## VizWiz

Launch, grow, and unlock your career in data

## #WOW2021 Week 15 - Workout Wednesday Website Analytics

The requirements for week 15 are here. This is another super useful challenge as it helps you develop a dashboard you could easily use in your own organization.

My go-to blog post for working with and formatting time is this one from Jonathan Drummey. I'd say it's critical for solving this challenge. Also, think about the calcs for the reference lines and the BANs. As a hint, they're not just simple reference lines based on the measure on the rows. You WILL need to calculate the overall average separately.

Click on the image to interact with the dashboard and/or download the workbook here.

## #WOW2021 Week 16 - How Do Sub-Category Sales Compare to the Sub-Category Average for Each Category?

Lorna was being very kind with Workout Wednesday Week 16. The chart was pretty simple to build and the LOD required would have been easy enough to write (though I would have used a table calc). However, Lorna wanted us to get familiar with the Quick LOD feature that came out in Tableau 2021.1. Quick LODs are a super fast way to create FIXED level of detail expressions.

This workout required creating two quick LODs. So you have to think through the aggregations and adjust the default aggregation BEFORE creating the quick LOD. Here are my steps:

1. Create a Quick LOD of Sales by Sub-Category by dropping Sales on top of Sub-Category (hold Command on a Mac while dropping). Since I left the default aggregation of Sales as SUM, this results in this LOD:

{ FIXED [Sub-Category]: SUM([Sales]) }

2. Change the default aggregation of this new field to average. You have to do this so that at the Category level, you're getting the average of the sales across the sub-categories in each Category.

3. Again, create the Quick LOD by holding Command (Control on a PC) and dropping the calc created in step 1 on top of the Category field. This is the resulting calculation:

{ FIXED [Category]: AVG([Sales (Sub-Category)]) }

I'll leave the rest of the calcs to you. Good luck!

## Using Parameter Actions to Highlight a Segment of a Waterfall Chart

This viz is based on a tutorial from Ryan Sleep, which you can find here. Feel free to download the workbook to see how it's built.

A few techniques covered:

1. Parameter actions
2. Table calculations
3. Gantt chart to build the waterfall chart
4. Highlighting
5. Formatting
6. Calculated reference bands

That's about it I think. For some reason Tableau Public isn't centering the text on the buttons at the top; they're fine in Tableau Desktop. See if you can rebuild it before you download it. You'll learn a lot and you'll make a great looking waterfall chart.

## How to Create a Dynamic Quadrant Chart Using a Set Action

A quadrant chart, by definition, is a scatter plot with a background split into four equal sections. Typically, though, the sections are divided up as to how they compare to the average of both axes.

In this video, I show you how to make the axes you want to compare to dynamic. I show you how to use a set action to change the reference point to which each quadrant is compared.

## #MakeoverMonday 2021 Week 17 - Price Parity in America

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
7. Cleaning tooltips
8. Divider lines in dashboards

View the final dashboard here.

## How to Create a Dynamic Quadrant Chart Using a Parameter Action

A quadrant chart, by definition, is a scatter plot with a background split into four equal sections. Typically, though, the sections are divided up as to how they compare to the average of both axes.

In this video, I show you how to make the axes you want to compare to dynamic. I show you how to use a parameter action to change the reference point to which each quadrant is compared.

## #MakeoverMonday Week 16 - The Impact of Covid on Air Travel in America

I struggled to come up with anything interesting this week, but that's ok. I was still able to explore the data a lot and ended up with a simple dashboard. Check out #WatchMeViz and interact with the viz below.

## How to Calculate a Z-Score

A Z-score is a numerical measurement that describes a value's relationship to the mean of a group of values. Z-score is measured in terms of standard deviations from the mean.

• If a Z-score is 0, it indicates that the data point's score is identical to the mean score.
• A Z-score of 1.0 would indicate a value that is one standard deviation from the mean.
• Z-scores may be positive or negative, with a positive value indicating the score is above the mean and a negative score indicating it is below the mean.

The calculation you need is Tableau is:

( SUM([Profit]) - WINDOW_AVG(SUM([Profit])) )
/
WINDOW_STDEV(SUM([Profit]))

Replace the SUM([Profit]) with whichever measure you'd like to use at the aggregation that makes sense in your data.

Get the data used in the video here - https://data.world/vizwiz/car-sales-mock-data

## #MakeoverMonday 2021 Week 15 - Fouls Called by NBA Referees

The original viz for this week was so good that I struggled to come up with something different. In the end, I wanted to learn by recreating the original. Check out #WatchMeViz and interact with the viz below.

## How to Create a Ternary Graph / Triangular Chart

Ternary graphs visualise the ratios between the three variables. A ternary graph requires three metrics, plotted as a triangle, where the sum of all three variables adds up to a constant. You can think of it as a three dimensional scatterplot.

Each dimension is plotted based on its relative variance (on a scale of 0%-100%) to the largest value within the dimension.

A value plotted near the top would indicate a weighting towards the variable at the top. Likewise, for the bottom right, a value plotted there would indicate a weighting towards the variable that was plotted on the bottom right. A value in the middle, indicates the dimension is balanced across all three variables.