# VizWiz

Data Viz Done Right

## #MakeoverMonday Week 31 - Bicycle Collisions in London

This week's data set was pretty straightforward. During #WatchMeViz I iterated through some maps, including joining to spatial files for London, and also lots of time series charts. Below are links to the resources, the video, and the final viz.

Resources:

## #MakeoverMonday 2021 Week 30 - America's Racial Breakdown by State

Makeover Monday week 30 looked at this viz from Visual Capitalist showing the percentage of each race in each State in America.

In the video below, you'll see my recreate the tiled treemap before creating a tiled bar chart. Thanks for watching!

## How to Compare to the Prior N Months Using the IN Function

This tip comes from an exercise I did alongside DS21 to find different ways to compare to the prior 3 months. Owen Barnes came up with the method using the IN function upon which this tip is based.

Check out how we did this same exercise with a table calculation and a level of detail expression on Owen's blog here.

## #MakeoverMonday 2021 Week 29 - Non-Whites Are At Higher Risk of Dying From COVID-19

Another COVID-19 data set this week and a great visualization that shows how much more likely ethnic minorities in the UK are to die from COVID.

In the video, I worked through rebuilding the original viz since I liked it so much. Interact with the viz below the video.

## #MakeoverMonday 2021 Week 28 - COVID Vaccination Rates by Ethnicity and Age in England

How can ethnic groups be treated differently when it comes to the COVID vaccine? It's terrible! And this data from NHS England clearly demonstrates the racial divisions that exist in this country.

I'm not sure what happened during the recording, but it got split into two parts. Both are below.

Resources:

Thanks for tuning in! Interact with the viz by clicking on the image below or here.

## #WOW2021 Week 26 - Profitability With a Dual Axis Chart

Typically our Wise Up Wednesday crew do these together but today, I was on my own In this video, I take you through how I completed Workout Wednesday 2021 week 26. It's a bit of a ramble since I started from scratch, but I got there.

Video and solution below...

## How to Disable Sorting on a Worksheet

Let's say you have multiple metrics on a chart (not required) and you have sorted the chart in a specific way, for example by sales, and you want to prevent your users from sorting by something else.

It's quite simple! All you have to do is turn off the sort controls. In this short Tableau Tip, I show you how to do it. Enjoy!

## #MakeoverMonday Week 27 - If Only _____ Voted

This week's data set was one of the most interesting we've had for Makeover Monday. I found it fascinating to see some of the extreme polarization in the demographics of US voters in the 2020 election.

Resources:

2. Original Viz - https://bit.ly/3qQGsAo
3. How to Create a Trellis Chart - https://www.vizwiz.com/2021/02/trellis-chart.html
4. The Data Visualisation Catalogue - https://datavizcatalogue.com/

The original was really good and I didn't particularly want to create a map. Instead, I wanted to visualize all of the demographics at the same time to see if any patterns emerged. I find them a bit hard to see in what I created, but when I know what I'm looking for (e.g., women vs. men) then the contrasts really stand out.

I create the heatmap the way I did for two reasons:

1. To see across each metric in order to identify consistent blue or red patterns for an entire demographic (e.g., early voting or urban).
2. To see if individual States always voted for Biden or Trump irrespective of the demographic (e.g., CA, MA, MD for Biden or KS, KY, LA for Trump).

There are parts of Watch Me Viz you can skip, like early on when I build some maps and try to join the data together (unsuccessfully) or when I change the data to Excel format.

Thanks for tuning in! Interact with the viz by clicking on the image below or here.

## #WOW2021 Week 22 - Can You Structure the Unstructured?

Week 22 was quite the tricky challenge. The idea itself is quite simple, but you had to (1) use REGEX to get the number of bedrooms (thanks to Sylvie Imbert at The Data School for her help!) and (2) know how to create bins without using the BIN function.

Unless you've done it before, you likely will get quite stuck figuring out how to create the bins because it requires a hidden function...SYS_NUMBIN. I won't go into detail here; you can read more on Jeffrey Shaffer's blog here.

Check out how we did it by clicking on the image below.

## Sample KPI Dashboard

This week at The Data School, I was teaching DS24 about dashboard best practices and how to effectively use containers. We picked a visualization from the wild (this one by Ryan Sleeper) as an example for us to rebuild and to learn about effective use of containers.

1. Mastering Containers (Part 1)
2. Mastering Containers (Part 2)

To see how we build the example below, feel free to download it and pick it apart. However, if you really want to learn how to build something like this, try to rebuild it based on the image alone. The videos above will definitely help.

Thank you Ryan for the inspiration!

## #MakeoverMonday Week 26 - How Popular Is Your Birthday?

The original visualization this week was superb. I don't think what I created was better, but I did come up with a slightly different take and I showed how to build a marginal histogram. I also failed trying to create a starburst chart (I'm going to give it another go).

Resources:

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

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

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!

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

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.

Resources:

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

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.

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

## How to Create a Dot Strip Plot

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

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

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.

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

## How to Calculate the Most Frequent Value of a Measure

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.

## #MakeoverMonday 2021 Week 22: The Plastic Waste Makers Index

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.

## How to Create a Marginal Histogram

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.

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

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.

## How to Show and Hide Underlying Data with a Set Action

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.

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

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:

## #MakeoverMonday Week 20 - Humans vs Animals

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.