose geo chart from the chart type dropdown menu. 27 00:01:52,700 --> 00:01:57,090 Now I have a map of the whole world, let's go over to the Customize tab. 28 00:02:00,173 --> 00:02:03,160 There are only two options for customizing the chart. 29 00:02:04,430 --> 00:02:08,415 And neither of these options allow us to add a title to the chart. 30 00:02:08,415 --> 00:02:12,020 Oh no, you know how much I love doing that! 31 00:02:12,020 --> 00:02:13,600 So, here's how we're gonna work around that. 32 00:02:14,880 --> 00:02:18,761 Let's move the chart to its own sheet and then rename the sheet. 33 00:02:26,110 --> 00:02:32,773 We'll call this Per Capita GDP - South America, 34 00:02:35,531 --> 00:02:37,150 and this is a geo chart. 35 00:02:38,660 --> 00:02:41,050 Now, we can continue customizing the chart. 36 00:02:42,420 --> 00:02:45,367 Right now we have a view of the whole world, but 37 00:02:45,367 --> 00:02:48,250 we only really want to look at South America. 38 00:02:48,250 --> 00:02:49,592 We'll go to edit the chart. 39 00:02:52,240 --> 00:02:55,960 In the Customize tab, open the Geo section. 40 00:02:58,130 --> 00:03:01,661 Now, from the region drop down, select South America. 41 00:03:04,660 --> 00:03:08,152 You can also take a moment here to explore all of the different regions that 42 00:03:08,152 --> 00:03:08,950 are available. 43 00:03:10,510 --> 00:03:14,814 If you have some data that includes location, consider doing an exploratory 44 00:03:14,814 --> 00:03:17,604 data analysis with the geo chart for that region. 45 00:03:20,670 --> 00:03:27,010 So now, our geo chart shows the per capita GDP of all the South American countries. 46 00:03:27,010 --> 00:03:31,886 But there's one more customization that I would suggest. 47 00:03:31,886 --> 00:03:35,954 Let's change the max color from green to blue, 48 00:03:35,954 --> 00:03:42,169 cornflower blue to help out our friends with red-green color blindness. 49 00:03:42,169 --> 00:03:42,847 And for now, 50 00:03:42,847 --> 00:03:47,300 that's all the customization we can get to in this current version of Google Sheets. 51 00:03:48,310 --> 00:03:50,270 Let's close the chart editor and 52 00:03:50,270 --> 00:03:54,190 make some observations based on our geographic visualizations. 53 00:03:57,442 --> 00:04:01,575 The legend at the bottom of this chart shows the values of countries' per 54 00:04:01,575 --> 00:04:02,400 capita GDPs. 55 00:04:03,530 --> 00:04:06,754 If I hover over an individual country, a label will pop up and 56 00:04:06,754 --> 00:04:10,123 there will be an indicator alongside the legend for that area. 57 00:04:13,634 --> 00:04:17,422 Let's make another geo chart, this time for total GDP. 58 00:04:20,952 --> 00:04:26,162 I'll click back to the South America data set from the bottom navigation bar and 59 00:04:26,162 --> 00:04:27,650 deselect my columns. 60 00:04:29,000 --> 00:04:32,256 And this time I'll select column A and 61 00:04:32,256 --> 00:04:36,129 column C while holding down Ctrl or Command. 62 00:04:36,129 --> 00:04:43,571 Insert Chart. In the chart editor, Chart Type. Geo Chart. 63 00:04:49,041 --> 00:04:52,385 Now, let's move our new chart to its own sheet and rename it 64 00:05:02,940 --> 00:05:11,300 Total GDP - South America Geo Chart. Now, let's customize the map. 65 00:05:12,680 --> 00:05:19,863 Change the region to South America by clicking edit chart, 66 00:05:19,863 --> 00:05:25,340 Customize, Geo, Region, South America. 67 00:05:25,340 --> 00:05:29,782 And remember, for our friends with red- green color blindness we'll change the max 68 00:05:29,782 --> 00:05:31,572 green color to cornflower blue. 69 00:05:35,070 --> 00:05:39,878 Awesome, so now we have two different geo charts. 70 00:05:39,878 --> 00:05:44,972 And looking between these two maps, I can see a story. 71 00:05:47,663 --> 00:05:50,505 Even though Brazil has the largest economy, 72 00:05:50,505 --> 00:05:54,180 which correlates with it having the largest population. 73 00:05:55,180 --> 00:05:59,837 When we look at the per capita economy, the distribution of wealth is 74 00:05:59,837 --> 00:06:04,030 actually slightly below the median for all of South America. 75 00:06:04,030 --> 00:06:09,033 The three countries in the blue for per capita 76 00:06:09,033 --> 00:06:15,050 GDP Are Chile, Argentina, and Uruguay. 77 00:06:17,790 --> 00:06:22,814 Remember that there are some limitations to the customizations of these geo charts, 78 00:06:22,814 --> 00:06:25,810 such as lack of titles and labels. 