Visualizing data

Basic principles of data visualization

Data visualization with Tableau Public

Introducing Tableau Public

Tableau Public allows you to create a wide variety of interactive charts and maps and organize them into dashboards and stories that can be saved to the cloud and embedded on any web page.

The free Public version of the software requires you to save your visualizations to the open web. If you have sensitive data that needs to be kept within your organization, you will need a license for the Desktop version of the software.

Tableau was developed for exploratory graphical data analysis, so it is a great tool for exploring a new dataset — filtering, sorting and aggregating the data in different ways while experimenting with various chart types.

Although Tableau was not designed as a publication tool, the ability to embed finished dashboards and stories on any web page has also allowed organizations that lack JavaScript coding expertise to create customized interactive online graphics.

The data we will use

Download the data for this session from here, unzip the folder and place it on your desktop. It a folder called nations, with the following files:

nations.csv Data from the World Bank Indicators portal, which is an incredibly rich resource. Contains the following fields:
- iso_a3 Three-letter code for each country, assigned by the International Organization for Standardization.
- country Country name.
- year
- region income_group World Bank regions and current income groups, explained here.
- population Estimated total population at mid-year, including all residents apart from refugees.
- gdp_percap Gross Domestic Product per capita in current international dollars, corrected for purchasing power in different territories.
- life_expect Life expectancy in years for a child born in the year in question, if prevailing patterns were to stay the same throughout its life.
- population Estimated total population at mid-year, including all residents apart from refugees.
- birth_rate Number of live births during the year per 1,000 people, based on mid-year population estimate.
- neonat_mortal Neonatal mortality rate: number of babies dying before reaching 28 days of age, per 1,000 live births in a given year.

Visualize the data on nations’ health and wealth

Connect to the data

Launch Tableau Public, and you should see the following screen:

Under the Connect heading at top left, select Text File, navigate to the file nations.csv and Open. At this point, you can view the data, which will be labeled as follows:

Text: Abc
Numbers: #
Dates: calendar symbol
Geography: globe symbol

You can edit fields to give them the correct data type if there are any problems:

Once the data has loaded, click Sheet 1 at bottom left and you should see a screen like this:

Dimensions and measures: categorical and continuous

The fields should appear in the Data panel at left. Notice that Tableau has divided the fields into Dimensions and Measures. These broadly correspond to categorical and continuous variables. Dimensions are fields containing text or dates, while measures contain numbers.

If any field appears in the wrong place, click the small downward-pointing triangle that appears when it is highlighted and select Convert to Dimension or Convert to Measure as required.

Shelves and Show Me

Notice that the main panel contains a series of “shelves,” called Pages, Columns, Rows, Filters and so on. Tableau charts and maps are made by dragging and dropping fields from the data into these shelves.

Over to the right you should see the Show Me panel, which will highlight chart types you can make from the data currently loaded into the Columns and Rows shelves. It is your go-to resource when experimenting with different visualization possibilities. You can open and close this panel by clicking on its title bar.

Columns and rows: X and Y axes

The starting point for creating any chart or map in Tableau is to place fields into Columns and Rows, which for most charts correspond to the X and Y axes, respectively. When making maps, longitude goes in Columns and latitude in Rows. If you display the data as a table, then these labels are self-explanatory.

Initial questions to ask this data

I first approached the dataset with the following questions:

What is the relationship between a nations’ wealth, measured as GDP per capita, and their citizens’ life expectancy?
How has this relationship changed over time?

You may have realized that these are essentially the same questions asked in the Gapminder video we saw in the opening session — so our chart will be rather similar.

Make a bubble chart to explore the relationship between wealth and life expectancy, and animate over time

From the morning session, you will remember that we can investigate relationships using a scatter plot. One would imagine that the people in wealthier countries would live healthier and longer lives. So we will put wealth on the X axis, as the presumed explanatory variable, and life expectancy on the Y.

First let’s rename these variables, so that their meaning is unambiguous. Hover over Life Expect, click on the small downward-pointing triangle that appeats, select Rename and call it Life expectancy at birth (years). Similarly, change Gdp Percap to GDP per capita.

