#ggplot2 — Public Fediverse posts
Live and recent posts from across the Fediverse tagged #ggplot2, aggregated by home.social.
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An alternative way of comparing two distributions for #TidyTuesday this week! 📊
The diameter of each arc shows the % with access to non-solid fuels, split by urban and rural areas ⛽
Code: https://github.com/nrennie/tidytuesday/tree/main/2026/2026-05-26
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An alternative way of comparing two distributions for #TidyTuesday this week! 📊
The diameter of each arc shows the % with access to non-solid fuels, split by urban and rural areas ⛽
Code: https://github.com/nrennie/tidytuesday/tree/main/2026/2026-05-26
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An alternative way of comparing two distributions for #TidyTuesday this week! 📊
The diameter of each arc shows the % with access to non-solid fuels, split by urban and rural areas ⛽
Code: https://github.com/nrennie/tidytuesday/tree/main/2026/2026-05-26
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An alternative way of comparing two distributions for #TidyTuesday this week! 📊
The diameter of each arc shows the % with access to non-solid fuels, split by urban and rural areas ⛽
Code: https://github.com/nrennie/tidytuesday/tree/main/2026/2026-05-26
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An alternative way of comparing two distributions for #TidyTuesday this week! 📊
The diameter of each arc shows the % with access to non-solid fuels, split by urban and rural areas ⛽
Code: https://github.com/nrennie/tidytuesday/tree/main/2026/2026-05-26
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Well, that was a quick lesson in not what to do.
Generated ~200 #RStats #ggplot2 plots with many having a large number of points. Took less than 5 minutes to generate them all.
But took forever to save them all, and 5GB rds.
Will take a lot less work to just generate them in the quarto reports when needed instead of generating and saving them I guess.
I really only need them for the reports anyways.
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Well, that was a quick lesson in not what to do.
Generated ~200 #RStats #ggplot2 plots with many having a large number of points. Took less than 5 minutes to generate them all.
But took forever to save them all, and 5GB rds.
Will take a lot less work to just generate them in the quarto reports when needed instead of generating and saving them I guess.
I really only need them for the reports anyways.
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Well, that was a quick lesson in not what to do.
Generated ~200 #RStats #ggplot2 plots with many having a large number of points. Took less than 5 minutes to generate them all.
But took forever to save them all, and 5GB rds.
Will take a lot less work to just generate them in the quarto reports when needed instead of generating and saving them I guess.
I really only need them for the reports anyways.
-
Well, that was a quick lesson in not what to do.
Generated ~200 #RStats #ggplot2 plots with many having a large number of points. Took less than 5 minutes to generate them all.
But took forever to save them all, and 5GB rds.
Will take a lot less work to just generate them in the quarto reports when needed instead of generating and saving them I guess.
I really only need them for the reports anyways.
-
Well, that was a quick lesson in not what to do.
Generated ~200 #RStats #ggplot2 plots with many having a large number of points. Took less than 5 minutes to generate them all.
But took forever to save them all, and 5GB rds.
Will take a lot less work to just generate them in the quarto reports when needed instead of generating and saving them I guess.
I really only need them for the reports anyways.
