Tableau 10: Practical and Concise Part 3 | Junaid Athar | Skillshare

Tableau 10: Practical and Concise Part 3

Junaid Athar

Play Speed
  • 0.5x
  • 1x (Normal)
  • 1.25x
  • 1.5x
  • 2x
13 Lessons (39m)
    • 1. Bar Chart

    • 2. Bar in Bar Chart Solution

    • 3. Highlight Single Category

    • 4. Visualizing Date and Time

    • 5. Find Patterns Over Time

    • 6. Gantt Chart

    • 7. Treemap

    • 8. Pie Charts

    • 9. Circle Charts

    • 10. Box And Whisker

    • 11. Scatter

    • 12. Dual Axix

    • 13. Combination Chart


About This Class

So, you've heard a lot about Tableau 10, but you don't know how to get started?  This Udemy course is exactly what you need! This course will teach you all the fundamentals you need. Trust me, you won't need any other course to reach the intermediate/advanced level after this course.

In this course, you'll learn how to make the data work for you so that you can aggregate, analyze and visualize your data. 

The course's curriculum goes as such: 

  • You'll get started with line and bar charts
  • You'll learn to use extracts, joins and blends 
  • You'll learn to advanced techniques such as Gantt charts, Treemaps, circle charts..
  • You'll master row and aggregate calculations 
  • You'll learn table calculations
  • You'll learn to format your data for visual impact
  • You'll know how to tell a story with Tableau

The course is aimed to be as complete as possible. It will include a lot of practice so that nothing stays theoretical, and the quality is in full HD, so that you can see everything on-screen.

NOTICE: I'll keep adding more and more content to the course to make it the best Tableau course on Udemy.

So, what are you waiting for?! Click on BUY NOW and LET'S GET STARTED!