Now drag GDP per capita to Columns and Life expectancy at birth (years) to Rows. Notice that this results in a chart with a single point:

This is because Tableau’s default behavior is to aggregate continuous variables — in this case it has added up all the values in the dataset using the function SUM.

To override this behaviour, and see every single data point, select Analysis from the top menu and uncheck Aggregate measures. The chart should now look like this:

However, removing aggregation disables some useful functions (more on this later), so select Analysis and check Aggregate measures once more. Hover over each of the measures in the Columns and Rows shelves, click on the downward-pointing triangle to open the dropdown menu, and change the aggregation from Measure (Sum) to Measure (Average). The chart should looks like this:

Now drag Country to the Detail shelf under Marks. This creates a separate mark for each country, plotting the average values over the entire time period for each. The chart should now look like this:

To show just one year’s data, and to animate the changes over time, drag Year into the Pages shelf. Notice that this both filters the data and adds controls to move through the years:

Although we are still aggregating the data using the function AVG, there is only one record per country, per year, so the chart is now plotting single values.

Experiment with the page controls, and notice that the chart goes blank in 2013 and 2014 — years for which there is no data. This is not desirable behavior, but we can prevent it by filtering those years out of the displayed data.

Hover over Year in the Pages shelf, click on the downward pointing trial and select Filter.... Uncheck the two years with missing data and click OK:

Now drag Region to Color, and the circles will be colored with Tableau’s default qualitative color scheme for categorical data. (Tableau’s qualitative color schemes are well designed, so there is no need to adopt a ColorBrewer scheme. However, it is possible to edit colors individually as you wish.)

For a more subtle color scheme, click on Color, select Edit Colors... and at the dialog box select the Tableau 10 Light qualitative color scheme, then click Assign Palette and OK:

In the Marks shelf, change from Automatic to Circle to switch to solid circles.

As the circles overlap, let’s give them some transparency so each can be seen. Click on Color again, drop the transparency to 75% and give each circle a gray border to help distinguish them from one another. The chart should now look like this:

It’s clear that there are a few outlier countries with very high GDP per capita, with most of the others clustered at the bottom of the range. Using a logarithmic scale for the X axis will help see differences in population density for most nations.

So right-click on the X axis and select Edit Axis. At the dialog box, check Logarithmic:

Running through the years, there are never any values of less that $100 on the X axis. So now let’s edit the axis range and also change the units so that it’s clear the figures are in $.

To fix the latter, hover over GDP per capita in the Measures panel and select Default Properties>Number Format... and fill in the dialog box as follows:

Now right-click on the X axis and select Edit Axis. At the dialog box, check Fixed and set the Start value as 100. Also edit the Title, to remove Avg. as only a single value is being shown:

Edit the Y axis Title to remove Avg. also. The chart should now look like this:

There does indeed seem to be a relationship between wealth and life expectancy, so let’s draw a trend line. Switch to the Analytics tab in the panel at left, drag Trend Line over the chart area, and drop it onto the chart icon labeled Logarithmic:

Remember from the opening session that the relationship between wealth and life expectancy across nations is logarithmic, but the logarithmic X axis transforms the curve into a straight trend line. However, rather than a single trend line we have one for each region, and confidence bands around each line have also been drawn:

Now select Analysis>Trend Lines>Edit Trend Lines and edit the dialog box to the following:

Hover over the trend line to see its equation. (If you wish, you can also turn off the logarithmic option on the X axis temporarily, to see what the logaraithmic curve looks like.)

Right-click on the line, select Format... and change the thick black line to thinner gray dashes. The chart should now look like this:

Use the Page controls to play through the years again, and notice that the slope of the line becomes shallower over time.

Having explored this relationship, we could stop there. But we can also highlight larger countries by dragging Population to Size. After doing so, click on Size and move the slider to the right to increase the size of all of the circles.

Tableau’s default behavior is to scale circles correctly, by area. So the relative size of the circles corresponds to the countries’ population in each year.

The chart should now look something like this:

Now click on the title bars for the size and color legends and select Hide Card to remove them from the visualization. We can provide the values for the total amount of protected land through a tooltip, rather than a legend. And we will later make a map to serve as a color legend, making that redundant.

