#ggplot2

aRtsy_packageaRtsy_package
2025-05-17

Today's artwork generated with and :

2025-05-16

@geospacedman Yes, I think 'layer' is introduced in Hadley's #ggplot2 implementation. Thank you for looking this up and sharing!

aRtsy_packageaRtsy_package
2025-05-16

Today's artwork generated with and :

Steven Sandersonspsanderson@rstats.me
2025-05-15

Same as yesterday, but this time, making a 2D Discrete Random Walk with my #R #Package #RandomWalker

#R #RStats #RProgramming #RandomWalks #Visual #ggplot2

A scatterplot titled "2D Random Walks with Outliers Highlighted." It shows multiple colored random walk paths in a 2D space, with outliers prominently highlighted in bold red dashed lines. Non-outliers are displayed in lighter colors. Black dashed horizontal and vertical lines indicate threshold boundaries for outlier detection. The x-axis is labeled "Cumulative Sum X," and the y-axis is labeled "Cumulative Sum Y."A scatterplot titled "2D Random Walk Outliers Only." It showcases only the outlier random walk paths in a 2D space, displayed in various colors on a white background. Black dashed horizontal and vertical lines mark the threshold boundaries for outlier detection. The x-axis is labeled "Cumulative Sum X," and the y-axis is labeled "Cumulative Sum Y."A scatterplot titled "2D Random Walk Non-Outliers Only." It displays multiple colored linear paths representing random walks in a 2D space, constrained to non-outlier data points. The x-axis is labeled "Cumulative Sum X," and the y-axis is labeled "Cumulative Sum Y." The paths are laid out in a grid-like pattern with varied colors.A screenshot of R programming code written for generating 2D random walks, analyzing outliers, and plotting results. The code uses libraries such as RandomWalker, dplyr, ggplot2, and tidyr. It calculates confidence intervals, identifies outliers, and generates three types of plots: non-outliers, outliers, and highlighted outliers. The syntax is color-coded, with comments explaining each step.
Steven P. Sanderson II, MPHstevensanderson@mstdn.social
2025-05-15

Same as yesterday, but this time, making a 2D Discrete Random Walk with my #R #Package #RandomWalker

#R #RStats #RProgramming #RandomWalks #Visual #ggplot2

A scatterplot titled "2D Random Walk Non-Outliers Only." It displays multiple colored linear paths representing random walks in a 2D space, constrained to non-outlier data points. The x-axis is labeled "Cumulative Sum X," and the y-axis is labeled "Cumulative Sum Y." The paths are laid out in a grid-like pattern with varied colors.A scatterplot titled "2D Random Walks with Outliers Highlighted." It shows multiple colored random walk paths in a 2D space, with outliers prominently highlighted in bold red dashed lines. Non-outliers are displayed in lighter colors. Black dashed horizontal and vertical lines indicate threshold boundaries for outlier detection. The x-axis is labeled "Cumulative Sum X," and the y-axis is labeled "Cumulative Sum Y."A scatterplot titled "2D Random Walk Outliers Only." It showcases only the outlier random walk paths in a 2D space, displayed in various colors on a white background. Black dashed horizontal and vertical lines mark the threshold boundaries for outlier detection. The x-axis is labeled "Cumulative Sum X," and the y-axis is labeled "Cumulative Sum Y."A screenshot of R programming code written for generating 2D random walks, analyzing outliers, and plotting results. The code uses libraries such as RandomWalker, dplyr, ggplot2, and tidyr. It calculates confidence intervals, identifies outliers, and generates three types of plots: non-outliers, outliers, and highlighted outliers. The syntax is color-coded, with comments explaining each step.
2025-05-15

πŸ“Š #MakeoverMonday – 2025 W20 | The Religious Composition of the World’s Migrants
.
πŸ”—: stevenponce.netlify.app/data_v
.
#rstats | #DataFam | #dataviz | #ggplot2

A diverging bar chart showing religious representation gaps between migrants and general population. Christians (+16.6), Muslims (+3.7), and Jewish (+0.9) are overrepresented among migrants (purple bars extending right), while Hindus (-10.2) and religiously unaffiliated (-10) are underrepresented (pink bars extending left). Buddhist representation is nearly equal (-0.1). Horizontal arrows indicate the direction of over- and underrepresentation.
aRtsy_packageaRtsy_package
2025-05-15

Today's artwork generated with and :

