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Anke boosted
Nicola Rennie
@nrennie@fosstodon.org  ·  activity timestamp 2 weeks ago

Mapping out how quickly you can get around Edinburgh with different modes of transport for day 26 of the #30DayMapChallenge!

Useful blog post if you want to try this yourself: https://jamiehudson.netlify.app/post/distance_map/

#RStats #DataViz #ggplot2

Three small multiple street maps of Edinburgh showing how far you can travel in 15 minutes on foot, by bike, and by car. Bike and car aren't that different.
Three small multiple street maps of Edinburgh showing how far you can travel in 15 minutes on foot, by bike, and by car. Bike and car aren't that different.
Three small multiple street maps of Edinburgh showing how far you can travel in 15 minutes on foot, by bike, and by car. Bike and car aren't that different.
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Nicola Rennie
@nrennie@fosstodon.org  ·  activity timestamp 2 weeks ago

Mapping out how quickly you can get around Edinburgh with different modes of transport for day 26 of the #30DayMapChallenge!

Useful blog post if you want to try this yourself: https://jamiehudson.netlify.app/post/distance_map/

#RStats #DataViz #ggplot2

Three small multiple street maps of Edinburgh showing how far you can travel in 15 minutes on foot, by bike, and by car. Bike and car aren't that different.
Three small multiple street maps of Edinburgh showing how far you can travel in 15 minutes on foot, by bike, and by car. Bike and car aren't that different.
Three small multiple street maps of Edinburgh showing how far you can travel in 15 minutes on foot, by bike, and by car. Bike and car aren't that different.
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Jeremy ⁂ and 1 other boosted
terence
@terence@fosstodon.org  ·  activity timestamp 3 weeks ago

#30DayMapChallenge · Day 19 · Projections. Here's a visualisation of eight map projections.

#ggplot2 adventures, an #rstats tale

A visualisation of eight map projections
A visualisation of eight map projections
A visualisation of eight map projections
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terence
@terence@fosstodon.org  ·  activity timestamp 3 weeks ago

#30DayMapChallenge · Day 19 · Projections. Here's a visualisation of eight map projections.

#ggplot2 adventures, an #rstats tale

A visualisation of eight map projections
A visualisation of eight map projections
A visualisation of eight map projections
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Mince Pie Butty boosted
Nicola Rennie
@nrennie@fosstodon.org  ·  activity timestamp last month

It's Day 10 of the #30DayMapChallenge and for the "air" prompt, I decided to look at air quality data before and after Bonfire Night in the UK 🎇

#RStats #ggplot2 #DataViz

Side by side maps of the UK showing air quality before and after Bonfire night. The day after Bonfire night shows many more sites marked as exceeding a threshold of 40 micrograms/m3.
Side by side maps of the UK showing air quality before and after Bonfire night. The day after Bonfire night shows many more sites marked as exceeding a threshold of 40 micrograms/m3.
Side by side maps of the UK showing air quality before and after Bonfire night. The day after Bonfire night shows many more sites marked as exceeding a threshold of 40 micrograms/m3.
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Nicola Rennie
@nrennie@fosstodon.org  ·  activity timestamp last month

It's Day 10 of the #30DayMapChallenge and for the "air" prompt, I decided to look at air quality data before and after Bonfire Night in the UK 🎇

#RStats #ggplot2 #DataViz

Side by side maps of the UK showing air quality before and after Bonfire night. The day after Bonfire night shows many more sites marked as exceeding a threshold of 40 micrograms/m3.
Side by side maps of the UK showing air quality before and after Bonfire night. The day after Bonfire night shows many more sites marked as exceeding a threshold of 40 micrograms/m3.
Side by side maps of the UK showing air quality before and after Bonfire night. The day after Bonfire night shows many more sites marked as exceeding a threshold of 40 micrograms/m3.
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Matthieu Viry boosted
Nicola Rennie
@nrennie@fosstodon.org  ·  activity timestamp last month