1. Bar Chart: in this part, we will get into more advanced data analysis and advanced visuals. We'll start by making our bar chart a little bit fans here. So I opened up the part three workbook, and from here we can use, um, barge Hurst toe compare values across different dimensions. Some questions you will ask yourself is, How much profit do that generate in each department? How Maney views did each of my websites get? How many cases did each doctor in the hospital treat last year? At age Case, you're looking to make a comparison among departments, websites or doctors in terms of hot some quantitative measure. We'll start by using the superstore data set and looking at the sales by category. So that's blood sales. Let's pull in category analysts, but then the rose and we could make this a bar chart. So here is a simple bar chart, and if we want ideally, we want in descending order so we can see the most sales at the top. To do that, there are a couple of ways to do that. You can click on the sword button in the Y axis, and that automatically sorted. That's one way to do it. You can also sort it by, um, coming to your category. Right, Clicking and choosing to sort. And instead of sorting it by the name, you can set it to descending based on a field. We want to use the sales some descending, order it okay, and we come back to this view, um, you can remove your filter by I mean, you can remove this sort based based on the sales by simply sorting by category. And now you're back to your default sorting options. Let's take an example of looking at profit by, so it's out sales. Let's replace that with profit, and we want to look at instead by category. Let's look at it by region so we can create a bullet chart. So let's pull in region in the Rose. And now we want to compare this to our profit targets so we can come to our profit targets . Data source. What? You could make just a simple flat file click on profit targets. Do a show me and click on bullet charts. This automatically creates a bullet chart that shows your profit target versus your actuals . So this little bit backwards, we prefer tohave the lines be the target and the bars be the actual so we can come up here , right click on your profit target and swap reference line fields. So now this gives the view that you're looking for. That's the basic example of how to set up a bullet chart in the next video will put together a bar and bar chart. So take some time and see if you can manipulate the data in a couple different ways to figure out how to get a barn bar chart. I'm a walk through the example of results that to make it look like this in the next video . 2. Bar in Bar Chart Solution: we left off with this bullet chart, and now we want to turn this into a bar and bar chart. To do that. It's really it takes a few steps, but it's pretty simple, A straightforward. You can take your profit targets and drag and drop them into your Y axis. This creates a replacing the columns and measure values and a filter for the measure names . You can see the measure names and rose to, so any time you want to or more measures to share the same space within a view, you can use a measure. Names and measure values. Measure names is a special dimension field. That tableau adds toe every data source. It is a placeholder for the names of measures you can place in it in the view anywhere you would place any other dimension. Measure values is a special measure. Feel that tableau ads every day to source. It is a placeholder for the values of other dimensions. You can use it in any way you would use any other measure. When these special fields are in use, you will see a new measure value fields in the shelf workspace and those this shelf contains all the measures right here. There are reference by the measure, names and measure values You can add and remove measures to and from these shelves, as well as rearranged order of any measure on the shelf. You can drag and drop the measure name and measure value field directly from the data window into the view. Many times, it is easy to remember that if you want to or more measures to share the same space, simply drag and drop the second onto the same space that is occupied by the first, similar to how we pull the profit target and put it on the Y axis if you want to or more measures to occupy the pain dropped the second onto the pain. It's that simple. So now there were reviewed the measure values and measure names. Let's continue with our bar and bar chart. Example. Take the measure names and move it onto the color field, so this creates a stacked bar chart with profit targets and profit actual profits. This this is not the view we want. We want them toe overlap. So now we can copy the measure Name, field, Reliance. Are we all re copy the measure. Names field onto the color, and now we want to copy them to the shot size two. So hold down control and drag it to the size. So now you see we have the profit targets and profit margins. Still, they're stacked, and we want them to overlapped so we can remove the stacking option by going to analysis stack marks. Turn that off and now you've created a bar and bar chart. You can make it larger to give a better view, and it's that simple, so you can now save this chart and use it in your dashboard. 3. Highlight Single Category: In this video, we will cover how to highlight a single column in a bar chart. So let's remove. Let's clear the bar chart. You don't need region. We don't need measure names. We're just going to start with a blank canvas. Let's pull in category and sales create a bar chart. We don't want it stacked, uh, turning stacked off. So that gives us. Oh, that's why the category isn't in the column. So now we have the bar chart. We're looking for slits sorted by sales descending. Let's assume we want to highlight the tables column we want to make. We wanna make this bar a different color. We can do that by creating a calculated dimension. So we go to analysis shoes, created, calculated field and, um, tables. Highlight will get into more depth about calculated dimensions later in this course, but for now, we're just gonna create a simple category equals tables. So this is just a true false statement. You can see we have a new calculated dimension called table highlights. So this essentially says, if it's tables make it true, it's not table. Make it fall, so you can see we have 1.6 million in sales. So if we replace category with table category, we'll see the 1.61 million sales and everything else is false. So that's what we're looking for, what we want to highlight it. So weaken. Drag the tables highlight to the color marks, and you can see now because it's true. It's a different color. The rest are false. That's where they remain the same color. So that's an example of how to highlight a single category or similar bar within your chart . This is very useful when you're making executive presentations, because different executives have different goals and different targets so they'll want their individual bar or their individual category highlighted in the next section will start looking at dates and times and how to build visuals onto goes 4. Visualizing Date and Time: So we reviewed how to highlight a single category in a bar chart, and now we will look into using the