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November 26, 2020

How to Create U.S. Electoral Cartograms

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I don't remember how I came across the set of cartograms I'm going to show you how to create. Alas, I wanted to recreate this mesmerising set of cartograms that Noah Veltman created based on election maps from various media outlets.

Noah's page contains the vector files for each map. I saved them individually and prepped the data in Alteryx so that I could build the polygons in Tableau. Download the workflow here.

I needed to create two branches because some of the States are divided up into parts. For example, Maine in the NPR map has four blocks since Maine allocates each of its four electoral college votes separately. This required the same steps to be reproduced twice. For those States with multiple blocks, I had to split out each block, pivot them, then split those results, and pivot one more time.

Once I had the CSV, it was pretty easy to build in Tableau.

  1. X on the Columns
  2. Y on the Rows (and reverse the axis)
  3. Set both X and Y to AVG
  4. Change the mark type to Polygon
  5. Add the Path field to the Path shelf (this tells table how to connect the edges of the polygon)
  6. Add the State field to the Detail shelf

From there, it was some formatting for the colors, etc. This process, I would think, would work for any SVG (vector) file. This was a fun little project. I learned a lot!

November 24, 2020

How to Create a Combination Bar Chart & Candlestick Chart

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In a recent Makeover Monday #WatchMeViz, I showed how to create a bar chart to compare two measures and then add a candlestick chart as well to show the difference between the two measures. It's actually quite simple; it requires some knowledge of:

  1. How Measure Names and Measure Values work together
  2. How to create a combined axis chart
  3. How to create a dual axis chart
  4. How to create a Gantt chart

In this video, I show you how to do just that. Enjoy!

November 23, 2020

#MakeoverMonday: America Needs to Pay Its Bills

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Today's Makeover Monday marked my 1,000th viz published to Tableau Public. I must say that I'm pretty proud of myself. This feels like a pretty big milestone in my career. I wonder how many hours I've spent using Tableau in my life.

Thank you for all of your support and encouragement along the way. Tableau wouldn't be anything without the Community.

Let's get to week 47. The visualization comes from Visual Capitalist.

What works well?
  • The bar/line combination charts work well since they are on the same scale. This also makes them easier to distinguish.
  • Choosing colors that match the American flag (I'm assuming that was intentional)
  • Making 2020 a slightly different shade of red
  • Title is clear
  • Text callouts add useful context
  • Big numbers to show the most recent values

What could be improved?
  • The 2020 bars are at the quarterly level, but the remaining bars are by year. Is it the end of the year? The start of the year? That could easily lead to confusion. Keep it as a consistent time scale.

That's about it. Overall, it's pretty well done.

During this week's #WatchMeViz, I iterated through 16 different charts before settling on a connected scatterplot. I created a tornado chart that I really, really wanted to make work, but I didn't quite get there. 

My goals:
  • Compare debt to GDP
  • Show the debt to GDP ratio
  • Show when the debt to GDP ratio exceeded 100%
  • Highlight important milestones that led to the largest increases

I find that I nearly always end up with a simple chart. I don't know why. I do know I don't like complicated though. I bet 90% of my vizzes are bars, lines, scatterplots, heatmaps, and maps.

Click on the viz to view on Tableau Public.

November 19, 2020

Pregnancy, Birth, and Abortion Rates in America

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With Amy Coney Barrett being sped through the confirmation process of the US Senate before the 2020 Election (as hypocritical as it was) to become the 9th justice on the Supreme Court, there is now a conservative stranglehold on the judicial branch of government.

Justice Barrett deflected all questions about her stance on abortion during the confirmation process and it has raised lots of speculation that Roe v. Wade will be overturned. Yeah, you know, because the government should control a woman's body, yet there is nothing similar for men. Like, why doesn't a man get castrated if he accidentally impregnates a woman? Blasphemy they say; hypocritical I say.

I wonder if any of the anti-abortion Justice or Congresspeople have ever considered their stance if their daughter had an unplanned pregnancy. What is she got raped and pregnant? I bet their tune would change.

Anyway, my political and social views aside, this made me think about abortion rates in America. Since Roe v. Wade, abortion rates in the US have plummeted.

What the data tells us is that Roe v. Wade has actually led to a REDUCTION in abortions. It also shows us the shift towards women waiting later in their lives to have children. 

All of the data comes from the Guttmacher Institute (I'd highly recommend you read their insights), which I have compiled and prepared. You can download the data here.

The view I wished that the Guttmacher Institute had was a way to view regional trends, State trends and comparisons to U.S. and All Ages data. I decided to create a tile map showing the trends over time, which also allows you to include or exclude the US and All Ages totals. It's an interesting data set to explore. Start with your own age and where you live. What's the situation there?

This was a fun visualization to build and I would like to thank Seffana Mohamed-Ajaz for her feedback and suggestions of some minor tweaks.

Click on the gif below to interact with the visualization. There's an important story to tell and important rights of women to ensure are retained.

