Into different types of dashboards, and you will leave with that understanding. By the end of the course, you should be able to create effective dashboards on your own, and you will also walk away with class files that help you get a head start. In each module, we'll work with a specific data set and build visualizations to be used on our dashboards. In the fifth module, we will switch our focus to a world population data set. We'll learn about ranking, correlation, stories, pivoting, and validating data joins, while building our vizs for our dashboards..
Module six will see us working with a USA College's data set. We'll learn how to use the starts with function, before moving on to using calculated values as filters. We'll format layers and learn about values and headers aliases. Looking to support our channel and get a great deal? Become a member today to unlock ad free videos. That's right, your favorite courses without a single ad. Interested in a specific video? Purchase one of our ad free courses individually. Looking for even more? Gain access to exams, certificates, and exclusive content at learnitanytime..
Com. More information can be found in the video description below. In this module, we'll be working with the World Population Dataset, and we'll start by learning about ranking. Then correlation, before switching our focus to stories, pivoting, and validating data joins. Since our first lesson is about ranking in Tableau, we're going to go over some information that will be useful for you to have in the background before we begin..
You'll be able to see all of this once we build the visualization. So Tableau has five rank function. So each of them does something slightly different. The base one rank gives you the ranking within your ordered partition. Ties are assigned the same rank with the next rankings skipped. So let's say we have two values of 32 and they have a rank of 3. The next value 33 will have a rank of 5 as the rank of three is repeated twice..
Is the value below which a percentage of date data fails, rank can be repeated. And I need to update this slide. It should say data instead of date. And that will be done before you have it in your video description. All of the rank functions can be used with an optional argument of ASC for ascending. Or D E S C for descending. Now, our world population, we have four different files..
Two of them are comma separated values, and two of them are Excel worksheets. We're gonna use all four files, but initially, we're gonna start with the Excel worksheet files. So we have world population and population by age group. So in Tableau, I'm going to use Excel this time and navigate to my world population folder. And so it shows the two Excel workbook files, and I'm going to.
Double click world population. And let's go up next to connections and add, and we're going to do Excel again, and we're going to grab the population by age group and bring that in. Let's drag population. The population by age group sheet to the logical layer, and you see that it automatically detected a relationship based on the country field..
Let's double click on that world population tile so we get to the physical layer and we're going to drag population by age group there. As well, and it automatically creates the inner join based on the country field. So now we have a joined data set. And so if you're looking at the bottom, you're seeing all of your fields from world population. And then as you go to your right, you'll see the fields from. Population by age group. And because it's the common field is country..
What we're going to do is we're going to hide the population by age group, country field, so we don't have it duplicating. And so you see that population by age group, right? It has the total population by age group. It has the 65 plus 25 to 64 years. 15 to 24, 5 to 14, and 0 to 4. World population data includes a rank, um, CCCA3 field is like the abbreviation, abbreviations of the country names. We have the country, the capital, the continent, 2022 population, 2021, excuse.
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1970, and then we have the area, the density, the growth weight, growth rate, and the world population percent. So that's what we're working with here in terms of data. Let's go ahead and save our file. I'm going to name it world population. We're going to go to Sheet 1, and we're going to drag. So let's do this, because we've seen this already..Even though we hit it on the data source screen, let's hide the country field under population by age group, so we don't get confused as to which one we want to use. And let's drag our country field from world population to rows. And since we're not going to use the built in rank measure at all, I'm going to go ahead and hide it. And so we're going to create. several calculated fields for using the rank functions that.
We reviewed on the slides. So I'm going to go and do my drop down and create a calculated field. And this one I'm going to name rank asc, period. I'm going to click. Where I can put in the function, and I'm going to grab the rank function, and then I'm going to grab the sum function, and I want the sum of the world populated population percentage..
And once you tab that in, notice that it has you flashing in between the two closing parentheses. And so that's where you use the rank optional arguments of ASC. Or, D E S C, and we're gonna do a single quote, A S C, close the single quote, and then we're gonna press, so notice it says the calculation contains errors and there's like a wavy red underline underneath that first quote before A S C..
That's because I forgot to have you type a comma. before that. So we have to separate the arguments of the function with a comma. So it's going to give us a, an ascending rank of the sum of the world population percentage. Go ahead and click okay. And we're not going to drag it into the view just yet. What we want to do is go underneath our measure names and.
You'll see your rank dash ASC. You're going to right click on it. And you're going to copy and then you're just going to right, right click anywhere in your field list. So I want to right click anywhere over there and choose paste. So we're going to create all of the calculated fields we need by copying and pasting until. We're done, and then we'll add them to the view. So with that copy of Rank AFC, I'm gonna right click on it and edit it..
And I'm gonna click after Rank. In the formula there and I'm going to type in underscore and you'll immediately see the other rank functions show up on the list. So what we're going to do here is we're going to choose, we're going to just click on rank modified and we're going to change the name at the top. So at. At the top, click after the word rank before the hyphen and type modified. So it should say rank modified dash ASC and we can get rid of the one indicating.