Hover over one of the circles, and notice the tooltip that appears. By default, all the fields we have used to make the visualization appear in the tooltip. (If you need any more, just drag those fields onto Tooltip.) Click on Tooltip and edit as follows:

Unchecking Include command buttons removes some additional Tableau tooltip functionality, giving a plain tooltip.

There’s a problem with the chart: Some of the smaller circles lie behind larger ones, which means that their tooltips can’t be accessed. To solve this, open the dropdown menu for Country in the Marks shelf, select Sort and fill in the dialog box as follows:

Now drag Country so it appears at the top of the list of fields in the Marks shelf. The sort we have just performed would not have been possible if we had unchecked Aggregate Measures earlier. It should ensure that the smallest circles always appear on top:

Take some time to consider how the chart is constructed in relation to the principles covered in this morning’s session, especially the perceptual heirarchy of visual cues.

Save to the cloud

Right-click on Sheet 1 at bottom, select Rename Sheet, and call it Bubble chart.

Having finished this chart, now is a good time to save our work. From the top menu, select File>Save To Tableau Public. At the logon dialog box enter your Tableau Public account details, give the Wookbook a suitable name and click Save. When the save is complete, you can close that window.

Make a map to use as a color legend

Select Worksheet>New Worksheet from the top menu, and double-click on Country. Tableau recognizes the names of countries and states/provinces; for the U.S., it also recognizes counties. Its default map-making behavior is to put a circle at the centroid of each area, which can be scaled and colored to reflect values from the data:

However, we need each country to be filled with color by region. Using Show Me, switch to the filled map option, and each nation should fill with color. Drag Region to Color and see how the same color scheme we used previously carries over to the map. Click on Color, set the transparency to 75% to match the bubble chart and remove the borders. Also click on Tooltip and uncheck Show tooltip so that no tooltip appears on the legend.

We will use this map as a color legend, so its separate color legend is unnecessary. Click the color legend’s title bar and select Hide Card to remove it from the visualization.

Center the map in the view by clicking on it, holding and panning. It should now look something like this:

Rename the worksheet Inset map and save to the web again.

Make a dashboard displaying the bubble chart and map color legend

From the top menu, select Dashboard>New Dashboard. We can set the size of the dashboard to fit the web page in which it will be embedded, and this can be a Range, giving some basic responsive design. For simplicity, we will set the dashboard to Laptop size.

Drag Bubble chart from the panel at left to the main panel. The default title, from the worksheet name, isn’t very informative, so right-click on that and select Hide Title.

Right click on the Year title for the Page control, and Edit title to increase its font size.

Notice that Tableau allows you to drop various other items onto a dashboard: horizontal and vertical containers, text boxes, images, web pages and blank space.

Drag a Text box onto bottom of the chart, until the lower part of the bubble chart becomes gray, showing where the new element will appear. Then add the source information:

The source text box will be much too large, so extend the size of the chart window as appropriate. Now is also a good time to set the font size for the axis labels, which are a little small. Right-click on each axis, select Format and increase the font size to 10pt.

Now select Dashboard>Show Title from the top menu. Right-click on it, select Edit Title... and change the default <Sheet Name> to something more informative:

When adding items to a dashboard, you can make them Tiled or Floating, which allows them to be placed over the top of one another. Switch to Floating and drag the map onto the bottom right of the chart. Hide its title, and if necessary reduce its size so that it doesn’t obscure any of the circles in any of the years. Also right-click on the map and select Hide View Toolbar and Hide Map Search. This will remove the map’s interactive controls.

The finished dashboard should look something like this:

Rename the dashboard and save to the web.

Once the dashboard is online, use the Share link at the bottom to obtain an embed code, which can be inserted into the HTML of any web page.

(You can also Download a static view of the graphic as a PNG image or a PDF.)

Some more questions to ask this data

I next decided to explore the data on neonatal mortality, asking the following questions:

How have the total number of neonatal deaths changed over time, globally, regionally and nationally?
How has the neonatal death rate for each country changed over time?

Create new calculated variables

The data contains fields on birth and neonatal death rates, but not the total numbers, which must be calculated. From the top menu, select Analysis>Create Calculated Field. Fill in the dialog box as follows (just start typing a field name to select it for use in a formula):

Notice that calculated fields appear in the Data panel preceded by an = symbol.

