Showing posts with label employment. Show all posts
August 24, 2021
#MakeoverMonday 2021 Week 34 - Entry-Level Jobs on LinkedIn Requiring 3+ Years Of Experience
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bar chart
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WatchMeViz
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In this week's Watch Me Viz, I tried something new. I used both Tableau and Power BI. I focused on methods for rebuilding the original chart. Unfortunately, the PBI demo didn't go so well. That wasn't any fault of PBI, but rather my laptop, as I have to run Parallels on my Mac in order to run PBI and I was also live streaming. Either way, I hope you find it useful.
May 16, 2017
Makeover Monday: Female vs Male Youth Employment in Latin America & Caribbean Countries
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unemployment
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Today, I had a few spare minutes and knew that Eva really wanted me to create something with the full data set she created for #VizForSocialGood. Also, I was really surprised at the remarkably few slope graphs this week. This is a great data set for slope graphs, whose main purpose is comparing two points.
So, here is my second Makeover Monday this week. Special thanks to Eva for feedback on my iterations. In this viz, I wanted to compare the unemployment percentage for 15-24 year olds by country. Perfect use case for a slope graph...and my 500th Tableau Public viz!! I wonder who has more??
May 15, 2017
Makeover Monday: What jobs do young people in Latin America hold?
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Cole Nussbaumer
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donut chart
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employment
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jobs
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youth
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For Makeover Monday, this week is a collaboration with #VizForSocialGood and Inter-American Development Bank. It's always a special day when you can make an impact. Eva and I are also hosting a Brightalk webinar about Makeover Monday at 4pm BST today. Join us if you have a chance.
This week's makeover is a donut chart that shows how many youths in Latin America and the Caribbean are employed in different jobs.
What works?
- Using a question for the title
- People immediately understand how to read a donut chart
- Sectors are sorted from largest to smallest
- Nice tooltips
What could be improved?
- Why are mining and basic services combined?
- The middle of the donut is wasted.
- The data doesn't tell an effective story.
- A bar chart would make comparing the sizes easier than a donut chart.
- Too many colors
For my viz, I decided to start by recreating the original in Tableau and then using story points to walk through each step of my makeover. I recalled this great post by Cole Nussbaumer in which she presents alternatives to pie charts. In particular I really like her big number viz, so I did my best to emulate that style. Simple and more effective that the donut chart for me.
August 10, 2015
Makeover Monday: 12 Ways to Visualize the Gender Gap of Federal Workers
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dot plot
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Jon Schwabish
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nelson davis
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slope graph
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wages
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Good friend Nelson Davis provided another great makeover example for this week. It started with this tweet from Jon Schwabish:
What would you call these charts? Not pie charts...maybe "spilt pie charts"? | From http://t.co/jZZKbLnAl0 pic.twitter.com/cyqwtp8UYz
— Jon Schwabish (@jschwabish) August 5, 2015
As I was thinking about this makeover, I couldn't settle on a single best way to visualize this data. I did know, though, that these moons/pies/donuts/dots needed to communicate more effectively. I've come up with 12 alternatives, each of which works way better than the original. The reason there are 12 is because there are multiple ways to display the dimensions based on the story you want to emphasize. And yes, I could have come up with another 12.
Special thanks for Carl Allchin for his feedback and help with the text on the tabs in the story points.
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