For the "accessibility" prompt on day 7 of the #30DayMapChallenge, I decided to investigate how accessible the default #ggplot2 colours are to people with different types of colour vision deficiency (and for different numbers of colours used). 🎨

TLDR: please choose a different, accessible palette

#RStats #DataViz

A 5x5 grid of maps of France. Each row contains areas shaded with a different number of colours, and each column shows how it looks with different types of colour vision deficiency. None are accessible, except when using only two colours.
A 5x5 grid of maps of France. Each row contains areas shaded with a different number of colours, and each column shows how it looks with different types of colour vision deficiency. None are accessible, except when using only two colours.
A 5x5 grid of maps of France. Each row contains areas shaded with a different number of colours, and each column shows how it looks with different types of colour vision deficiency. None are accessible, except when using only two colours.
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Nicola Rennie
@nrennie@fosstodon.org  ·  activity timestamp last month

For the "accessibility" prompt on day 7 of the #30DayMapChallenge, I decided to investigate how accessible the default #ggplot2 colours are to people with different types of colour vision deficiency (and for different numbers of colours used). 🎨

TLDR: please choose a different, accessible palette

#RStats #DataViz

A 5x5 grid of maps of France. Each row contains areas shaded with a different number of colours, and each column shows how it looks with different types of colour vision deficiency. None are accessible, except when using only two colours.
A 5x5 grid of maps of France. Each row contains areas shaded with a different number of colours, and each column shows how it looks with different types of colour vision deficiency. None are accessible, except when using only two colours.
A 5x5 grid of maps of France. Each row contains areas shaded with a different number of colours, and each column shows how it looks with different types of colour vision deficiency. None are accessible, except when using only two colours.
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devSJR :python: :rstats: boosted
Sascha Wolfer
@sascha_wolfer@fediscience.org  ·  activity timestamp last month

#Rstats problems: Did you ever think that the dots for dotted lines are a bit too far apart per default? TIL that it's super easy to change this.

In #ggplot2, simply try something like:

scale_linetype_manual(
values = c(a = "dotted", b = "11")
)

The '11' means: 1 point for a dot, 1 point for a gap. Find out more here: https://stackoverflow.com/questions/25788945/how-to-define-more-line-types-for-graphs-in-r-custom-linetype

Stack Overflow

How to define more line types for graphs in R (custom linetype)?

There are 6 line types defined for plots in R defined as "dashed", "longdash" ... Link How can I define more types if I have more that 6 series to plot ? The graph lines can be
A graph with two dotted lines. The dots for one of the lines are much closer together.
A graph with two dotted lines. The dots for one of the lines are much closer together.
A graph with two dotted lines. The dots for one of the lines are much closer together.
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Sascha Wolfer
@sascha_wolfer@fediscience.org  ·  activity timestamp last month

#Rstats problems: Did you ever think that the dots for dotted lines are a bit too far apart per default? TIL that it's super easy to change this.

In #ggplot2, simply try something like:

scale_linetype_manual(
values = c(a = "dotted", b = "11")
)

The '11' means: 1 point for a dot, 1 point for a gap. Find out more here: https://stackoverflow.com/questions/25788945/how-to-define-more-line-types-for-graphs-in-r-custom-linetype

Stack Overflow

How to define more line types for graphs in R (custom linetype)?

