Learnrs of module 1

Author: phgrosjean

inst/tutorials/A00La_discovery/A00La_discovery.Rmd

@@ -4,7 +4,7 @@ author: "Guyliann Engels & Philippe Grosjean"
 description: "**SDD I** Découverte des tutoriels de type \"learnr\"."
 tutorial:
   id: "A00La_discovery"
-  version: 2.0.0/5
+  version: 3.0.0/5
 output:
   learnr::tutorial:
     progressive: true
@@ -42,36 +42,13 @@ library(SciViews)
 library(readxl)
 library(testthat)
 library(equatags)
-
 ```
 
 ```{r, echo=FALSE}
 BioDataScience1::learnr_banner()
 ```
 
 ```{r, context="server"}
-#observe({
-#  session_user <- session$user
-#  if (!is.null(session_user) && session_user != "rstudio-connect") {
-#    # Get more data from the users database
-#    users <- try(mongolite::mongo("users", url = "mongodb://127.0.0.1/sdd"), silent = TRUE)
-#    if (inherits(users, "try-error"))
-#      message("Impossible to connect to the users database.")
-#    query <- paste0('{ "login": "', session_user, '" }')
-#    fields <- '{ "login": true, "email": true, "firstname": true, "lastname": true, "iemail": true, "iid": true, "ifirstname": true, "ilastname": true, "icourse": true, "ictitle": true, "iurl": true, "institution": true, "iref": true, "_id": false }'
-#    if (!users$count(query)) {
-#      message("User '", session_user, "' not found in the users table.")
-#      user_info <- list(login = session_user) # Minimal info...
-#    } else {
-#      user_info <- as.list(users$find(query, fields)[1L, ])
-#    }
-#    try(users$disconnect(), silent = TRUE)
-#  } else {# Try getting user data from the URL query string
-#    user_info <- parseQueryString(session$clientData$url_search)
-#  }
-#  options(learnitdown_learnr_user = user_info)
-#})
-#
 BioDataScience1::learnr_server(input, output, session)
 ```
 

inst/tutorials/A01La_base/A01La_base.Rmd

@@ -4,7 +4,7 @@ author : "Guyliann Engels & Philippe Grosjean"
 description: "**SDD I Module 1** Les bases de l'utilisation de R."
 tutorial:
   id: "A01La_base"
-  version: 2.0.1/7
+  version: 3.0.0/7
 output: 
   learnr::tutorial:
     progressive: true
@@ -15,6 +15,33 @@ runtime: shiny_prerendered
 ```{r setup, include=FALSE}
 BioDataScience1::learnr_setup()
 SciViews::R()
+# Required for RSConnect
+# SciViews::R
+library(rlang)
+library(data.table)
+library(ggplot2)
+library(tibble)
+library(tidyr)
+library(dplyr)
+library(dtplyr)
+library(broom)
+library(forcats)
+library(collapse)
+library(fs)
+library(data.trame)
+library(svFast)
+library(svTidy)
+library(svMisc)
+library(svBase)
+library(svFlow)
+library(data.io)
+library(chart)
+library(tabularise)
+library(SciViews)
+# ...more
+library(readxl)
+library(testthat)
+library(equatags)
 ```
 
 ```{r, echo=FALSE}

inst/tutorials/A01Lb_scatterplot/A01Lb_scatterplot.Rmd

@@ -4,7 +4,7 @@ author : "Guyliann Engels & Philippe Grosjean"
 description: "**SDD I Module 1** Réalisation de graphiques en nuage de points."
 tutorial:
   id: "A01Lb_scatterplot"
-  version: 2.5.0/6
+  version: 3.0.0/6
 output:
   learnr::tutorial:
     progressive: true
@@ -16,6 +16,33 @@ runtime: shiny_prerendered
 ```{r setup, include=FALSE}
 BioDataScience1::learnr_setup()
 SciViews::R(lang = "fr")
+# Required for RSConnect
+# SciViews::R
+library(rlang)
+library(data.table)
+library(ggplot2)
+library(tibble)
+library(tidyr)
+library(dplyr)
+library(dtplyr)
+library(broom)
+library(forcats)
+library(collapse)
+library(fs)
+library(data.trame)
+library(svFast)
+library(svTidy)
+library(svMisc)
+library(svBase)
+library(svFlow)
+library(data.io)
+library(chart)
+library(tabularise)
+library(SciViews)
+# ... more
+library(readxl)
+library(testthat)
+library(equatags)
 # Dataset
 urchin <- read(file = "urchin_bio", package = "data.io")
 ```
@@ -69,7 +96,7 @@ chart(data = urchin, height ~ weight) +
 
 ## Retour sur la vidéo
 
-Commencez par réaliser les graphiques vus durant la capsule vidéo.
+Commencez par réaliser les graphiques vus dans la capsule vidéo du cours.
 
 ### Exercice 1
 
@@ -285,7 +312,8 @@ a <- chart(data = urchin, height ~ weight %col=% origin) +
 b <- chart(data = urchin, log(height) ~ log(weight) %col=% origin) +
   geom_point()
 
-combine_charts(list(a, b), labels = NULL, common.legend = TRUE, legend = "right")
+# partial arguments matching: leg$height instead of leg$heights and leg$width instead of leg$widths in ggpubr::.plot_grid()
+suppressWarnings(combine_charts(list(a, b), labels = NULL, common.legend = TRUE, legend = "right"))
 ```
 
 Réalisez par vous-mêmes le graphique de droite montrant le **logarithme de la hauteur** en ordonnée et le **logarithme de la masse** en abscisse. Utilisez la couleur pour différencier l'origine des individus.