VizWiz

The Workout Wednesday 2020 Week 53 challenge required extensive knowledge of containers in Tableau. Containers can be quite the mystery! It's taken me years to grasp them.

In this webinar, I showed what I've learned about containers, how to complete the Workout Wednesday challenge, and how you can master containers.

Resources:

1. Workout Wednesday Challenge - http://www.workout-wednesday.com/2020w53/
2. Data source (Superstore 2020.3) - https://data.world/vizwiz/superstore-20203
3. Workbook - http://bit.ly/WOW2020WEEK53

It's Valentine's Day and what's the point? In this #WatchMeViz session, I explored lots of visualization before settling on a viz that was basically the same as the original with the exception of the colors, title and interactivity. Enjoy!

Wow! What a fun #WatchMeViz that was! I iterated through 16 charts and then when the idea solidified, there was some great conversation and feedback on the chat to help me get to the end. I find survey responses quite difficult to visualize, so instead of getting frustrated, I thought about all of the ways I can compare data to see if anything would work.

Most importantly, thank you to all of your on the live chat. It makes a huge difference to me and I love getting your feedback and questions along the way. You make me better. You can find the final visualization below the video.

Trellis charts are a version of a small multiples chart that organizes the dimensions in the view across a grid. In this tip, I show you how to create a trellis chart that will work even when you are missing data.

Trellis / Panel Chart Calculations

//Columns
(index()-1)%(round(sqrt(size())))

//Rows
int( (index()-1)/(round(sqrt(size()))))

Steps

1. Create the column and row calcs
2. Create a custom date
3. Place custom date on columns, measure on rows and dimension on detail
4. Place column on columns, row on rows, and custom date on detail
5. Ensure dimension is above date on detail shelf
6. Change custom date on columns to ATTR
7. Configure table calcs
1. Check both the Dimension and the date field date in order
2. Ensure the dimension is above the date field in the Specific Dimensions section
3. Set "At the level" to the dimension

ORIGINAL CHART

WHAT WORKS WELL?

WHAT COULD BE IMPROVED?

MY VERSION

What could be improved?

Final Dashboard (click to interact)

This week's viz to makeover reminded me of a very similar (almost exactly the same) data set that we used for Makeover Monday in 2016. Here's the original viz:

Honestly, it's absolutely fantastic. It's one of the best examples of scrollytelling I've every seen. Check out the original here. 

Since I had explored this data set before, I know pretty quickly what I wanted to do. During Watch Me Viz, I went ahead through many iterations of working with time series data; they're all available in the workbook. Watch the video here (or below).

Here's my final viz. Each dot represents a month and the line represents at 10-year moving average. Each mark is compared to the 1951-1980 median. Click on the image to view the viz on Tableau Public.

 What is a Candlestick Chart?

A candlestick chart is a style of financial chart used to describe price movements of a security, derivative, or currency. Each "candlestick" typically shows one day, thus a one-month chart may show the 20 trading days as 20 candlesticks. Candlestick charts can also be built using intervals shorter or longer than one day.

It is similar to a bar chart in that each candlestick represents all four important pieces of information for that day: open and close in the thick body; high and low in the “candle wick”. Being densely packed with information, it tends to represent trading patterns over short periods of time, often a few days or a few trading sessions.  

~ Source: Wikipedia

In this tutorial, I show you how to build a candlestick chart in Tableau. They are built as Gantt charts with a couple of simple calculations. Follow along by downloading the data set here. 

I must admit that I REALLY struggled with this data set. I could have easily just compared males vs. females by country and year, but it seems we've been doing that over and over again. I looked to explore the data and thought a connected scatterplot would look nice, but it didn't.

Fortunately Michel Mahon proposed looking at the lag between the year of HIV infection rate and death. Morbid yet interesting analysis. It took me a while to get the calcs working; I'd recommend you build your view as a table to verify the calcs when you're not sure if they're correct. In the end, thanks to Michel's suggestion, I created a slope graph that compares the lag in years for both men and women.

As the documentation suggested, women die more quickly than men.

Below are both my visualization and the Watch Me Viz session on YouTube. Thanks for tuning in!

Back in March 2020 when COVID lockdown started in the UK, the streets were amazingly empty, the air got fresher and I saw more and more people outside. You could hear birds chirping on streets you never would have before. And we could ride our bikes right down the middle of the road since there were no cars. The lack of cars was glorious! (COVID isn't of course).

For 2021, #MakeoverMonday gets started with a simple graphic that compares pedestrian and bicycle counter stats for 2019 and 2020 at 31 counters across America. The data is collected by the Rails to Trails Conservancy, and you can learn more about the data here. 

ORIGINAL VISUALIZATION

Dot matrix charts are useful for visualizing the distribution and frequency of discrete data. They help you understand the scale and proportion. The purchase is to understand how many, not how much. 

In this example, I'm using two colors to distinguish new vs. used cars. However, if you have only one variable or category, then stick to one color.

Resources:

1. Workbook - https://bit.ly/DotMatrixPlot
2. Data set - https://data.world/vizwiz/car-sales-mock-data