#tidytuesday 2025-02-10 looking at the 2026 Winter Olympics schedule. Shown below are the concurrent Olympic events binned by hour.
#RStats #ggplot #ggplot2 #dataviz
For #tidytuesday week 2026-02-03 looking at an edible plants dataset, I was curious about relationship between sun and water requirements; I thought the more sun, the more water. However most edible plants like a lot of sun, but only a moderate amount of water.
#RStats #ggplot2 #ggplot #dataviz
#tidytuesday week 2026-01-27: Brazilian companies. Not an economy or finance person but wanted to try my hand at a Lorenz curve and a ridgeline plot to show some of the data.
#RStats #ggplot2 #ggplot #dataviz #brazil
dplyr 1.2.0 is out now and we are SO excited!
- `filter_out()` for dropping rows
- `recode_values()`, `replace_values()`, and `replace_when()` that join `case_when()` as a complete family of recoding/replacing tools
These are huge quality of life wins for #rstats!
tidyverse.org/blog/2026/02...
Oh Jin 🫂
Time is a healer. Hang in there buddy
Not all departments are listed, and departments are still coming up with number of positions to eliminate, so this more or less just a snapshot.
A cleaner version just showing numbers of employees being laid off.
The Government of Canada recently undertook measures to eliminate positions to save money (Comprehensive Expenditure Review). Using data they released, I showed the number and percentages of employees to be eliminated either by attrition or by layoff.
#rstats #tidyverse #ggplot #ggplot2 #dataviz
Side note, I did not know APOD existed prior and I will be bookmarking!! Super cool.
Made with #ggplot and #ggside. Was looking for an excuse to mess around with ggside and I feel like it fits nicely on a heat map.
For this week's #tidytuesday, in reading some of the #APOD posts, I noticed the Sun was mentioned a lot. I was curious to see just how much the Sun is mentioned. Turns out, the Sun is mentioned in 1/3rd of posts. Increasing over the years, but relatively stable month-to-month.
#RStats
For last week's #tidytuesday, I was curious about language diversity among prominent natively spoken languages in Africa. #Cameroon has the highest number of natively spoken languages, which is unsurprising given their vast (250-600 estimated) language diversity overall.
#RStats #Tidyverse
Bit late on the last #tidytuesday of 2025 looking at Christmas novels. I created a word map using the top 100 non stop words and a word sentiment tree map using the nrc lexicon. Positivity, joy and trust appear in higher proportion than other text datasets I've looked at!
#RStats
Did anyone else get absolutely destroyed by this year’s COVID/Flu vaccines?
I once had an interview where they asked me all questions that would have been answered by my resume. It was so strange.
Yes
I feel bad that I randomly stopped my series. I got sick and then life happened :(
We need this asap
Yes
My backpacking itinerary
JIN LOL
Yeah, there are some flaws in the original dataset. The author of the data had to clean **very** messy data and there will be some issues as a result. Also, bear in mind these are all publicly submitted sightings.
Yes, I recognize the colour theme is abysmal by conventional standards but I really wanted it to be alien / UFO themed.
👽🛸 Spooktober: Data After Dark - October 8
Today is part one of a multi-part segment on a UFO sighting dataset.
For part 1, I created an interactive Shiny app to explore the data. Map points are clickable!
colewb.shinyapps.io/alien-atlas/
#DataViz #R #Shiny #ggplot2 #RStats #Alien #UFO
🎃👻 Spooktober: Data After Dark - October 7
Today's plot shows inflation adjusted U.S. Halloween spending across 4 categories from 2005 to 2025 (2025 anticipated).
#Spooktober #DataViz #R #ggplot2 #RStats #Tidyverse #Retail #Halloween
To get this data, I scraped all store locations off their website and used {stringdist} and {tidygeocoder} to geo-tag each location to allow them to be mapped. Full scraping and cleaning script can be found here: github.com/colebaril/da...
Spirit Halloween’s reach spans across North America, with the highest density of stores in the eastern U.S. and major metropolitan regions. Its presence thins in rural and northern areas, reflecting population distribution and retail availability.
A map of North America showing the distribution of Spirit Halloween stores using purple circles sized by store count. The highest concentrations appear along the eastern United States, particularly around the Great Lakes, the Northeast, and the southeastern states. Dense clusters also appear around major U.S. cities such as Los Angeles, Dallas, and Chicago, while western Canada has smaller clusters near Vancouver, Calgary, and Edmonton. Northern Canada, the northern U.S. plains, and remote regions show few or no stores. The map highlights how Spirit Halloween stores are most common in densely populated urban and suburban areas.
🎃👻 Spooktober: Data After Dark - October 6
Spirit Halloween stores seem to pop up almost everywhere out of nowhere. I wanted to see just how ubiquitous these temporary shops are across North America.
#Spooktober #DataViz #R #ggplot2 #RStats #Tidyverse #SpiritHalloween #Retail #Halloween
