## VizWiz

Launch, grow, and unlock your career in data

## #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.

## Designing for Mobile First - Sample Mobile Sales Dashboard

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.

Enjoy!

## How to Create a Time Series Drilldown with a Set Action

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.

## Threshold Analysis - Level of Detail Expressions vs. Table Calculations

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!

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

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.

## How to Create a Layered Hex Map with a Spatial File

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

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

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

Resources:
1. Data Set - https://data.world/makeovermonday/2021w18
2. Chart chooser - https://datavizproject.com/