Workout Wednesday 2020 Week 47 Solution Guide - Clustered Histogram

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First off, please don't follow this guide if you haven't already given the challenge your best effort. It won't benefit your learning to simply follow these steps without learning what you did right and wrong.

The ultimate goal from #WOW2020 Week 47, was to create this clustered histogram:

The toughest parts of this challenge is creating the x-axis. You can't use traditional bins because:

  1. You can't lump together the $2,000+ orders (bins are fixed sizes).
  2. You can't use bins in calculations, thus you can't lump them together this way either.

So how do you mimic what bins do without using bins? You could write some crazy long case statement with 20 options in it (from 100-2000 for each $100 bin), or you could simply use the FLOOR function. The FLOOR function rounds to the nearest integer of equal or less value. Think of it like a round down to the nearest integer.

Ok, so what does that have to do with bins? With a bit of math, the floor function allows us to mimic bins. For example, this calculation will create bins of 1,000:


This obviously means, then, that to create bins of 100, we simple remove a zero:


And now we're really close. The problem remaining is that it's looking at the row level, but we want each bins to be at the Order ID level. We don't have Order ID in the view, therefore we need to create a level of detail expression, I called it SALE AMOUNT:

FLOOR({ FIXED [Order ID] : SUM([Sales]) }/100)*100)

Calculations work inside out in Tableau. To turn this into a sentence, I would say:

  1. For each Order ID, return the sum of sales.
  2. Divided each Order ID sales by 100 and round down to the nearest integer.
  3. Multiply that result by 100 to get it back up to bins of 100.

Great, but what about lumping together all of those above $2,000? A couple of simple IF statements do the trick. I started by building the view like this:

We need to unstack the bars:

Uh oh! We need to do something to make the bars next to each other instead of on top of each other. Let's create a calc that offsets the bars:

This will put the bars that are in the 0-100 bin at 25, 50, and 75. Then those in the 100-200 bin will be 125, 150, and 175. And so on.

We then need to go back to our SALE AMOUNT calculation and account for both the offset and lumping together above $2,000.

Ta da! Magic! Now that we have the correct calculations, it's a matter of building the view.

On the Size shelf, change it to Manual sizing and drag it around until the bars are split up a bit. The tooltip requirement involved a couple more calculations, but none of them are complicated. You can get them from my viz, but only do that if you're REALLY stuck. Give it your best effort first.

Click here or the image below for the interactive version and to download my solution.

November 17, 2020

How to Create a Single Column Hierarchy Drill Down Drill Up with Parameter Actions

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Twice recently I've used parameter actions to create a single column drill down and drill up to mimic a hierarchy. 

  1. HR Analytics KPI Dashboard (Viz • Blog post)
  2. Makeover Monday Week 46 (Viz • Blog post)

Many of the examples of drill down you've probably seen so far use either set actions or parameter actions to create an additional column. The drawback is that you end up with an extra column that only has values when you drill down.

In this example, I show you how to use only ONE column to mimic drill down / drill up functionality. In total, it requires 2 parameters, 4 calculate fields, and 2 parameter actions. I find this method much more intuitive to the user. 

Let me know what you think or how you put it into practice. Enjoy!

November 16, 2020

#MakeoverMonday Week 46: The Growth of Internet Ad Spend - 2020 vs 2012

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Thanks for attending #WatchMeViz (link) for #MakeoverMonday Week 46. I enjoy the commentary and ideas you provide along the way. I hope you're learning something as well.

The topic this week was the switch in advertising revenue to the internet.

In the video, I first reviewed the initial visualization and talked about what works and what does. I then iterated through 17 different methods for visualizing the data, before settling on the one below which was inspired by Ellen Blackburn's viz about eligible free school meals and educational attainment (link)


  1. Data Set -
  2. Chart Guide -

Click on the image below for the interactive version.

Visualizing a Profit & Loss Statement with KPI Cards

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Data HAS to be consumed quickly to be understood and to make quick decisions. A "typical" profit and loss statement is on a spreadsheet. However, spreadsheets are notorious for (1) errors and (2) being very difficult to spot areas of concern.

That's where dashboards come into play. Back in July 2017 I proposed a new way to visualize a Profit & Loss Statement (P&L). The dashboard has been very well received and put into practice at many organizations. They've reported back to me how useful it has been. 

But then I got thinking about an even easier way to visualize the data. I felt like the previous version was a bit chart heavy. So, while I've been creating templates for other areas of a business (HR, Social Media, Customer Service), I decided to also focus on a new version of a P&L statement with KPIs. This dashboard is based on a Finance Dashboard example from Excel Dashboard School.

You can download the data I used to build this template here. Click on the image below to interact with and download the workbook.

November 12, 2020

How I Use Layout Containers (Part 2) - HR Analytics KPI Dashboard

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In this second live stream demonstration of how to effectively use layout containers, I got into an ever so slightly more complex use case, particularly with the header section and how to use shading and padding. Check out the first video and dashboard about social media KPIs here.

