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#30DayChartChallenge
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#30DayChartChallenge - Day 28: Inclusion What's the opposite of inclusion? Exclusion and this chart compares the rate of adults at risk of poverty or social exclusion in the EU based on their country of birth. #rstats #dataviz
30 Days.
1 Dataset. 
It's the last day of the #30DayChartChallenge, and the final prompt is "National Geographic Theme" so here's my first and only map created for the challenge!
Made with #RStats
Colours inspired by National Geographic logo
{ggpattern} to use striped areas for missing data
It's almost the end of the #30DayChartChallenge and for the prompt of "Extraterrestrial", I decided to make a chart designed in the style of an extraterrestrial who has never heard of good data visualisation principles!
How many chart crimes can you spot? 
The Parkes Observatory is national heritage listed in Australia. Apparently "Australia was an international leader in the ground-breaking field of radio astronomy research in the post-World War II period".
It may have even helped CSIRO invent wifi!
Another #Quarto + #RStats + Observable combination for Day 27 of the #30DayChartChallenge
Two heatmaps to illustrate the prompt of "Noise" - unsorted heatmaps look like random noise, (sensibly) sorted heatmaps are more likely to reveal patterns!
I'm delighted to learn that the Queensland government measures the height and direction of waves along the coast.
They use it for things like planning construction, investigating erosion, emergency services during cyclone season, global wave monitoring and so on.
You can use it to plan surfing, fishing, and the like!
Catching up on Day 24 of the #30DayChartChallenge where the prompt is using data from the World Health Organization 
Tried an experimental way to visualise two variables, where lower values are better for both
Area shrinking towards zero indicates improvement
Think this would work better if there's a more natural scaling between two variables
#30DayChartChallenge Day25 Risk
Rates of poor mental health are increasing – especially among young people, raising concerns about impacts on their health and employment prospects.
Missing out on early job experience makes it harder to build skills, secure stable work and progress to better-paid roles – without action, this will become a major challenge for the next generation.
More in our Commission for Healthier Working Lives report 
https://www.health.org.uk/reports-and-analysis/reports/action-for-healthier-working-lives
To help stamp out trachoma, you can donate to Fred Hollows Foundation to treat it directly or donate to a charity that helps communities emerge from poverty and break the cycle of infection and re-infection.
For Day 23 of the #30DayChartChallenge, the prompt is "Log scale"
(Technically, this isn't actually a log scale but I wanted to play around with the idea of giving the more recent, more densely located data points more space)
I'm almost back on track with the #30DayChartChallenge with another trio of plots - this time all made from scratch in D3!
I learned how to: Make scatter plots, line charts, and area charts
Highlight and annotate specific data points
Fit Loess curves in D3
Down under, you can use the Southern Cross to tell time and direction.
Aboriginal Australians are among the world's first astronomers. The southern cross forms part of the Emu in the Sky, a dark constellation, which has featured in storytelling for thousands of years.
Making use of highlighting and annotations
For Day 20 of the #30DayChartChallenge and the prompt of "Urbanization", I used #Python to make a very abstract plot in the style of a city skyline silhouette! 
(Still using the income inequality data via Our World in Data)
Catching up on Day 16 of the #30DayChartChallenge with the prompt of "Negative"!
Waterfall chart made in #RStats
Doesn't feel as intuitive when decreases are a positive outcome
Needed a few hacky approaches to get the right layout
Continued thread
For day 2 of #30DayChartChallenge, I made an area chart in #rstats to show the increase in automobile crashes in Delaware (and the proportion in which alcohol was involved). It might be a stretch to call it a slope chart. :) #dataviz
Code: https://github.com/bardolater/30DayChartChallenge/blob/main/2025/02_Slope.r
When I decided to visualise the same dataset on income inequality for all 30 prompts of the #30DayChartChallenge, I wasn't sure how I'd manage to make the prompt of "Birds" fit with that data... 
But I managed to shoehorn some data about birds in there!
The result? A "correlation is not causation" / "dual axes are bad" plot in the style of Spurious Correlations made with #RStats!
For day 1 of #30DayChartChallenge, I made a quick waffle chart in #rstats from open data about automobile crashes in Delaware. As a #BikeTooter who commutes to work by #bike, I'm keenly interested in road safety.
Code: https://github.com/bardolater/30DayChartChallenge/blob/main/2025/01_Fractions.r
