#ggpmisc — Public Fediverse posts

Day 2 | Comparisons – Slope | #30DayChartChallenge. Analysis develop with R using #ggplot2, #tidyverse, #ggpmisc, , #terra, #ggtext, #showtext y #sf. Data source: Sentinel-2 MSI (2019-2024)

#rstats #dataviz #ggpmisc #ggplot2 Fresh updates to packages 'ggpp' and 'ggpmisc' are on CRAN.

'ggpmisc' provides tools for annotations based on model fits, optionally followed by multiple comparisons. Multiple pairwise comparisons with `stat_multcomp()` are based on package 'multicomp' and support P-value adjustments as well as user defined sets of pairwise contrasts. stats supporting major axis, quantile and non-linear regression for curves and matching annotations are also provided.

#ggplot2 #ggpmisc #dataviz #ggplot #rstats Version 0.5.5 of package 'ggpp' is now in CRAN. 'ggpmisc' 0.5.4 has been in CRAN for some time. What is new compared to version 0.5.3 of these packages? 1) compatible with 'ggplot2' under development (future version 3.5.x), 2) Pairwise labels and multiple comparisons (based on 'multcomp' package), 3) Easy stacking of error bars. See (https://docs.r4photobiology.info/ggpp) and (https://docs.r4photobiology.info/ggpmisc) for the code behind the examples below and additional examples.

#rstats #ggpmisc #r4photobiology I have continued updating my R for Photobioloy website at (https://r4photobiology.info). I am now using the pre-release of Quarto 1.4 and learning how to tweak the look and workings of the website. I got 'plotly' (https://www.r4photobiology.info/galleries/plot-interactive.html) and 'gganimate' (https://www.r4photobiology.info/galleries/plot-animation.html) working within Quarto web pages together with 'ggpmisc'. A couple of hours ago I added RSS feeds. 😀

#rstats package #ggpmisc version 0.5.3 is now on CRAN. 'ggpmisc' is now fully compatible with #gganimate and partly compatible with #plotly. A gallery of animated ggplots with code (https://www.r4photobiology.info/galleries/plot-animation.html) is now online. (https://github.com/aphalo/ggpmisc)

#ggplot2 #ggpmisc #dataviz #ggplot #rstats I have added new pages and revamped older ones containg R code examples for plots to the galleries (https://www.r4photobiology.info/galleries.html) at my website about R (https://www.r4photobiology.info/). They demostrate the use of packages 'ggpmisc', 'ggpp' and 'ggrepel' for more easily adding insets, annotations and data labels to plots created using the grammar of graphics implemented in 'ggplot2'.