Palm trees

This example looks at perceptions of different countries as holiday destinations.

So, we can see that 52% off our sample are concerned about cleanliness in Mexico, compared to only 9% in France.

It's a table that benefits from a visualization.

Visualization > Bar

That's not so good. Let's do it as small multiples.

I don't love this.

Pyramid

Nope.

Radar

The labels are overlapping too much here.

Inputs > Chart type: Palm
Data manipulation> Switch rows and columns.

I love these. Look at how Great Britain and Australia have the same shape. This tells us that they are perceived similarly.

By hovering over, we see that the major concerns are to do with Cost and None of these. And this is the same concerns as people have when traveling to Australia.

To make this clearer, let's move the countries with similar profiles on the table to be next to each other.

The height of the palm trees tells us the average number of concerns. We can now easily see that Egypt has the highest level off concerns but is similar to China.

And, the basic issue for both is that people are concerned about most things.

The only thing people aren't concerned about are being boredome.

Now compare France with Great Britain. We can see that the key differences are these two fronds, with which present Language and Friendliness.

We can improve on this by putting some filters onto it

Filter > Control > List box Filter.

Let's filter by gender and age

Let us tidy this up.

First, I'm going to hide the table, so it is invisible when I share with clients.

Our design team created a great background for these. When I say created, I mean they found it on Shutterstock and added a blue box.

Let's publish it, so we can share it with others.

So, in no time at all, we've build this beautiful and useful calculator for exploring the data.

 

Campground

The earlier example used an existing visualization. Let's create something a bit more bespoke

This time we are going to pull in some raw data from a survey about campsites and build a beautiful interactive dashboard.

I'm going to do something a bit weird to start. Don't worry. It will get interesting.

I'm going to start by creating a bar chart which just shows one bar.

On the toolbar select Visualization > Number > Number in Bar

Let's hook this up to the table.

We will link it up to show the first row of data that is satisfied.

We can resize by dragging and dropping, but with things like this it can be easier to have more micro control.

Now, let's set this up as a traffic light system, so that when the values change it updates.

One of the cool things about Displayr is the Duplicate and modify workflow. Once you have something you like, you duplicate it and then modify it.

Continually select and duplicate until it looks like below.

Now, having duplicated them, I will hook them up to the numebrs.

Go through and change charts 3 to 18's Row numbers

Now for the cool bit.

Our designers came up with another great idea for this one, which they found on Shutterstock and tweaked a bit. Don't forget that you can use our designers too if you don't have the skills in house.

On the toolbar select Image > Browse your computer > and then browse for Resources\Data\Basic Displayr Demo\Campground_Background.png

This image is the wrong size, so we will need to resize it.

On the navigation bar, on the right, Zoom out and resize and click the zoom to fit button.

Now, we can make it beautiful just by moving the bars to the right spots.

I'm going to turn the overall bar into a circle.

Continue, remembering to use Align - vertical

 

Filtering

Let's now make it dynamically update when by camp site.

As you can see, now we've hooked up all our bars to dynamicaly change when we change the campsite.

 

NPS

I've got a variable in this data set which tells me how likely people are to recommend their camp site. Let's turn it into the net promoter score.

We are reading the value in this circle from the table we looked at before. We can also make it pull in data from a variable.

And, I will change it so that it's red if below 0, and green if above 50

As you can see it took us about 10 minutes to get this going. The hard part isn't so much the getting it working, it's more about figuring out how to make it beautiful. Our designers can help with this as well if you need.

 

Reach

In this example we will build a simple tool, designed for end users to experiment with different product ranges. The key thing we will see in this example is the flexibility you can get to do different types of calculations in Displayr.

This data set shows preferences for a sample of people for 11 different flavors of bubble gum.

The goal with this dashboard, is to allow the user to select different subsets of flavors, and find out how many people like one or more of the flavors.

Anything > Page Design > Control > List Box

By default, it has two options. We can replace them. Or, just delete them and hook it up to take its labels from the raw data.

Now we have a listbox where the user can choose the flavors they want.

Let's change it to multi select.

Now for the tricky bit.

Table > Raw Data > Variable Set

Here's the raw data. Each row represents a person. The numbers tell us if they liked a flavor, a 1, or didn't, a 0. So, far example, the first person in the data like Classic, Grape, Sour, Orange, and Cola.

Now, I want to set it up so that it only shows the columns of the selected flavors.

Now, I need to hook this up so the columns are selected based on the listbox.

Table > Select

As you can see, our new table has just got Sour and Strawberry selected.

Reading down this table, we can see that respondents 1 through 7 all like at least one of the two selected flavors. But, respondent 8 and 10, don't like either.

We can express this mathematically by calculating the maximum of each row.

Calculation > Maximum > Maximum Each Row

Now, we need to compute the percentage of people that like one or more of the brands. This is just the average of this column.

Calculation > Average

So, 70% of people like one or more of Sour And Strawberry

Now, let's write a sentence that automatically updates and calculates the percentage of people that like at least one of the flavors.

Anything > Page Design > Automatic Text data

Let's check it works. What happens when we add Classic?

That makes sense.

Move average below and off page.

Let's put a venn diagram on it to explain the reach.

Visualization > Venn

We can hook this up to our table showing the selected flavors.

Now, most of this is not interesting to a user, so I'm going to move it down and hide it.