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- I wish I could avoid using #pandas altogether, i just can't seem to wrap my head around it (constantly running into issues with indices, loc, iloc, missing data, and more; this is probably also user error though)
- #plotnine is wonderful, basically drop-in replacement for #ggplot2 but it doesn't feel like a mere copy
- still looking for a package for generalized additive mixed models that can do mgcv style estimation but also "normal" glms, and nice summary outputs (tips beyond pyGAM?)2/n
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- I wish I could avoid using #pandas altogether, i just can't seem to wrap my head around it (constantly running into issues with indices, loc, iloc, missing data, and more; this is probably also user error though)
- #plotnine is wonderful, basically drop-in replacement for #ggplot2 but it doesn't feel like a mere copy
- still looking for a package for generalized additive mixed models that can do mgcv style estimation but also "normal" glms, and nice summary outputs (tips beyond pyGAM?)2/n
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- I wish I could avoid using #pandas altogether, i just can't seem to wrap my head around it (constantly running into issues with indices, loc, iloc, missing data, and more; this is probably also user error though)
- #plotnine is wonderful, basically drop-in replacement for #ggplot2 but it doesn't feel like a mere copy
- still looking for a package for generalized additive mixed models that can do mgcv style estimation but also "normal" glms, and nice summary outputs (tips beyond pyGAM?)2/n
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- I wish I could avoid using #pandas altogether, i just can't seem to wrap my head around it (constantly running into issues with indices, loc, iloc, missing data, and more; this is probably also user error though)
- #plotnine is wonderful, basically drop-in replacement for #ggplot2 but it doesn't feel like a mere copy
- still looking for a package for generalized additive mixed models that can do mgcv style estimation but also "normal" glms, and nice summary outputs (tips beyond pyGAM?)2/n
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- I wish I could avoid using #pandas altogether, i just can't seem to wrap my head around it (constantly running into issues with indices, loc, iloc, missing data, and more; this is probably also user error though)
- #plotnine is wonderful, basically drop-in replacement for #ggplot2 but it doesn't feel like a mere copy
- still looking for a package for generalized additive mixed models that can do mgcv style estimation but also "normal" glms, and nice summary outputs (tips beyond pyGAM?)2/n
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Managed to get {ggchord2} working with {ggiraph} so you can* have interactive chord diagrams with tooltips!
*currently a bit hacky but technically does work
Example: https://nrennie.rbind.io/data-viz-projects/local-council-elections/
This example is a remake of a Sankey chart published by YouGov today in this article: https://yougov.com/en-gb/articles/54811-labours-voter-coalition-broke-more-to-left-than-right-at-2026-local-elections
Original Sankey chart: https://flo.uri.sh/visualisation/29040587/embed
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Managed to get {ggchord2} working with {ggiraph} so you can* have interactive chord diagrams with tooltips!
*currently a bit hacky but technically does work
Example: https://nrennie.rbind.io/data-viz-projects/local-council-elections/
This example is a remake of a Sankey chart published by YouGov today in this article: https://yougov.com/en-gb/articles/54811-labours-voter-coalition-broke-more-to-left-than-right-at-2026-local-elections
Original Sankey chart: https://flo.uri.sh/visualisation/29040587/embed
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Managed to get {ggchord2} working with {ggiraph} so you can* have interactive chord diagrams with tooltips!
*currently a bit hacky but technically does work
Example: https://nrennie.rbind.io/data-viz-projects/local-council-elections/
This example is a remake of a Sankey chart published by YouGov today in this article: https://yougov.com/en-gb/articles/54811-labours-voter-coalition-broke-more-to-left-than-right-at-2026-local-elections
Original Sankey chart: https://flo.uri.sh/visualisation/29040587/embed
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Managed to get {ggchord2} working with {ggiraph} so you can* have interactive chord diagrams with tooltips!
*currently a bit hacky but technically does work
Example: https://nrennie.rbind.io/data-viz-projects/local-council-elections/
This example is a remake of a Sankey chart published by YouGov today in this article: https://yougov.com/en-gb/articles/54811-labours-voter-coalition-broke-more-to-left-than-right-at-2026-local-elections
Original Sankey chart: https://flo.uri.sh/visualisation/29040587/embed
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Managed to get {ggchord2} working with {ggiraph} so you can* have interactive chord diagrams with tooltips!
*currently a bit hacky but technically does work
Example: https://nrennie.rbind.io/data-viz-projects/local-council-elections/
This example is a remake of a Sankey chart published by YouGov today in this article: https://yougov.com/en-gb/articles/54811-labours-voter-coalition-broke-more-to-left-than-right-at-2026-local-elections
Original Sankey chart: https://flo.uri.sh/visualisation/29040587/embed