2025-05-14

Amazing survey response! Looks like 3 is the winner - but was expecting 2 (geom_point and geom_smooth) or 4 (each line) to be more popular. Curious to hear about logic that gets us to 3 πŸ™πŸŽˆ #ggplot2

2025-05-14

This week's #TidyTuesday data is all about seismic activity at Mount Vesuvius! πŸŒ‹

πŸ“Š Two heatmaps showing weekly and annual patterns
🩹 Joined with {patchwork}
🎨 Volcano inspired colour palette

Code: github.com/nrennie/tidytuesday

#DataViz #RStats #DSLC #ggplot2

A heatmap showing seismic activity at Mount Vesuvius from 2013 to 2024. Each column represents a year, with weeks running vertically. Darker shades indicate stronger seismic events. A square above, indicates year total. The chart shows no clear seasonal trend, but overall activity varies by year.
aRtsy_packageaRtsy_package
2025-05-14

Today's artwork generated with and :

Statistics GlobeStatisticsGlobe
2025-05-13

Make your plots more stylish and visually appealing! The ggthemes package offers a variety of pre-built themes that help you customize the look of your ggplot2 visualizations, drawing inspiration from popular design standards.

The visualization shown here is from the package website: yutannihilation.github.io/allY

More: statisticsglobe.com/online-cou

aRtsy_packageaRtsy_package
2025-05-13

Today's artwork generated with and :

2025-05-12

Who are the #ggplot2 extenders? Here are some super-extenders (folks with 3 or more extension packages on CRAN). A growing number -- highlighted -- have presented or are scheduled to present at the ggplot2 extenders meetup!

ggplot2-extenders.github.io/gg

aRtsy_packageaRtsy_package
2025-05-12

Today's artwork generated with and :

Aditya Dahiyaadityadahiya
2025-05-11

Visualizing terminated NSF grants with {vayr} and {packcircles} algorithmic layout! πŸ“ŠSTEM Education hit hardest.
Code πŸ”— tinyurl.com/tidy-nsf-grants
Data: grant-watch.us (@GrantWatch)
Tools by Alex Coppock at alexandercoppock.com/vayr/inde

This graphic visualizes approximately 1,040 terminated NSF grants under the Trump administration in 2025, using a packcircles layout. The Y-axis lists nine NSF directorates, while the X-axis categorizes grants into four types: continuous, standard, fellowship, and cooperative. Each dot represents a single grant, arranged via position_circlepack() from the {vayr} package. Cumulative bar plots along the axes display the total funding committed via USAspending.gov for each directorate and grant type. Key findings reveal that STEM Education faced the largest funding cuts, predominantly in continuing grants, while Technology and Innovation saw the most cooperative agreement terminations.
Aditya Dahiyaadityadahiya
2025-05-11

πŸ—ΊοΈ Earthquakes at Mt. Vesuvius (2013–2024): Since 2019, they're shifting westward (annual weighted centroids).
Data: @INGV_press @libbyheeren.bsky.social
Full Code πŸ”— tinyurl.com/tidy-mt-vesuvius
Made with {ggplot2} {ggmap} {terra}

This graphic shows the geographic distribution of seismic events at Mount Vesuvius from 2013 to 2024, with each earthquake represented as a grey dot sized by its duration magnitude (Md). For each year, the red circle marks the weighted centroid of all events, calculated using Md as the weighting factor. Over the 12-year period, the centroids trace a clear westward shift beginning in 2019, suggesting a possible geographic migration of seismic activity within the region. This trend may warrant further investigation into evolving subsurface dynamics at the volcano.
aRtsy_packageaRtsy_package
2025-05-11

Today's artwork generated with and :

2025-05-10
This visualization shows volatility and change patterns in Mount Vesuvius seismic activity from 2011 to 2023 through three related charts. The top chart displays waiting times between consecutive earthquakes on a logarithmic scale, showing that most events occur within 2-20 hours of each other, with a median of 2.6 hours. The middle chart shows month-to-month percentage changes in seismic activity, with nearly balanced increases (72 months, 50%) and decreases (73 months, 50%), suggesting a dynamic but stable volcanic system. The bottom chart presents long-term patterns with monthly counts, a 6-month moving average, and a trend line, revealing multi-year cycles despite short-term volatility.
aRtsy_packageaRtsy_package
2025-05-10

Today's artwork generated with and :

aRtsy_packageaRtsy_package
2025-05-09

Today's artwork generated with and :

Client Info

Server: https://mastodon.social
Version: 2025.04
Repository: https://github.com/cyevgeniy/lmst