Now create a second calculated field giving the total number of neonatal deaths:

(We have run some simple arithmetic, but it’s possible to use a wide variety of functions to manipulate the data in various ways.)

Make a series of treemaps showing neonatal deaths over time

For any one year, I realized that a treemap would allow me to directly compare the neonatal deaths in each country, nested by region.

In a new worksheet, drag Country and Region onto Columns and Neonatal deaths onto Rows. Then open Show Me and select the treemap option. The initial chart should look like this:

Now remove Region from Label to show just the country names, and drag Region to Color. Click on Color and set transparency to 75%, to match the appearance of our previous chart.

The treemap should now look like this:

Notice that Tableau has by default aggregated Neonatal deaths using the SUM function, so what we are seeing is the number for each country added up across the years.

To see one year at a time, we need to filter by year. If you drag the existing Year variable to the Filters shelf, you will get the option to filter by a range of numbers, which isn’t what we need:

Instead, we need to be able check individual years, and draw a treemap for each one. To do that, select Year in the Dimensions panel and Duplicate.

Select the new variable and Convert to Discrete and then rename it Year (discrete). Now drag this new variable to Filters and select 2012 (the last year for which there is data).

The treemap now displays the data for 2012:

That’s good for a snapshot of the data, but with a little tinkering, we can adapt this visualization to show change in the number of neonatal deaths over time at the national, regional and global levels.

Select Year (discrete) in the Filters shelf and Filter ... to edit the filter. Select all the years with even numbers (apart from 2014, for which there is no data) and click OK:

Now drag Year (discrete) onto Rows and the chart should look like this:

The formatting needs work, but notice that we now have a bar chart made out of treemaps.

Extend the chart area to the right by changing from Normal to Fit Width on the dropdown menu in the top ribbon:

I find it more intuitive to have the most recent year at the top, so click on this sort icon in the top ribbon to change the order of the bars:

The rectangles are now too small for the labels to work well. Rather than removing them entirely, let’s just leave a label for India in 2012, to make it clear that this is the country with by far the largest number of neonatal deaths. Click on Label in the Marks shelf, and switch from All to Selected under Marks to Label. Then right-click on the rectangle for India in 2012, and select Mark Label>Always Show. Right click again on the rectangle and select Format. Under Sheet, open the dropdown menu for Default>Pane and set the color to a dark gray. The chart should now look like this:

We can again use the map as a legend for the regions, so hide the color legend. Edit the tooltip as follows:

To remove some clutter from the chart, select Format>Borders from the top menu, and under Sheet, Rows and Columns set all the options to None. Right-click on Year (discrete) at the top left of the chart and select Hide Field Labels for Rows. Then hover just above the top bar to get a double-arrowed drag symbol and drag upwards to reduce the white space at the top. You may also want to drag the bars a little closer to the year labels. The chart should now look like this:

Rename the worksheet Treemap bar chart and save to the web.

Make a line chart showing neonatal mortality rate by country over time

To explore the neonatal death rate over time by country, I decided to use a line chart.

First, rename Neonat Mortal as Neonatal death rate (per 1,000 births). Then, in a new worksheet, drag this variable to Rows and Year to Columns. Also drag Country to Detail in the Marks shelf to draw one line per country. The chart should now look like this:

Drag region to Color, set the transparency to 75%, and remove the color legend. Notice that this data finishes in 2013. To make the range consistent with the treemaps, drag Year (discrete) to filter and select all years apart from 2013 and 2014.

Now right-click on the X axis, select Edit Axis, edit the dialog box as follows and click OK:

To minimize chart junk, select Format>Borders from the top menu, and under Sheet set all the options to None. Then select Format>Lines, under Columns set Grid Lines ro None, and under Sheet set Axis Ticks to None.

Right-click on the X axis again, select Format, change Alignment to Up and use the dropdown menu set the Font to bold.

The chart should now look like this:

We can also highlight the countries with the highest total number of neonatal deaths by dragging Neonatal deaths to Size. The chart should now look like this:

This line chart shows that the trend in most countries has been to reduce neonatal deaths, while some countries have had more complex trajectories. But to make comparisons between individual countries, it will be necessary to add controls to filter the chart.