The dashboard being rebuilt is based on data from this Excel dashboard -

I started by building a wireframe to show how I would use each container.

Click on the image below the video (or here) for the interactive version. You can then download it from Tableau Public and rebuild it yourself. Enjoy!

November 10, 2020

How I Use Layout Containers (Part 1) - Social Media KPI Dashboard

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Layout containers are super useful, if you understand the concept for how to use them. In this livestream, I build a simple KPI dashboard of social media metrics.

The dashboard being rebuilt is based on this Excel dashboard -

I started by building a wireframe to show how I would use each container.

From there, I started constructing the dashboard. If you want to follow along, you can download the data here.

The link to the video below by Curtis Harris was a game changer for me as to how I understood Tiled vs. Floating. I can't recommend it enough. It's a big influence on every dashboard I create.


1. Things I Know About Tableau Layout Containers by Curtis Harris -
2. Practice: Workout Wednesday 2018 Week 51 -

Click on the image below the video for the interactive version.

#TableauTipTuesday: How to Reorder a Stacked Bar Chart with Set Actions

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One of the drawbacks of stacked bar chart is that it can be difficult to see the contribution to the total for any sections of the bar except the bottom. In this tip, I show you how to click on any portion of a bar to move it to the bottom of the stacked bar chart, thus making it easier to understand its contribution.

November 9, 2020

#MakeoverMonday Week 45 - Global Share of Nintendo Switch Software & Hardware Sales

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For #MakeoverMonday week 45, we were analyzing the software and hardware units sold across several regions, as defined by Nintendo itself. The data was pretty simple. I started by doing some basic data prep to simplify the names of the fields and to pivot the data to make it easier to compare the years.

In this video, I will first review the initial visualization and talk about what works and what does. I then iterate through several methods for visualizing the data, hoping to find one that works well with this data set. With feedback from the viewers, I was able to create a bar chart that compares the percentage of global units sold of software vs. hardware for Nintendo.

I showed several methods for visualizing the data:

  1. Line charts (several versions)
  2. Stacked bar chart
  3. Side-by-Side Bar
  4. Tables
  5. Scatter plot
  6. Connected scatterplot


  1. Data Set -
  2. Final visualization -
  3. Tableau Color Palette Generator -
  4. Colors from Image Tool -
  5. ASCII character reference -

Dashboard Templates - Example 1: Customer Service Dashboard

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As part of the training at The Data School, we're often tasked by clients to build industry specific dashboards and/or dashboards that can be used as templates for their organization. Of course what the client can ask for is often much more broad. From a dashboarding perspective, we tend to have the freedom to create what we think works best for their data. This them, in turn, helps create a sort of "brand" for their dashboards internally.

That got me thinking about common use cases for dashboards, dashboards that would likely span industries and companies and could serve as templates for others. In this series, I'll be posting templates that I have been building based on the data and sample dashboards from Excel Dashboard School

Let me make it clear that I am in no way criticizing the work they have created. My intent is to build an alternative method for displaying the data as a template in Tableau. The data and templates they have provided are the starting point for my work. I want to thank them for being so kind and sharing their work.


Customer Service Dashboard


  1. Dashboard Overview -
  2. Data and Interactive Dashboard -


Click here for the interactive version.

November 3, 2020

How to Create a Floating Bar Chart

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Floating bar charts are similar to Gantt bar charts, except they don't use dates or duration for the length of the bar. In this video, I show you how to use floating bar charts for comparing metrics.

Example 1 - Comparing mental health syndromes between women and men

Example 2 - Comparing year over year sales

Data Sources:

  1. Mental Health Symptoms -
  2. Superstore 2020.3 -

November 2, 2020

#MakeoverMonday Week 44 - Where do women have more access to the internet and mobile phones than men?

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#MakeoverMonday week 44 is another #Viz5 initiative. The topic this week is access to the internet and mobile phones by gender and country.

First, sorry about the video cutting out at the very end. My mistake.

In this video, I first review the initial visualization and talk about what works and what does. In the end, I went with a quadrant chart, which is a scatter plot with broken up into four quadrants. The viz focuses on only two of the quadrants to highlight the significant difference in the number of countries where women have more access to men for both technologies vs. the opposite.

I showed several methods for visualizing the data:

  1. Side-by-Side Bar
  2. Bar in bar
  3. Bar Graph vs. Reference Line
  4. Barbell
  5. Peas in a pod
  6. Floating bar chart
  7. Slope graph (terrible choice)
  8. Ranked slope graph (even worse choice)
  9. Histograms
  10. Box plot
  11. Scatter plot


  1. Final workbook - LINK
  2. Data set -
  3. Country and region information (Be careful joining this as some country names don't match. You'll want to using data blending and alias the country names to match.) -
  4. Chart Guide -
  5. Interactive chart chooser -