I struggled mightily with this week's #MakeoverMonday. My goals was to replicate the original visualization by Bloomberg.

I knew I need to create path to connect the US at the center to each country.

I wanted to make the US the center of the of the map.

• I overthought the data prep.
• I forgot how to create the paths.
• I couldn't get the math right to offset the longitude.

The coloring and labeling was straightforward for me.

Adding the US as a circle in the middle was pretty simple.

• I looked at a previous visualization I created using paths.

• I opened the workbook and the data to see the configuration.
• I replicated that set up by adding a second set of records to the data set.
• Viewers on the livestream helped me figure out the math to offset the longitude.

The simplest way to explain the location of each country is to think of the lat/lon for the US as 0,0. Then you compare that to the lat/lon for every other country to create the offset.

I got there in the end. What do you think? Was the juice worth the squeeze?

Click the image below to access the viz. 

That's a wrap. Watch Me Viz has retired, for good. 

This week's data was about the performance of all of the WMV livestreams. There was some incredible viewer participation, which ultimately led to this viz that explains why WMV should quietly disappear.

Check out the livestream below.

Catch up on my latest #MakeoverMonday Watch Me Viz. I dive into a step-by-step redesign of Visual Capitalists "What are Retail Investors Interested in Buying in 2023?" chart. 

Starting with an overview of the original visualization, I review the gaps and areas for improvement. Why was a makeover necessary, and what potential did we see? 

The livestream walks you through the entire transformation process, from the initial critique to the final touches. 

Expect to uncover advanced design techniques and gain insights into the strategic thought process behind each decision. 

Whether you're an aspiring designer or a seasoned data analyst, this step-by-step makeover promises valuable takeaways for all. 

How many people power the Forbes Cloud 100? Is there a correlation between company rank and employee size? Have they expanded or contracted.

Learn how to build 28 charts in 60 minutes that compare two years.

Join me for live analysis of Zoosk's recent survey, covering 8,793 members' dating drink preferences! 

In this livestream, I'll break down the responses across 7 different drink types, comparing the preferences between men and women. 

Is there a gender divide when it comes to what people choose to drink on dates?  

I'll explore this question and more. 

At the global level, how has crop production changed over the last fifty years? 

In this Watch Me Viz live stream, I analyzed how the yield and land use of producing cereal has changed over the last 50 years.

I really liked the original visualization, so I rebuilt it in Tableau. I learned how to use dynamic zone visibility, layout containers, and more. Check it out.

Resources:

1. Data - https://data.world/makeovermonday/2023w24

2. Final Dashboard - https://tabsoft.co/3P3Sdl3

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Watch Me Viz is a weekly live stream where I help people become better at #Tableau, #PowerBI and data analysis. I show how I take an existing visualization, critique it, analyze the data, and build several visualizations all the while looking for a "better" visualization than the original.

If you are considering participating in Makeover Monday, you can get started by downloading data sets from the Makeover Monday website. I promise you'll become better at data analysis and data visualization by practicing every week.

Data sets - https://www.makeovermonday.co.uk/data/

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More Watch Me Viz - https://bit.ly/WatchMeViz2023

This week we explored the cost of 20g of protein in various foods. During Watch Me Viz, I showed how to create toggles to allow the user to filter by vegan and vegetarian foods. I did this with parameter actions; if you want to learn more, watch the video below.

In the end, though, my fancy filtering with parameter actions didn't quite work out. I hadn't account for the option when the user might want to look at all foods. So I ended up using basic filtering. I overcooked the whole process, but I bet you'll learn something anyway.

I then went through the entire dashboard design process using containers, padding, shading and more. Check that out if you're interested in learning how to use layout contains.

Here's the #WatchMeViz recording, followed by the interactive viz. Enjoy and thanks for watching!

2023 is here and #MakeoverMonday will be here the entire you to help you continue to learn and improve. Come on the journey with us each week. Build your portfolio. Showcase your skills. You just might get that job you've been seeking. It's happened, a lot, by participating every week.

For week 1, we were analyzing greenhouse gases in the atmosphere from 1979-2021. The original visualization is quite simple.

We have CO2 and total gases on the left axis and the variance to 1990 on the right. Overall, the chart is pretty easy to read, with the exception of knowing that the red line is always compared to the 1990 value. That definitely needs to be more clear. It's also missing a title, so without the website it is posted on, you wouldn't necessarily know what it's about.

For my viz, I started by reproducing the original, but it doesn't look as good because the data we have starts at 1979. So you miss the big upward curve. From there, I focused primarily on making good looking sparklines that show comparisons with a parameter action. I also showed how to create an "area chart" with multiple colors. I'm going to create a tip video for it; I like how it turned out.

Here's the livestream and below is the visualization for you to interact with. The viz does not render properly on Tableau Public, but hopefully you get the idea.

I hope you continue to join me throughout the year so that we can learn together.

Have a wonderful 2023!

Quite the interesting topic this week. I get an email from The Economist regularly and there was an article about the wholesale price of cocaine. That led me down a rabbit whole and I found the data, but also for heroin and also for retail prices.

On Watch Me Viz, I stuck with simple lines charts that compared the price for a country to the overall price for all of the countries in the data set. I allow the user to choose a drug and a country.

I then wanted to show how to Dynamic Zone Visibility feature works (if you haven't seen it, be sure to watch it back). In the end, a simple dashboard that compares the measures in two ways, allows for some filtering, looks good, and that's it.

Check out the dashboard below the video.