Data Viz Done Right

June 23, 2021

How to Move All Column Labels to the Top of a Chart

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A very common frustration I hear is that Tableau can't move headers from the bottom of a chart to the top if there's more than one dimension. 

In this tip, I'm going to show you how simple it is to move all discrete column labels to the top of a chart. Please keep in mind that this is a workbook level setting. Therefore, all charts in the workbook will show all discrete headers at the top. 

Power BI - #WorkoutWednesday 2020 Week 53 - Executive Sales Dashboard

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Today I've been teaching DS23 a bit of PBI. We teach PBI as more of awareness than expertise. I need them to understand how it work in the event it comes up while on their placements.

After creating some charts with Superstore and showing them how easy it is to download data from the web, I gave them (and myself) the task of completing Workout Wednesday 2020 Week 53. We had established the basics of building the charts so it was pretty simple, notwithstanding the inevitable formatting time (this is a lot of work in Tableau too). 

Overall, I found this particular WW pretty simple with PBI. Give it a shot!

June 22, 2021

#MakeoverMonday 2021 Week 25 - Stop & Search in England & Wales

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Tough topic this week, stop & search by race. What really stuck out to me is how much more likely anyone with black ethnicity of any type is to be stopped and searched. No one can tell me there isn't racism in the UK.

  1. Final Viz (and below)
  2. Data Set
  3. How to Create a Trellis Chart
  4. Data Viz Catalogue

June 14, 2021

#MakeoverMonday 2021 Week 24: Which States Have the Highest Average Student Loans?

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If you watch this week's #WatchMeViz (below), you'll get a good look at how I use containers to create a dashboard. I didn't iterate very much this week, as far as the number of charts is concerned, but I did mess around way too long when trying to create a hex inside of a hex map. HINT: It turned out terrible.

  1. Final workbook
  2. U.S. Hexmap Shapefile (credit: Joshua Milligan)

June 8, 2021

How to Create a Dot Strip Plot

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Dot strip plots are a space-efficient method of laying out ranks across multiple categories. They are useful for showing the distribution of small data sets. For larger data sets, a histogram would be a more effective visualization.

In a dot strip plot, the dots placed in order on a strip and typically include a reference line for either the median or the average. My default is to use median reference lines as these are better for reducing the impact of outliers. 

In this example, I show you how to:

  1. Create a dot strip plot showing the median sale by model and date for each car make
  2. Include a reference band from to lower to upper quartile to make it easier to see the outliers in the data
  3. Color the marks that are above or below the median

Download the sample data used in the tutorial here.

June 7, 2021

#MakeoverMonday 2021 Week 23: The Percentage of Never Married is on the Rise

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This week I iterated through 12 charts and a dashboard in 50 minutes. Once again, I ended up with a bar chart. They're rarely going to let you down. The only other bit I added was the thinner bar showing the change from 2006 to 2016.

  1. Final Viz (and below)
  2. Preferences file (all of my custom color palettes)
  3. How to Create a Combination Bar Chart & Candlestick Chart 

June 1, 2021

How to Calculate the Most Frequent Value of a Measure

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In this tip, I show you how to use both a level of detail expression and a table calculation to compute the most frequent value in a measure. 

First, I show you how to return this as a histogram as well as a single number.

By the end of this tip you will be able to calculate the most frequent quantity ordered. This same process could be used, for example, to compute the most frequent discount. 

May 31, 2021

#MakeoverMonday 2021 Week 22: The Plastic Waste Makers Index

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This week I iterated through 18 charts and 3 dashboards. To be honest, I think a bar chart was definitely the best way to represent the data, but I wanted to do something different. I'm not convinced the scatterplot works.

May 25, 2021

How to Create a Marginal Histogram

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Marginal histograms are a great choice when you want to display your data at different levels of aggregation in a single view. 

You can think of a marginal histogram as a heatmap with a histogram to the side and the top of the heatmap. Each graph provides a frequency distribution. 

In this example, I'm going to show you how to create a marginal histogram that displays a frequency distribution of the number of taxi rides by weekday and hour for January 2020 in NYC. 

Download the data here.

May 24, 2021

#MakeoverMonday 2021 Week 21 - How are wildlife populations changing?

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My Makeover Monday this week is very similar to the original other than I converted it to a diverging bar chart. Check out #WatchMeViz and the final visualization below. I iterated through 10 charts in about 45 minutes.

May 20, 2021

How to Show and Hide Underlying Data with a Set Action

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In this tip, I show you how to use a set action to drill down into the underlying data behind a mark. This example uses a dot plot to go from sales at the category level to then show each underlying sale.