date parameters and functionality to do Time series analysis. So we're gonna look at sales by year. We can pull in the order date and replace the category. We want to remove this color because this is the tables category right here. So tableau automatically creates a line chart for us, which is really important. So now that we use the order date, we want to look at how the built in date hierarchy is set up. You may specify how a day feel should be used in the view by right clicking on the date field or using a drop down menu and selecting the various options. So let's review those options. If you do that, use a drop down here. The first section will be the date part, so this is only part of the date. The next part is the date value. This is truncated, so you can choose to have the entire value and then the exacting. So this is the individual date. Lastly, you have the option to choose between discrete and continuous. We'll leave everything as is for now. But let's see. Let's assume we want to do a monthly analysis to see what in which month do you sell the most product, So we can choose to select a month from the date part section and then replace that. I mean, it's a little bit easier to see in a bar chart, so you can see we sell the most in November in November. So this creates a total sales by month for the four years we saw in the previous view. So this tells us November is the most popular month. But let's say we want throughout which month year was the most popular. We can go back to our date and instead of using date part, use a truncated section, and now this creates a single bar for each month and year, and you can see in November 2014 was the most popular month of sales for that year. It's important to note that nearly any of these options continues as discrete or continuous fields. Date parts are discreet by default date values and exact dates or continuous by default. However, however, you can switch them between discrete and continuous as needed toe. Allow flexibility and the visualizations. For example, You may have you. You must have an access and thus a continuous field to create a reference line. Also tableau will Onley connect lines, the lowest level of row or column headers using a continuous date value and stabbed. Multiple discrete date parts will allow you to connect lines across multiple years and quarters. So let's say we want to do a year over year analysis of the sales so we can go back to our month view. Look at this as a line graph, and now I want to see a different line for every year. To do that, we can pull in the order day and put that into the color mark and change that two years so it are out of math. Used sets it two year, and so now you have a different line for every year. This creates a great visual to help executive see Year over year growth in the next section will look at other variations of date time and how to visualize those 5. Find Patterns Over Time: we left the last video with a year over year analysis. Got a couple things I left out where the labels and then also we used the month number and said the month name. So to do that, it's as simple as taking the year, holding down control and dropping that into the labels bucket. And you can see the labels here and then in the month. We've set that as continuous. If we change that too discreet look at the month name and this gives ah, a little bit better visual than the last example. So we've looked and using year over year old now analysis. But now let's do something a little different. Here is another example of using date parts on different shelves, so it she's useful analysis. Um, this next visualization is useful when looking at patterns across different parts of time, such as hours or days in a month. So we're going to use the heat met and can remove to show me. So what do you choose? The heat map this individually creates. However, we want to put the we want to remove the year and actually having the individual days in the columns and we want the months on the rose, and we can set that two days, and instead of having some sales be the size, we want that to be the color. So this heat map shows helps you find patterns. You can see it gets darker, the lower you go, and then also. So that means there are more sales later in the year, and then you can see at which dates of the month have the most sales. This view is very useful and doing those detail analysis where you're looking for patterns . Now, in the next video, we'll look at how to create a get chart. But before we do that, I want you to take a minute and see if you're able to create a Gant chart for yourself using the same data set. 6. Gantt Chart: so we reviewed how to use a heat map, and now we're going to use a Gant chart to look at how long it takes an order to be process . So from time it's received as an order to time it ships. So let's start by looking at each individual order. So we're going to go and pull in the order i d. And set that on the road that's gonna ask you that's too much data you can just say and all the members and we can also choose to order to filter the state of based on, um, one month of one year. So let's look in December 2013. And now we have all the data filter for December 2013 and we need to figure out how long it takes for in order to be processed. So right now we have an item called Time to ship in the measures. But let's say we want we didn't have that item. We can create our own time to ship measure. To do that, we create a calculated dimension under the analysis part criticality Dimension called Ship . Time and again, we'll go into much greater detail of calculated measures. But for now, let's use the date different function. And she's a day, the order date and the ship tied. Should they well gives gives us the time it takes to process the order. So right now, we just put the day into quotes to make it literal, and we hit, okay. And now we have a ship time calculation which we can use to put into to show how long it takes to ship. Something to do that. We just put that into the size. Um, Mark, remove the sales because we really don't need that and then choose again. Chart. So here you have again chart that shows you for each order. How many days takes the ship. However, it's doing something funky in the sense because if you have multiple items on the same order, it will summarize the two and and double or triple your time of ships. So what we can do is SAB choosing some. We set that to be a minimum, and now that gives you an accurate view off again. Chart in the next section will review how to use more advanced functionality within tableaux with tree maps and area chucks 7. Treemap: in this video will. We will review how to create a tree map and a couple of use cases for using a tree map in the real world. So let's remove the order. I d date ship time, and we're gonna look at the sales volume in treatment format, so we pull in sales volume and let's look at it by region, by category, can go re byproduct and item is the same as a product, which is tree map and what this does. It gives us a view of each square being a region. You can see the East is here. Central's here. West is here, so let's say we don't necessarily want. We want the each color to represent a category so we can drag the color the category