The copy at the end of the name. Click okay. At this point, you can just right click in your field list and paste again. And then you have your rank, you know, your pasted rank ascending one. We're going to right click and edit it. Let's change the name of this one first. So, after rank at the top, before the hyphen, we're gonna do dense, space, get rid of the one at the end. And we're gonna click after rank in the formula, do the underscore, and click on rank dense. And okay..
And now we're gonna right click and paste again. We're gonna edit our pasted one. And this one. So, we did. Modified, we did dense. We're going to underscore, and we're going to start, um, oops, I'm doing it in the name. So this one, I'm sorry, in the name we're going to make it rank unique, and get rid of the one..
And then do your underscore in the function, and grab, uh, Rank unique and click OK.
So right now we have rank, rank dense, rank modified, rank unique, all in ascending order. We're going to paste again. And for this one, when we edit it, we're going to change the name first to rank D E S C. In that second argument, A S C in the formula, we're going to change.That to D E S C, and I forgot to get rid of the one in the name. Click OK. Now, so we don't have to keep changing it from A S C to D E S C, we're going to right click and copy rank D E S C, and then paste. is going to be, we're going to change the name first, rank modified dash D E S C, and then do your thing with the underscore in the formula and grab modified..
So I'm going to have you do, um, two more copies. You're going to make one. So we're doing modified together. You're going to make one dense and then one unique for descending. So now you should have eight different rank measures, four for ascending, four for descending. I forgot to do the percentile one, so I'm going to recopy rank ascending, paste it,.
And we need to edit that so that it's It's rank percentile with the appropriate name and do it for descending as well. So now we should have our 10 calculated fields under measure names. Go ahead and save your file. So now that we have that done, let's drag our measure names field to the filter shelf. We're going to select none, scroll to the bottom, or toward the bottom. And we're going to select all of the rank calculated fields that we just created..
And we're also going to select the world population percentage measure. So all of our ranks and world population percentage. And we're going to click OK. We don't have to show that filter. Now we're going to drag Measure Names to Columns and we're going to drag Measure Values to Rows after Country. And then go to your Show Me and change it to a Text Table..
And so let's first start by widening the columns. I'm putting my mouse between any two columns and dragging a little bit to the right. And I want to make sure I see this world population percentage, but I don't want it to say the word percentage, I want it to be the percent sign. So I'm going to right click on that heading, and I'm going to choose edit alias, double click percentage, and type the percent symbol, and click OK..
And now I'm going to widen it, because that would be the widest column heading, I believe. World population population. Percentage, I'm gonna collapse my show me, and actually I'm gonna edit the alias again, and I'm gonna abbreviate population to just POP with a period, that way I don't have to have it as wide. I think this one, yeah, the descending, the rank percentile descending.
Would be the column that we need to make the widest so we can see. And then we want to organize this a little bit. So under the marks card in the measure values, we want rank ascending, and then we're going to move it. We're going to move rank dense ascending underneath it. So we have all of our sendings together and then we want our rank modified ascending. and rank percentile ascending, and then rank descending,.
Rank density sending, modified descending, percentile descending. Oops, I forgot my unique ascending. I'm going to put unique under modified. So I have them organized, so I have Rank Ascending, then Dense, Modified, Unique, and Percentile, and then Descendings, Dense, Modified, Unique, Percentile, and then the World Population Percentage..
So you'll notice in the list of measure values, under your marks card, all of them have like a triangle to the right of them. That's because Rank, and all of the Rank, Functions, basically are what are known as table calculations. And so they have that triangular icon. For the rank ascending one, we're going to do the drop down arrow. Let's go to edit table calculation. So it's actually going across the table. You can stay in that box..
Just watch me for a moment. So here, if I widen the columns, it's saying along. I go into the calculated field and edit it. At the top it says results are computed along table across, right? And I could, we could have changed it from in here by clicking on default table calculation. So instead of opening each function, we're going to use the dropdown.
Next to the measure value and we're going to hover over compute using. And we're going to choose country. And we're going to do that for all of them in the list. Just hover over compute using country. It's a lot more efficient in opening. each calculated field to make that edit. And when you do all of that, your headings should now all say along country, except for the world population percentage at the end..
And so we don't need it to say all of that. So we're going to edit all of these aliases. So I'm going to right click on a rank ASC along country, edit the alias. And just get rid of the words along country and do that for all the rest of your headers. And now I'm going to right click on any header there and rotate the label. And then I can decrease my column width because now they.
Don't have to be that wide. So, I can see everything pretty much. I'm going to do it down just a little bit more. So I don't have to scroll across to view any of the headings anymore. So now we're going to change the orders of our ranking in the view, so that we can see them and compare them more clearly. We're going to click on the rank. ASC heading and you'll see the sort country ascending by measure values icon. And there's also a sort country descending by measure values icon. We're going to click on the sort country ascending by measure values icon..