Now let's make it beautiful!

I've got another beautiful background that our designers drew

So, in no time at all, we've created a beautiful dashboard that allows a client to experiment with different flavor portfolios.

So, as we've seen, we can create a beautiful visualization with bespoke calculations in not much time.

 

Burger tracking

This is the last of the four dashboards. We won't quite finish this one.

In this example we will build a PowerPoint-style dashboard for a tracking study.

New document > Burger Chef Brand tracker

 

Page master

This dashboard will have many pages, so we will set up some master pages to start with.

Page Master

I've been given some styling instructions to follow.

The image here is the background image for use in PowerPoint slides. It can be copied and pasted into Displayr.

As you can see, this image is in widescreen, so we will need to change our document size

And, we'll set up a title page master as well

Let's return to the document

OK, let's create a title page

We will add some data about restaurant chains

This table shows the key data we are going to focus on..

It compares the brand health data, of some key brands.

This data was just labeled as Q in the data file, so I'm going to rename it as Brand Health

While my table has lots of different brands, when comparing the brands, I'm only interested in the burger brands, so I'll hide the others

And we will order the rows of the table to more strongly reflect the puchase process

And let's filter it to the last 3 months

Now, let's also add some controls so that users can filter this by age and gender.

We will filter by age and gender.

The filters are at the top of the screen. I will move them to the page master.

As you can see, when I change the filters, the data updates.

Let's create a new page to visualize this

+ New Page > Title Only: Burger Brand Health Comparisons

 

Last 3 Months

Insert > Visualization > Pyramid

Output in pages: table.Brand Health

Let's tidy it up a bit more

When there is an ordering, it is often useful to show this via a gradient.

I'm going to use a special shade of red, for reasons that will become apparent.

 

Aided awareness

Now I'm going to illustrate the cool Duplicate and Modify workflow at the heart of Displayr.

We will duplicate these two pages.

The table we are looking like is based on lots of data, looking at the various brand health measures by brand. I'm going to start by pulling out the data that just shows aided awareness.

Again, we use the Duplicate and Modify approach. I first duplicate the aided awareness variables.

Then I combine them back as a new variable set.

And, I'll replace the current data with this new data.

And, let's cross this by our date data.

It's currently showing weekly data. Let's make it monthly.

Now we have a table that is aided awareness for each brand.

We're only showing three months of data, because it's remembering that filter we put on before, so we need to remove it.

I'm going to change the stat testing so that it explicitly tests for changes over time

Properties > Significance > Options
Advanced > Date > Compare to previous period

Now for a bit of magic.

Displayr has automatically hooked up this page to the revised data. Let's view this as area charts.

We'll add a 3 month rolling average

TREND LINES > Line of best fit > Moving average

This is a great way to show lots of brands, but it's also useful to just show one brand in much more detail.

Again, we duplicate and modify.

 

Over time

I'm going to add a combo box so users can select their brand. I can't quite remember how though, so I will have to search for it.

Anything > Page Design > Control > Combo Box

Move combo Box down to bottom left

I want the user to select their brands, so I will hook it up to the earlier table showing the brands over time.

And, we'll move this to the page master as well.

Now, I have to hook this up to the visualization

In this viusalization, I have switched the rows and columns about. So, while in the original table, the brands were in the rows, in the data underlying the visualization, they are columns.

For example, let's look at Pizza Heaven

Now, I'll turn it back into a column chart

A common question we're asked in support is how to put statistical testing onto charts, so let me show you, as it's a bit fiddly.

If you know your stat testing, you'll know that one way of quantifying the degree of statistical significance is to use a z-Statistic

STATISTICS > Cells > z-Statistic

Where the z is more than 1.96, it's signficance at the 95% level of confdeince.

To put the arrows onto this chart, I'm going to use the Annotations field.

Because we put brand onto the page master, it now appears here as well. I'll hide it under a whitebox.

 

Significance tests between brands

Now this page is doing stat testing over time, but what if we want to do stat testing between the brands

Again, we'll duplicate what we've done

Let's hook this up to the earlier brand health data.

We're getting an error because we linked the chart to the brand combo box, but, you may remember we hid the pizza brands from the earlier table.

As we want to compare the brands, it doesn't make sense to filter by the brand, so we'll delete it

We just want to see aided awareness, so let's enter that

We've got a different error now. Remember when we added the z-statistic to our earlier monthly data? We don't have this on our table for brand health. Let's update that table.

I know a lot of you like to use column letters for stat testing, so let's do that here.

Properties > Column comparisons

Now, we need to tell it to use the column comparison letters.

As we've hooked it up to all the metrics, it's showing them all. But, let's simplify this to just show awareness

So, now we have a chart showing column comparisons.

 

Ever buy

OK, now for a bit more magic.

We've created all these pages for aideded awareness.

Let's select them all, duplicate, and modify them.

Remember before how we created the data for aided brand awareness? We now need to do the same thing for ever eaten.

So, wait a second, and you will see this update automatically.

With this last one, we need to change the setting where we told it what row to use.

As you can see, while it took a bit of time to set up the first few, because we just duplicate and modify, it's very fast to create anything new.

As you can see, by using the Duplicated and Modify workflow, we can now quickly add new pages to the dashboard.

I'll record and send you a longer version of this last dashboard, including setting up a title page and navigation.