into the color mark and rearrange it. So it's next the category, and what this does is gives the same color for each category so you can see in the South region table of the biggest seller. But in the East region there, um, they're also the biggest seller, so this helps you look do like for like analysis. We could also pull in regions into the rose to see a different size for each region. So that's how you would use a tree map to do your analysis on sales by category and item. 8. Pie Charts: In this recording, we will review pie charts. A pie chart is actually a mark typing tableau as we'll see in future parts. This gives you some additional flexibility with additional flexibility with pie charts that's not available for other types of charts, such as the ability to place them on maps. Create a pie chart is not difficult. Simply changed the mark. Type two pi. This will give you an angle shelf that well that you can use to encode a measure. Whatever dimensions, you have a place on the Marks card. Typically, the color shelf will define the slice of the pie, so let's walk through an example. So we choose a pie chart, and now we have an angle on the Marks section. Let's remove category. Let's remove items and now we have a pie chart of sales by a region. For the month of December 2013 we can remove the December filter and you can see the pie chart change shape. Let's add both the region and sales volume in the labels, so this is a really simple of his example of creating a pie chart. You'll notice that the pie chart uses sales to define the angle of each slice, the higher the some of the sales, the wide of the slices. The department dimensions, slices the measures and defines slice of the pie. This view also demonstrates the ability to place multiple fields on the label shop. The second sales is the percent of age of the total percentage of the total table calculation you saw previously. Be careful when using pie charts. Most visual experts will affirm that is far more difficult for the human eye to differentiate different angles as to differentiate between Lech or position. For example, without the labels in this chart, you would you really be able to tell whether one slice was really 25% instead of 30%. A bar chart showing sales for the three departments would be more readable. So let's take a look. So now you can see you definitely see which one is the highs and lowest versus a pie chart , which a little more challenging to figure out the different shapes and sizes. So that's the quick, quick introduction of pie charts and the next video we will review circle charts and visualizing distributions 9. Circle Charts: Welcome back, Teoh Tableau for beginners training. In this chapter, we will use circle charts to look at distribution. We're going to start by pulling in the sum of profit, and we want to look at that by region and we want in a circle chart. We want this some to be in the columns. We want the region to be a row, and now this gives you one dot for each region we want to color the regions and then we want to look at it by state. So what this will do is give you one dot for each state. You can see that there is no reference line, so there's nothing to compare against. One thing that does definitely jump out is that these three states you're losing money, and so you probably want to stop marketing in those states and close down your business. And if you want to add a reference line, you can right click on the Y axis select add reference line, and we want the reference line herself hit, Okay, and now you have an average for each region. This lets you see the distributional a bit better. One thing that is a little bit annoying that jumps out at me is that there's lots of overlap, so to resolve that issue we used jittering jittering is a method where we add noise intentionally. To remove some of this overlap, we can take the index, uh, from the measures, drop that into the rose, and so it shrinks the graph for some reason, expand the graph and shoes to calculate the index based on the state. So now you have less overlap, and you can better see where the clusters of data are. What you've done is index each state within each region and a as indexes continuous because it's green over here, it defines an access and causes a circle to spread out vertically. Now you can see more clearly each individual mark. You can use jittering techniques of many different kinds of visuals, so that's one way to visualize distribution. In the next chapter, we will look at boxing with whisker plots 10. Box And Whisker: and this part of the course we will look at box and whisker plots, box and whisker plots at additional information and context of distribution. They show the upper and lower quartile and whiskers which extend to either 1.5 times the upper slash lower quartile or to the maximum slash minimum values in the data. This allows you to see which data points are close to normal and which are out liars. So let's create a with box and whisker plot on the distribute thes circle chart. We just had you can instead of having the average you can change that to actually be a, um, box and whisker plot. So hit it at the edit reference. And so having a line, you can tell it to be a box plot. You leave the data with 1.5 times up, you are hit, okay. And this gives you your box and whisker plot. We can remove the index because it gets a little We don't need the jittering anymore so much, and we still want to be a large view. And this lets you see what your real outliers are so you can see the Ohio in the east in New York in the East have way more profitability than the rest of the East. That's all cluster together. This guy's will fire out there, too. In the central region, we have Texas and US Illinois that are pretty far outside off the district up box and whisker plot. In the West, you can see there's a wide distribution, and it includes pretty much everything. And then the South. Everything's clustered nicely together. Another possibility to show distribution is to use the hissed. A gram. Ah, hissed a gram looks similar to a bar chart, but the bars show the count of occurrences of a value. For example, standardized test orders looking for evidence, upgrade, tempering would use. Use the history Graham to see if there are any large jumps or spikes. So to create a history, Graham will create bins and then create a bar chart, which will do in the very next video 11. Scatter: in this video, we will continue to look at distribution by reviewing history grams, and then we will move on to scatter plots. Esta grams and tableau are very easy to make. There's there, right here in the show Me. So all you have to do is it's have one measure and choose your history Graham, and automatically creates the bins for you. Ah, been is the size of the Y axis the size of one bar. So that's our profitability been. We can also look there are sales been I mean our sales, Mr Graham. So pulling sales click instagram You can see most of our sales are from 0 to $1000 in value . So that's how you use history Rams to look at distribution. Next, we're going to use a scatter plot. Ah, scatter plot is an essential visual type to understand the relationship between To measure , consider a scatter plot. When you find yourself asking questions like does how