Because of my old age I guess, I'm often asked how I switched from base R #RStats to #tidyverse. I learnt by watching @drob screencasts 🎥 in which he analyses #TidyTuesday data he has never seen before (!
Workshop to come on reproducible science in our lab.
Quick and dirty text mining of the ISEC2020 abstracts.
Une analyse descriptive du phénomène de concentration d’attaques de loup sur des élevages d’animaux domestiques en France.
Procrastination... Je me suis "amusé" à reproduire cette géniale figure de @coulmont sur le jour des décès en 🇫🇷 en fonction de l'âge et du temps avec #rstats et le #tidyverse https://t.
This week we host our first winter school on «Reproducible Research in Numerical Ecology » co-organised by #GDR_Ecostat & #CESAB @FRBiodiv. Many thanks to our incredible list of speakers : Nicolas Casajus, Stéphane Dray, @GueryLorelei, @oaggimenez, @FGuilhaumon & @NinaSchiett !
👩 💻🗺️👨 💻 The slides of my introduction to #GIS and #mapping in #rstats using the #sf 📦 and brown 🐻 distribution in the #pyrenees as a case study https://t.co/SKQOCzbxHn - raw material on #github https://t.
My introduction to the #tidyverse for our lab meeting to manipulate and visualise data in #rstat https://t.co/As9bkXY9GZ. Feel free to steal and modify this material for your own use. Be advised, this is work in progress & a mix of 🇬🇧/🇫🇷😋 Comments welcome!
I read this awesome post (in French) by Baptiste Coulmont, professor in sociology, who explored the French academic network in sociology. Coulmont used the composition of PhD commitees to determine academic links between colleagues. The approach very appealing because it uses public data available from the website these.fr. Here, I used Coulmont’s R code to produce the French academic network in ecology. This was a nice opportunity to illustrate how to work in the tidyverse and to do some web scraping using the rvest package.