Tableau’s default behavior when data is filtered is to redraw charts to reflect the values in the filtered data. So if we want the Y axis and the line thicknesses to stay the same when the chart is filtered, we need to freeze them.

To freeze the line thicknesses, hover over the title bar for the line thickness legend, select Edit Sizes... and fill in the dialog box as follows:

Now remove this legend from the visualization. We will later add an annotation to our dashboard to explain the line thickness.

To freeze the Y axis, right-click on it, select Edit Axis..., make it Fixed and click OK:

Right-click on the Y axis again, select Format... and increase the font size to 10pt to make it easier to read.

Now drag Country to Filters, make sure All are checked, and at the dialog box, and click OK:

Now we need to add a filter control to select countries to compare. Hover over Country in the Filters shelf and select Show Quick Filter. A default filter control, with a checkbox for each nation, will appear to the right of the chart:

This isn’t the best filter control for this visualization. To change it, hover over the title bar for the filter, note the range of filter controls available, and select Multiple Values (Custom List). Then select Edit Title... and add some text explaining how the filter works:

Take some time to explore how this filter works.

Rename Income Group to Income group so its case is consistent with the other variables named on the chart. The add Region and Income group to Filters, making sure that All options are checked for each. Select Show Quick Filter for both of these filters, and select Single Value Dropdown for the control. Reset both of these filters to All, and the chart should now look like this:

Now let’s provide a single label to highlight India, as we did for the treemap. Drag Country onto Label, then click on Label and highlight Selected. Then hover over the line for India, select a point, right-click and select Mark Label>Always Show. Right-click on the point again, select Format and under Sheet>Pane set the font color to a dark gray.

The chart should now look like this:

Finally, click on Tooltip and edit as follows:

Rename the sheet Line chart and save to the web.

Make a dashboard combining both charts

Select Dashboard>New Dashboard from the top menu, and make it Laptop size.

Add Treemap bar chart to the dashboard, hide its title and then Fit Width to make it fill the dashboard area. Similarly, add Line Chart to the right of the dashboard, which should now look like this:

This needs some reformatting. Drag the bottom of the first filter control down to create some room for the lists of countries that it will create.

Notice that the Region and Income group filters control only the line chart. To make them control the treemaps, too, for each filter select Apply to Worksheets>Selected Worksheets... and fill in the dialog box as follows:

The filters will now control both charts.

Add Inset map for a color legend at bottom right. Hide its title and remove the map controls, as for the first dashboard.

We can also allow the highlighting of a country on one chart to be carried across the entire dashboard. Select Dashboard>Actions... from the top menu, and at the first dialog box select Add action>Highlight. Filling the second dialog box as follows will cause each country to be highlighted across the dashboard when it is clicked on just one of the charts:

Click OK on both dialog boxes to apply this action.

Add a title and source information. Then switch to the Floating option, then drag a Text box to the top of the line chart to add an annotation explaining the thickness of the lines.

Give the dashboard an appropriate name, and save to the web.

The final dashboard should look like this:

Again, take some time to consider how this visualization of the data works, in relation to the principles we discussed in the opening session.

From dashboards to stories

Tableau also allows you to create stories, which combine successive dashboards into a step-by-step narrative. Select Story>New Story from the top menu. Having already made a dashboard, you should find these simple and intuitive to create. Select New Blank Point to add a new scene to the narrative.

Better responsive design

While the Tableau dashboard size Range option gives some basic responsive design, this will not easily allow you to create dashboards that work on every device from a small smartphone to a large desktop computer.

I would suggest creating three different dashboards, each with a size Range appropriate for phones, tablets, and desktops respectively. You can then follow the instructions here to put the embed codes for each of these dashboards into a div with a separate class, and then use @media CSS rules to ensure that only the div with the correct dashboard displays, depending on the size of the device.

If you need to make a fully responsive Tableau visualization and are struggling with these instructions, contact me for help!

As for all responsively designed web pages, make sure to include this line of code between the <head></head> tags of your HTML:

<meta name="viewport" content="width=device-width, initial-scale=1.0">