much a spender marketing really make a difference to sales? How much does power consumption go up with each degree of heating or cooling? Is there any correlation between rental price and the length of contract Each of these questions seeks to understand the correlation between two measures. Scatter plots are great to see these relationships and also to locate out liars. Let's make a scatter plot with profit and sales. So let's clear our chart apple in sales pulling profit and we want to look at these by department. So right now we only have one point we can pull in department from the dimensions. Add that to the color marker, and then we can also pull in category and add that to the description. So where is category? It's right here. So add that to the label. And now you can see how the different house sales and profit are kind of correlates because the more sales you have more profit. You have, however, bookcases look like a negative profit margin product, and you can see no matter how much you sell, you're always gonna be losing money on that. On that category, the dimensions of department and category show the detail off those dimensions. Each marking the view represents the total sales in total profit for a particular category in a particular department. So that's one way you can look at scattered plus to see your distribution. Next, we will use a dual axis chart to really get into some or advanced analyses. 12. Dual Axix: So we created this scatter plot, and now we're going to create a dual access charge. One very important feature tableau are there is the dual access plots. Scattered plots use two axes, and they are extra. Why you always seen how toe use measure, name and measure values to show more than one measure on single axes you saw in the stack bar. Example that placing multiple continuous Greenfield's next each other on rows or columns results in multiple side by side accidents. Dual axis. On the other hand, I mean that a view is using two axes that are opposite to each other with a common pain. So let's create an example. So all you have to do is create is dragged to green fields into the Rose column. Remove your department and category. So this is just a stack box, and we want to look at this buy order date in the quarter. So let's choose quarter. And right now we have two different lines. If you want to make him into one one axes, you can choose jewel axes, and now you can see two different measures over time. On the same chart, you can observe several key features of the view. The sales and profit fields on the roads indicate that they have a dual axes by sharing a flattened side. You see that right there in the middle. The Marks card is now an accordion like control, with an all selection section and a section for sales and profit. You can use this customized marks for all measures or specifically customized marks for either sales or profit. So you can choose to have this be a color and what color it is, and you can change those options in this view. Right now, we're not gonna change anything. Sales and profit both defined. Why axes that are on opposite sides of the view so you can see right here and right here the sales are on the Y two axes. Profit is on the wild. One axes note that the peaks of the lines might lead you to believe that sales and profits were roughly equal, but this is unlikely to be the case that's just by business lunch. However, if you look at the actual data, you'll see that the two axes are very different in size, So what you can do is right click on the profit axes and tell it to synchronize. So sorry. I wonder what? On the y two acts with sales axes and tell it to synchronize the axes. And now this tells a much better story. You must set the synchronize option using the secondary axes. And if the synchronize access option is ever disabled or the secondary access, it's unlikely that to feels defining. The axes are different numeric types, So this is a very good example of how you need to make sure that you're presenting the data . Tell the story you're looking for. Creating a dual ACSI chart is relatively easy, so we just did it. And now in the next example, what we're going to do is create a combination chart. 13. Combination Chart: we're going to create a combination chart using the same data set we've been using of the superstore. So we're actually gonna look at sailed in two different ways, which is Libit not is not intuitive, but you'll see the value in the visual. So we create to sums we make him dual axes, which absolutely does nothing. It makes it look like the two lines overlapped, which that's exactly what's happening then. What we want to do is the first sales we want to make that a bar and the second sales. We want to actually make a different line for every department. So if you Dragon Department and put it on the color mark now, what this shows is a breakdown of sales by department on the lines do, and the bar is the total sales. However, you can see that axes on the line so it doesn't tell the story the way it should be told. So you can right click and synchronize axes. And now that tells you the breakdown of your total sales by department. In this line view over times, there are several things to note about this view The field on the color shelf is listed as multiple fields. So what that does is that indicates that different fields have been used for color for each axes on the mark's car. No field for the first sales axes an apartment for the second you can see in the first sales axes. There's nothing here on the second Sales acts easy at the department. The view demonstrates the ability to mix levels of detail. In the same view, The bars are drawn at the highest level, one that lines are drawn at the level of department. The view demonstrates the ability to use the same field sales in this case multiple times on the same shelf so you could see sales are used twice. The the months have been format to show abbreviations. This was done via the drop down menu on the order date field on the columns selecting format and then selecting the desired format for that field. Dual axes and combination charts open a wide range of possibilities for mixing mark types and levels of detail. We'll see a few more examples throughout the rest of the course, but you should definitely experiment with this feature and let your imagination run wild. So that's the end of this part of the course. Eso We'll summarize it real quick. We covered quite a bit of ground in this chapter. You should now have a good grasp of when to use certain types of visuals. The types of questions you asked will often lead to a certain type of you. You explore how to create these various types and how to extend basic visuals using a variety of advanced techniques such as calculated fields generating multiple mark types and dual axes along the way, we also covered some details on how dates working tableau. Hopefully, the examples using the calculations have made you eager to learn more about creating calculated fields. The ability to create calculations and tableau opens up endless possibility for extending data, calculating results, customizing visuals and creating rich user interactivity. We'll dive deep into calculations in the next two chapters to see what works and what doesn't