I first saw this technique demonstrated by Lindsey Poulter; I've extended it to include jittering.

May 19, 2021

#WOW2021 Week 20: Can you compare Same Day to a Selected Date?

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Wow! This workout will really test your knowledge of table calcs. The challenge comes from Lorna; view the requirements here.

The main purpose of this challenge is to get familiar with dates and parameters. Fortunately, every Wednesday I host what we call "Wise Up Wednesday" during lunch for my colleagues at The Information Lab and The Data School. We needed all of our brain power for this one. For us, the toughest part wasn't writing the calculations themselves. Rather, it was the logic required for the calculations.

From Lorna:

What if you want to compare a date you choose to the same DAY. For example, Tuesday 18th May 2021, would compare to Tuesday 19th May 2020 for the previous year, and Tuesday 20th April for the previous month. The reason you would want to do this is to compare the Tuesday to Tuesday.

This is where the logic gets tricky. We approached the solution by taking one version at a time, meaning we started by creating the calcs for the same day last year before we went onto the other two scenarios.

We got the in the end. I'd recommend building everything as a table, then change it into a chart later. It's much easier to follow what you calcs are doing.

Good luck! Here's our solution:

May 17, 2021

#MakeoverMonday Week 20 - Humans vs Animals

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Check out this week's #WatchMeViz as I look at what men and women think about fighting an animal unarmed. I iterated through 17 vizzes in 60 minutes that show how to compare two measures.



Designing for Mobile First - Sample Mobile Sales Dashboard

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Last week, I was teaching DS23 about mobile design. We reviewed the pros and cons, what to think about from a user and usability perspective, how to make the most important information easy to understand, etc.

We then picked an image of a mobile dashboard we found on the internet and worked together to rebuild it. We started by creating a default dashboard, then looking at what Tableau's Device Designer would do to it.

We then decided to create a mobile-only dashboard as our use case what executives on the go. This also gave us a great excuse to practice using containers.


May 12, 2021

How to Create a Time Series Drilldown with a Set Action

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In this video, I show you how to use a set action to drill down from a monthly view to a daily view. This technique will work with any date drill down, whether it be year to quarter, year to month, quarter to day, etc.

May 11, 2021

Threshold Analysis - Level of Detail Expressions vs. Table Calculations

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DS22 is nearing the end of their training and today was a bit of a refresher. One of the questions I wanted them to answer was how many sub-categories in each region had sales above $40,000?

We then expanded that to include (1) the sales for those sub-categories and (2) the % of sales those sub-categories make up of the region sales. They were to complete this using LODs.

As they worked on the task, I thought that this, for sure, could be done with table calculations. This is perfect for the Data School Gym. 

If you know me, you know I love table calculations. And if you know Lorna Brown, you'll know she HATES table calculations. So this is your Data School Gym challenge Lorna.

Of course, everyone is welcome at the Data School Gym. It's actually not that hard and is a good way to help you learn about LODs vs. table calcs.

I'm not too fussed about making it look exactly the same. The point is to see if you can create the identical tables. Enjoy!

May 10, 2021

#MakeoverMonday 2021 Week 19 - The Cost of 1GB of Mobile Data in Every Country

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This was my first time making a World Tile Map (thanks for the template to Neil Richards). Download the template here

In my version, you can view the cost overall or you can compare to a selected country. The title will update automatically depending on if you've selected a country or not.



May 4, 2021

How to Create a Layered Hex Map with a Spatial File

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In this tip, I show you how to use a spatial file to overlap hexagons on a map. This technique is much simpler, looks better, and is easier to maintain.

Typically when you want to create an overlapping hex map, you will use a template that has x/y coordinates for the rows and columns, hex shapes, then try to pack them together until they look just right. But then you put them into a dashboard and the sizes need to be adjusted again. What a pain!

Watch this tip to see the simple way to create layered hex maps.

RESOURCE: Hex map template via Joshua Milligan here

May 3, 2021

#MakeoverMonday 2021 Week 18 - Realized vs. Granted Compensation for CEOs

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In this session I first reviewed the original visualization, then went into data discovery and analysis before finishing with a new visualization.  Watch the video and interaction with the visualization below.

Charts created: 
  1. Line Chart 
  2. Stepped Lines 
  3. Variance to baseline 
  4. Win/Loss chart 
  5. Comet Chart 
  6. Gantt Chart 
  7. Bar chart w/ reference line 
  8. Connected scatter plot 
  9. Slope Graph 
  10. Circle Timeline 
  11. Heatmap 

  1. Data Set - 
  2. Chart chooser -

April 30, 2021

#WOW2021 Week 15 - Workout Wednesday Website Analytics

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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.