79 00:06:25,810 --> 00:06:29,983 Additionally, a chart shouldn't have to rely on colors alone in order to tell 80 00:06:29,983 --> 00:06:30,500 a story. 81 00:06:31,840 --> 00:06:36,120 For instance, what if these map charts were printed out? 82 00:06:36,120 --> 00:06:40,383 Since there are no titles or static labels, it would be hard to understand, 83 00:06:40,383 --> 00:06:44,930 especially since this geo chart is meant to be interactively viewed on a screen. 84 00:06:46,120 --> 00:06:49,850 And if they're printed out in black and white, as many things are, 85 00:06:49,850 --> 00:06:52,480 it would be even more difficult to understand. 86 00:06:53,750 --> 00:06:57,454 And notice how since these geo charts are on their own sheets, there is not 87 00:06:57,454 --> 00:07:01,158 an option to add alternative text in the same way that we have been doing for 88 00:07:01,158 --> 00:07:01,960 other charts. 89 00:07:02,980 --> 00:07:06,727 We can work around that by adding a new sheet dedicated as describing our 90 00:07:06,727 --> 00:07:07,730 visualizations. 91 00:07:09,440 --> 00:07:13,950 Create a new worksheet and name it geo chart alternative text. 92 00:07:13,950 --> 00:07:16,545 In the bottom left corner, click on the plus sign. 93 00:07:18,694 --> 00:07:22,476 And I'll rename this from Sheet5 to 94 00:07:22,476 --> 00:07:31,121 Geo Chart Alternative Text. In row 1, 95 00:07:31,121 --> 00:07:32,831 we'll create the headers. 96 00:07:32,831 --> 00:07:35,516 First, Chart Title. 97 00:07:37,837 --> 00:07:39,588 And second, Description. 98 00:07:43,502 --> 00:07:46,750 This worksheet here will describe our two geo charts. 99 00:07:47,790 --> 00:07:50,493 Let's copy over the Geo Chart titles. 100 00:07:52,270 --> 00:07:59,312 First, I'll copy the Per Capita GDP by clicking the option to Rename and copying. 101 00:08:01,334 --> 00:08:06,935 I'll go back to my new worksheet and paste in the title. 102 00:08:06,935 --> 00:08:10,060 And then I'll do the same for total GDP. 103 00:08:25,781 --> 00:08:26,360 Nice. 104 00:08:28,210 --> 00:08:33,462 I can resize column A by double-clicking on the blue line between A and B. 105 00:08:36,981 --> 00:08:42,811 For our descriptions, we can say that the per 106 00:08:42,811 --> 00:08:47,869 capita GDP In Brazil is 107 00:08:47,869 --> 00:08:54,413 along the median of the South American countries. 108 00:08:57,996 --> 00:09:03,931 Chile, Argentina, And 109 00:09:03,931 --> 00:09:09,347 Uruguay have the highest per capita GDP. 110 00:09:16,071 --> 00:09:22,209 And for total GDP we can say that Brazil has the largest 111 00:09:22,209 --> 00:09:27,050 economy In South America, 112 00:09:29,020 --> 00:09:34,981 which correlates with its population also being the largest. 113 00:09:42,750 --> 00:09:47,683 Now, this alternative text worksheet will address the shortcomings 114 00:09:47,683 --> 00:09:52,626 of this graph type that I've outlined earlier as far as readability. 115 00:09:52,626 --> 00:09:54,842 Nice. Geo charts can be useful in 116 00:09:54,842 --> 00:09:59,891 an exploratory data analysis to quickly gain insight into location 117 00:09:59,891 --> 00:10:04,695 based data if your regions are included in the customize geo tab. 118 00:10:04,695 --> 00:10:08,622 The included regions are a strong limitation to be aware of. 119 00:10:08,622 --> 00:10:12,145 If you try to plot the other datasets in this workshop, 120 00:10:12,145 --> 00:10:17,127 you'll find that these small regions, the Caribbean and Central America, 121 00:10:17,127 --> 00:10:19,750 are not easy to see on any region option. 122 00:10:20,880 --> 00:10:23,480 Hopefully this will change in the future. 123 00:10:23,480 --> 00:10:26,547 But if your data is compatible with what is available, 124 00:10:26,547 --> 00:10:28,220 I encourage you to try it out. 125 00:10:29,650 --> 00:10:31,790 We're at the end of our workshop. 126 00:10:31,790 --> 00:10:36,790 Congratulations, you've completed data visualization with Google Sheets. 127 00:10:36,790 --> 00:10:37,846 I hope you liked it and 128 00:10:37,846 --> 00:10:42,050 find it useful for expanding your repertoire of data storytelling. 129 00:10:42,050 --> 00:10:43,418 If you have any questions, 130 00:10:43,418 --> 00:10:46,280 feel free to ask them in the Treehouse community forums. 131 00:10:47,320 --> 00:10:49,600 I'm AJ and I'll catch you next time.