There are 6 line types defined for plots in R defined as "dashed", "longdash" ... Link How can I define more types if I have more that 6 series to plot ? The graph lines can be
A graph with two dotted lines. The dots for one of the lines are much closer together.
A graph with two dotted lines. The dots for one of the lines are much closer together.
A graph with two dotted lines. The dots for one of the lines are much closer together.
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Simon Tournier
@zimoun@social.sciences.re  ·  activity timestamp last month

Today, @edumerco motivated me to give a deeper look to #Org mode and #Emacs #Lisp for processing data as a reproducible computational notebook. It reminds me this great MOOC [1]. 🤩

And today I learn more about #Sociocracy thanks @edumerco! Well, the concept of #Guix teams needs more love. 😍

Bah the kind of day when you feel part of something. 🥳

Thanks @bzg for the connection. 😁

1: https://www.fun-mooc.fr/en/courses/reproducible-research-methodological-principles-transparent-scie

Eduardo Mercovich (él)
@edumerco@social.coop replied  ·  activity timestamp last month

Dear @zimoun , thank you for such a rich meeting and sharing your experience with #ReproducibleResearch and #guix for this #tem25 thesis . :)

#orgmode Babel (blocks of code calling anything integrated with the text and images) are great for #LiteraryProgramming and reprod. research.

Also, thank you for your mention of #ggplot2 that @ansate nailed too a little later. :)

Thanks also to @bzg too. 🙏

Re #PeerGovernance, I'd be delighted to share my experience with the guix community anytime.

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Sharon Machlis
@smach@masto.machlis.com  ·  activity timestamp 2 months ago

The {ggbot2} #RStats 📦 launches a chatbot you can speak to in plain language, and it can write ggplot2 R code and display the dataviz.
Plus: The {shinyrealtime} #RStats 📦 has a demo voice app that generates #dataviz code in both R and #Python
https://www.infoworld.com/article/4072500/how-to-run-an-r-data-visualization-chatbot-you-can-talk-to.html
#GenerativeAI #ggplot2

InfoWorld

How to run an R data visualization chatbot you can talk to

Posit’s ggbot2 is a voice assistant for ggplot2. Tell it what you want in a spoken conversation, and it will generate plots and ggplot2 R code from your data.
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Unnamed TNG skant beefcake boosted
James Hawley, PhD
@jrhawley@scholar.social  ·  activity timestamp 3 months ago

Wow, setting default labels for your data in #rstats using "label" attributes is a good idea. I'd never heard of this before, but I'm glad that #ggplot2 is now supporting it. Manually specifying axis labels was a bit tedious.

I do like that if you transform the data, the default label is not applied (see the sqrt(body_mass) variable in the first figure here).

https://www.tidyverse.org/blog/2025/09/ggplot2-4-0-0/#labels

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James Hawley, PhD
@jrhawley@scholar.social  ·  activity timestamp 3 months ago

Wow, setting default labels for your data in #rstats using "label" attributes is a good idea. I'd never heard of this before, but I'm glad that #ggplot2 is now supporting it. Manually specifying axis labels was a bit tedious.

I do like that if you transform the data, the default label is not applied (see the sqrt(body_mass) variable in the first figure here).

https://www.tidyverse.org/blog/2025/09/ggplot2-4-0-0/#labels

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Nicola Rennie
@nrennie@fosstodon.org  ·  activity timestamp 4 months ago

I had the pleasure of curating this week's #TidyTuesday data about Scottish Munros ⛰️ So the chart just had to be an annotated, snow-capped, density mountain! 📊

Code: https://github.com/nrennie/tidytuesday/tree/main/2025/2025-08-19

#RStats #ggplot2 #DataViz

Density plot showing height of Munros in Scotland with a peak about 3100 ft, going up to 4411 ft of Ben Nevis
Density plot showing height of Munros in Scotland with a peak about 3100 ft, going up to 4411 ft of Ben Nevis
Density plot showing height of Munros in Scotland with a peak about 3100 ft, going up to 4411 ft of Ben Nevis
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Sharon Machlis
@smach@masto.machlis.com  ·  activity timestamp 4 months ago

New presentation just posted at today's @useR_conf virtual conference: Plot Twist: Adding Interactivity to the Elegance of ggplot2 with ggiraph

By @tanya_shapiro & @CedScherer

Video https://www.youtube.com/watch?v=GnDjRxyO-7A

#RStats#DataViz #ggplot2 #user2025

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