When we do that, we'll see that our data updated and now it's sorted by country. Right? According to their ranks. So, this first one, the, the basic rank function, numbers are skipped by the number of repeated values and it has ties. So you're seeing a bunch of ones, and then you'll get to 57. Right? So, and then as you scroll down, you have a bunch of 57s, then it goes to 75. And then 84, so you're seeing the repeats and you're seeing the skipped.
Rankings because again it's, the numbers are skipped by the number of repeated values and you will have ties. When we look at our rank dense ASC, you'll see that we have our ones there, right? And as we scroll down, so there are no gaps. It goes from 1s to 2s to 3s to 4s, so we don't have that gap in numbers when you're using the rankDense function. You can also see that rankModified, the gaps happen, right, before The repeated rank. So it doesn't go from one to 57..
It starts with 56 and then you'll see the next gap 74s, so on and so forth. So for modified, the gap happens before the repeated rank. And then we look at unique. There are no gaps and no ties. Just sequential ranking numbers here. And then the percentile, again, the rank can be repeated, but it's showing the percentile of values, showing the value below which.
A percentage of the data falls. So we have all of our rank functions ascending and in descending order. in the same table here. Let's go ahead and save and we're going to name this sheet country ranking by world population and I'm going to use the percent sign and I'm going to spell ranking correctly because that would probably be helpful. Now we're going to start formatting the values in our table..
So I'm going to just right click in the table and go to Format to bring up that pane. And then I'm going to go to the Fields dropdown. And let's start with the sum of the world population percentage. And we want to format that as a percentage with no decimal places. And then we're going to go back to the fields drop down. And so for all of our rankings, we have to do them field by field, for all of our rankings, we want them to just be standard format, standard number format..
So I'm gonna just go through the list from top to bottom. So number standard. And you can go ahead and complete that process on your own. I'm gonna just have you pause the video and do that. The percentile ranks need to be in a percentage with zero decimal places. So when you're done, your values in your table should look like mine. Um, I have to do, let me go to rank ascending again, forgot to hit that one..
So you can see it in the table, it makes it easy to see what you may have forgotten. It also makes it easy when you go to your fields list that it will have selected the last one that you modified. And in the format pane, let's go to our paint bucket for shading. We're going to give our worksheet the dark gray color. And, ooh, I do not like that banding. Um, we're going to go down to row banding and choose none for the pane and the header..
And let's go to our font icon at the top of the format. pane, and let's change the default worksheet font to white bold. And then we're gonna edit our title and select everything, and make that bold and white font as well. So there you have it, uh, the country ranking by world population percent, and we used every rank function, both ascending and descending, that we have..
Now we're going to get into our second lesson, which is about correlation. Correlation analysis compares two or more quantitative variables to see if the values in one vary systematically with values in another. So for some examples, do lemonade sales increase as the temperature rises? Has nothing to do with our data set. As men increase in height, does their weight also increase? Again, has nothing to do with our data set. The one we're going to be using is density impacted as growth rate increases..
So that will be the example we'll use for correlation. You'll be given an equation that has an R squared value and a P value, similar to when we did trend lines. The closer R squared is to one, the stronger the correlation between your two metrics. You want a p value that is less than 0. 05. If it's higher than that, that means that the tableau correlation between the variables isn't statistically significant. A very low p value means that you can have greater trust in the tableau.
Correlation, and that the results you're seeing did not occur randomly. In other words, it really is a good correlation and you can trust it. The equation enables you to predict how your x variable will change your y variable. An r squared value of 0. 127, for example, means that 12. 7 percent of the changes in, in our case, density can be explained by growth rate..
Therefore, 87. 3 percent of changes in density Cannot be explained by growth rate, so they're not really correlated to each other. I'm going to go ahead and save my file and bring up a new sheet and let's go ahead and name that sheet impact of growth rate on density by country. So we are going to drag The density field to columns and the growth rate to rows. And so with correlation, the question is, does our X variable change our Y variable?.
So in order for us to answer the question on the slide, is density impacted as growth rate increases? We're really saying, does the X variable change the Y variable? So we need growth rate to be our X variable. So I'm going to do control W to swap the columns and rows. So that will be the case when we do our correlation. Now I'm going to just drag and drop country into the view, and I'm.
Going to put continent in color. On the marks card, so let's switch this to entire view and the way that we do a correlation is the same way we do a trend line. Um, we can do it from the analytics tab like we did it earlier, or you can use the analysis menu, hover over trend lines and choose show trend lines. So you're seeing all of these trend lines that are showing. And if you hover over any one of them, what you're looking for here is. The closer R squared is to the number one, the stronger the correlation..
If the p value is less than 0. 05, you can have greater trust that the results did not occur randomly. So this is looking like there is no correlation here. If I'm keeping an eye on the R squared, number, right? And for each of those lines, it's kind of the same thing. The P value is pretty good, but the R squared value is lower. So we can see that really the growth rate has no impact in terms of correlation on the density. Go ahead and save your file and bring up a new sheet..
