If you're not participating in the Back to Viz Basics community project yet, you should be. It's all about creating effective, simple charts, which is exactly what you need to be able to do before you build anything fancy. This will definitely help you master data visualization best practices.

For week 3, the objective was to build a text table of Olympic medal counts. Sounds simple, but unfortunately, building good looking tables isn't one of Tableau's strengths. 

I also started the #WatchMeViz livestreams again. You can find all of them on this playlist. Thank you to those that attended live and asked good questions and left thoughtful comments. Below is the livestream as well as my final viz.

Until next week...

In this tip I show you how to use the INDEX and RANK functions to label the top N values in a chart. I also explain the difference in how they work, and how the RANK function is simpler to configure.

In this week's Watch Me Viz, I covered the following charts: 

1. Line chart
2. Trellis chart
3. Slope graph
4. Connected scatter plot
5. Bar charts with comparisons
6. Diverging bar charts
7. Heatmap
8. Hex map
9. Tile map
10. Barbell chart
11. Peas in a pod chart
12. Bump Chart
13. Comet chart

In the end, I settled on the bump chart using highlighting and BANs. Other topics covered include:

1. Sorting calculations
2. Level of detail expressions
3. Rank table calculations
4. Parameters
5. Filter actions
6. Padding in dashboards
7. Cleaning tooltips
8. Divider lines in dashboards

There are times when you want to prevent your users from sorting a chart. This video has the solution for you.

Enjoy!

• Create the highlight table showing profit ratio by ship mode and sub-category.
• The columns should be sorted by the ship mode selected in the drop down first, followed by the remaining ship modes sorted descending by their overall profit ratio.
• The Product Subcategories should be sorted ascending or descending (depending on end user selection) of the profit ratios for the selected ship mode.

With Tableau 10 came the ability to create cross-database joins. In this video, I show you how to:

1. Create a cross-database join
2. Create a calculation across the data sources
3. Use the calculation to sort the view
4. Use the calculation as a boolean

A fun Data School Gym challenge for you today. Using this data source of human height since 1896, create this visualisation:

Requirements:

1. Each country should show only 1896 and 1996 and they should be connected
   
2. Label the midpoint with the country name
   
3. Use an orange to blue diverging color palette based on the Avg Height
   
4. Allow the user to filter by sex (no All option)
   
5. Create a parameter to allow the user to pick a country; it should also include an (All) option
   
6. Use the parameter to sort the visualisation; (1) If (All) is chosen then sort from largest to smallest based on the 1996 value. (2) If a specific country is chosen, that should be displayed at the top and the rest should be sorted from largest to smallest.

When the user picks Bermuda, for example, the visualisation should look like this:

Here’s the interactive version. Post a comment with a link to your solution. Good luck!

With the Olympics starting this weekend, I thought we’d take a look at the most classic way that people display Olympic medal counts, as stacked bars. Being an American, I pretty much have only known NBC as the host of the Olympics, so when I went to their website and looked for historical medal counts, I was mortified. This viz is just about as bad as it can get.

What works well?

• The countries are ordered from most medals to least.
  
• There’s cute little actions when you click on the medals.
  
• They used appropriate colors for each medal type.
  

Seriously, that’s all I see that’s any good. This is an incredibly poorly done graphic.

What doesn’t work well?

• There’s no title.
  
• There aren’t any tooltips, so I have no idea how big each bar is; I’m forced to guess.
  
• I can only see seven countries at a time, and I can’t even see the name of the seventh country. I mean, who would ever want to compare only the 15th-21st ranked countries?
  
• When I click on the scroll button, it scrolls by an increment of 2. Why?
  
• Comparisons are nearly impossible with a stacked bar except for the total medal count and bronze.
  

Here are some of the changes I made:

• I separated out each medal into a dot plot and chose to show only the top 25.
  
• I included a summary next to each country to provide the exact medals counts.
• I included a mobile view, but in this view I remove this summary for a better visual look.
• I included informative tooltips.
  
• I included a title so you know what the chart is about.
  
• I included filters so the user can decide which Olympic games to include.
  
• The "sort by" option allows the user to pick the medal count to sort by making comparisons easier.
  

Today is my 9 year anniversary using Tableau. On April 11, 2007, I downloaded a trial of Tableau 3.0 and my life has never been the same. What better way to celebrate than working on Makeover Monday and creating my first mobile dashboard.

This week’s Makeover Monday was quite tough. How do you take a viz that’s already great and make it better? Or how do you tell the story differently? I wrote about this viz on my other site (DataVizDoneRight.com) a couple weeks ago. Here’s the viz again:

What works well?

• Title catches your attention
  
• Subtitle makes you more interested and sets up the story
• Very well organized
• Clear labeling of the headers
• Pictures of the faces make it feel more real
• Consistent use of colors makes it easy to understand and follow
• Nice totals on the right for context and they’re out of the way as to not distract
• Dark background works well and makes the bars pop out
• Great tooltips!
• Fantastic sorting interactivity
• Great spacing; there’s a lot of information yet it still feels simple

What could be be improved?

• Include a filter for gender
  
• Include more women
• Change the mark type for the ends

So given how good this is already and how little I saw that I could do to make it better, I thought I would use this week to practice making a mobile version, formatted for iPhone 6. I rarely create visualisations specifically for mobile and the only way to improve that ability is to practice.

Adding the filter for gender was easy. Including more women was out of scope.

Notice that I changed the ends of each bar to dots. I did this because I think the vertical bars are a bit tough to see; I wanted to make it easer for the viewer.

One challenge I had was that I wanted the sorting to be “touchable” like the gender filter is, but I couldn’t get it to work. I didn’t want to spend a ton of time fiddling with it, so I resorted to a parameter for the sorting.

I’d like to hear what you think about this mobile version. Does it work well? What could I do to make it better mobile experience?

A new week means another challenge in the Data School Gym. This challenge came about because Nai Louza had a tough calculation she needed help figuring out. Here’s the final result you should produce:

Click on the image for a larger version

Requirements

1. Build a stacked bar chart that shows % of total sales for the East and West within each Product Sub-Category
   
2. Sort the bars by the % of total sales in the East
   
3. If you reorder the Regions, the sort should switch to the % of total sales in the West
   
4. Provide a method for the users to pick how many product sub-categories they want to include

Hints

1. You can do this with table calculations. You do not need to use LOD calcs.
   
2. For the sorting, you have to figure out how to sort by only the value of the East (or West if you change the order on the color shelf).
3. The Top N filter you see above is NOT a parameter.

You can find the final solution that I created here. Don’t cheat. Try to figure it out before looking at the solution. Reverse engineering is such a great way to learn.