Curator: @jonthegeek
https://DSLC.io welcomes you to week 14 of #TidyTuesday! We're exploring Timely and Effective Care by US State!
https://tidytues.day/2025/2025-04-08
https://www.visualcapitalist.com/mapped-emergency-room-visit-times-by-state/
Submit a dataset! https://github.com/rfordatascience/tidytuesday/blob/main/.github/CONTRIBUTING.md
```
library(tidyverse)
crossing(x=0:10, y=x) |>
mutate(dx = rnorm(n(), 0, (y/20)^1.5),
dy = rnorm(n(), 0, (y/20)^1.5)) |>
ggplot() +
geom_tile(aes(x=x+dx, y=y+dy, fill=y), colour='black',
lwd=2, width=1, height=1, alpha=0.8, show.legend=FALSE) +
scale_fill_gradient(high='#9f025e', low='#f9c929') +
scale_y_reverse() + theme_void()
```
#rstats #tidyverse #generativeart
Day 6 | Comparisons – Florence Nightingale (theme day) | #30DayChartChallenge. Visualization made with R using #tidyverse, #ggtext and #showtext. Data source: HDX - https://data.humdata.org/dataset/cod-ps-hnd.
"It is worth emphasizing that tinyplot requires only base R. It has zero recursive dependencies and we have been careful to keep its installation size down to a minimum."
That's my kind of package. Let's go Tinyverse!
New blog post on the Tidyverse blog: Learning the #tidyverse with the help of #ai tools #rstats
ggplot2 is the gold standard when it comes to data visualization.
The image in this post showcases examples of ggplot2 visualizations, demonstrating its versatility to create a wide range of plots with nearly limitless customization options.
Check out my online course, "Data Visualization in R Using ggplot2 & Friends," for a deeper dive into creating stunning plots with ggplot2.
More info: https://statisticsglobe.com/online-course-data-visualization-ggplot2-r
gganimate is a powerful extension for ggplot2 that transforms static visualizations into dynamic animations. By adding a time dimension, it allows you to illustrate trends, changes, and patterns in your data more effectively.
The attached animated visualization, which I created with gganimate, showcases a ranked bar chart of the top 3 countries for each year based on inflation since 1980.
More information: https://statisticsglobe.com/online-course-data-visualization-ggplot2-r
https://DSLC.io welcomes you to week 13 of #TidyTuesday! We're exploring Pokemon!
https://tidytues.day/2025/2025-04-01
https://medium.com/@hanahshih46/pokemon-data-visualization-and-analysis-with-r-60970c8e37f4
Submit a dataset! https://github.com/rfordatascience/tidytuesday/blob/main/.github/CONTRIBUTING.md
Understanding probability distributions is key to making informed decisions in statistics and data science. Probability distributions describe how the values of a variable are expected to behave, making them crucial for interpreting data and predicting outcomes.
The visualization shown in this post illustrates the distributions.
Further details: https://statisticsglobe.com/online-course-statistical-methods-r
Visualizing gene structures in R? gggenes, an extension of ggplot2, simplifies the process of creating clear and informative gene diagrams, making genomic data easier to interpret and share.
Visualization: https://cran.r-project.org/web/packages/gggenes/vignettes/introduction-to-gggenes.html
Click this link for detailed information: https://statisticsglobe.com/online-course-data-visualization-ggplot2-r
https://DSLC.io welcomes you to week 12 of #TidyTuesday! We're exploring Text Data From Amazon's Annual Reports!
https://tidytues.day/2025/2025-03-25 https://gregoryvdvinne.github.io/Text-Mining-Amazon-Budgets.html
Submit a dataset! https://github.com/rfordatascience/tidytuesday/blob/main/.github/CONTRIBUTING.md
The mighty ggmap is a powerful R library for visualizing data geospatially.
Learn how to make great looking data with Stadia Maps.
#RStats #DataViz #Geospatial #Tidyverse
https://docs.stadiamaps.com/tutorials/getting-started-in-r-with-ggmap/?utm_campaign=tutorial_start_ggmap&utm_source=mastodon&utm_medium=social
Curator: @lydz_gibby
https://DSLC.io welcomes you to week 11 of #TidyTuesday! We're exploring Palm Trees!
https://tidytues.day/2025/2025-03-18 https://www.nature.com/articles/s41597-019-0189-0
Submit a dataset! https://github.com/rfordatascience/tidytuesday/blob/main/.github/CONTRIBUTING.md
Local regression is a non-parametric method for fitting smooth curves to data by applying multiple localized regressions. It is useful for uncovering non-linear relationships when the data’s exact form is unknown. Proper use of local regression can reveal trends in noisy data, but poor implementation might lead to misleading results.
Image: https://en.wikipedia.org/wiki/Local_regression#/media/File:Loess_curve.svg
More details: http://eepurl.com/gH6myT
There are now so many "backends" for {dplyr}—duckdb with {duckplyr}, polars with {tidypolars}, various database engines with {dbplyr}, {data.table} with {dtplyr}. Is there a blog post or flow chart somewhere with pros and cons of each? Like, comparisons of memory requirements, speed, and how likely they are to "just work"?
Curator: @jonthegeek
https://DSLC.io welcomes you to week 10 of #TidyTuesday! We're exploring Pixar Films!
https://tidytues.day/2025/2025-03-11 https://erictleung.com/pixarfilms/articles/pixar_film_ratings.html
Submit a dataset! https://github.com/rfordatascience/tidytuesday/blob/main/.github/CONTRIBUTING.md
Curator: @lydz_gibby
https://DSLC.io welcomes you to week 9 of #TidyTuesday! We're exploring Long Beach Animal Shelter!
https://tidytues.day/2025/2025-03-04 https://www.longbeach.gov/press-releases/long-beach-animal-care-services-hits-highest-adoption-rate-ever-surpasses-2024--strategic-plan-goal/
Submit a dataset! https://github.com/rfordatascience/tidytuesday/blob/main/.github/CONTRIBUTING.md
https://DSLC.io welcomes you to week 8 of #TidyTuesday! We're exploring Academic Literature on Racial and Ethnic Disparities in Reproductive Medicine in the US!
https://tidytues.day/2025/2025-02-25 https://katcorr.github.io/this-art-is-HARD/
Submit a dataset! https://github.com/rfordatascience/tidytuesday/blob/main/.github/CONTRIBUTING.md
This #Tidyverse blog post introduces Air, an extremely fast #R formatter: https://www.tidyverse.org/blog/2025/02/air/
It looks promising for prettifying code.
