#ggdist — Public Fediverse posts

#Día5 | Comparaciones – Experimental | #30DayChartChallenge. Experimenté agregando una sumatoria horizontal de observaciones en un boxplot sobre la capacidad endocraneana en especies del género Homo. Creada usando R con #ggplot2, #ggdist, #dplyr, #scales, #ggtext, #patchwork, #tibble y #tidyr.

#Día5 | Comparaciones – Experimental | #30DayChartChallenge. Experimenté agregando una sumatoria horizontal de observaciones en un boxplot sobre la capacidad endocraneana en especies del género Homo. Creada usando R con #ggplot2, #ggdist, #dplyr, #scales, #ggtext, #patchwork, #tibble y #tidyr.

Merry Distmas! A new version of
#ggdist
(3.3.2) just hit CRAN
#rstats

The main impetus of the update is minor fixes to support
#ggplot2
3.5.0, but there are a few things worth mentioning... 1/5

Merry Distmas! A new version of
#ggdist
(3.3.2) just hit CRAN
#rstats

The main impetus of the update is minor fixes to support
#ggplot2
3.5.0, but there are a few things worth mentioning... 1/5

🎥 @mjskay
also has a quick talk that summarises the wealth possibilities. #rstats #ggdist
https://www.youtube.com/watch?v=ChwczkfFsXM

🎥 @mjskay
also has a quick talk that summarises the wealth possibilities. #rstats #ggdist
https://www.youtube.com/watch?v=ChwczkfFsXM

If you are thinking of plotting distributions and/or confidence intervals, I highly recommend you check out the ggdist package by @mjskay
#RStats #ggdist
https://github.com/mjskay/ggdist

If you are thinking of plotting distributions and/or confidence intervals, I highly recommend you check out the ggdist package by @mjskay
#RStats #ggdist
https://github.com/mjskay/ggdist

Here's an example of #ggblend with #ggdist: ggdist can create gradient lineribbons using color ramps, but can have problems when they overlap

ggblend can partition a geometry and blend those partitions: e.g. using "multiply" to blend overlapping lineribbons together

Here's an example of #ggblend with #ggdist: ggdist can create gradient lineribbons using color ramps, but can have problems when they overlap

ggblend can partition a geometry and blend those partitions: e.g. using "multiply" to blend overlapping lineribbons together

#ggdist 3.3.0 just hit CRAN! Some highlights:

1. A big change is the new default density estimator, which detects bounded distributions; see linked post: https://fediscience.org/@mjskay/110359116199194043

This also means Mode() and hdi(), which use the density estimator, should be better too.

#rstats

#ggdist 3.3.0 just hit CRAN! Some highlights:

1. A big change is the new default density estimator, which detects bounded distributions; see linked post: https://fediscience.org/@mjskay/110359116199194043

This also means Mode() and hdi(), which use the density estimator, should be better too.

#rstats

round 2 of "try to make #ggdist's default density estimator better" #rstats

I think this is the one for now (better be too b/c gotta release another version soon!!!)

round 2 of "try to make #ggdist's default density estimator better" #rstats

I think this is the one for now (better be too b/c gotta release another version soon!!!)

welp guess a new version of #ggdist drops soon

#rstats

welp guess a new version of #ggdist drops soon

#rstats

@healthstatsdude @ct_bergstrom @knewman
I'll give a shameless plus for #ggdist, which makes it easy to create a bunch of visualizations of distributions, including density plots, dotplots, and beeswarms: https://mjskay.github.io/ggdist/

One big difference compared to ggbeeswarm is that ggdist will automatically set the dot size to ensure the chart does not overrun the display area

@healthstatsdude @ct_bergstrom @knewman
I'll give a shameless plus for #ggdist, which makes it easy to create a bunch of visualizations of distributions, including density plots, dotplots, and beeswarms: https://mjskay.github.io/ggdist/

One big difference compared to ggbeeswarm is that ggdist will automatically set the dot size to ensure the chart does not overrun the display area

Playing with a new default kernel density estimator for the #ggdist #rstats 📦. Thoughts?

Trying to deal with edge effects in default KDEs on bounded data. Never gonna convince everyone to use histograms or dotplots, so a better default would help...

See https://gist.github.com/mjskay/b6b067a74c6542452d2ce49c3a4be8b4

Playing with a new default kernel density estimator for the #ggdist #rstats 📦. Thoughts?

Trying to deal with edge effects in default KDEs on bounded data. Never gonna convince everyone to use histograms or dotplots, so a better default would help...

See https://gist.github.com/mjskay/b6b067a74c6542452d2ce49c3a4be8b4