From 3f3332c96b45e89cd5a8ac1b4274f2ee35f29da5 Mon Sep 17 00:00:00 2001
From: Nikolay Nikolaev <nikolay.borislavov@gmail.com>
Date: Sun, 21 Jan 2024 10:22:57 +0100
Subject: [PATCH] Add Maxi Zeug

---
 tutorial_page.Rmd                             | 122 ++++-
 tutorial_page.html                            | 500 ++++++++++++++++--
 tutorial_page_files/figure-html/barplot-1.png | Bin 0 -> 13758 bytes
 tutorial_page_files/figure-html/ggplot-1.png  | Bin 0 -> 14166 bytes
 tutorial_page_files/figure-html/plot-1.png    | Bin 0 -> 16341 bytes
 5 files changed, 565 insertions(+), 57 deletions(-)
 create mode 100644 tutorial_page_files/figure-html/barplot-1.png
 create mode 100644 tutorial_page_files/figure-html/ggplot-1.png
 create mode 100644 tutorial_page_files/figure-html/plot-1.png

diff --git a/tutorial_page.Rmd b/tutorial_page.Rmd
index a8883f8..68445c8 100644
--- a/tutorial_page.Rmd
+++ b/tutorial_page.Rmd
@@ -7,6 +7,7 @@ runtime: shiny_prerendered
 ```{r setup, include=FALSE}
 library(learnr)
 library(readxl)
+library("ggplot2")
 options(scipen = 10)
 gameData <- read_excel("bgg_dataset.xlsx", sheet = "Sheet")
 knitr::opts_chunk$set(echo = FALSE)
@@ -93,9 +94,18 @@ Nur eine Spalte aus dem Datensatz lässt sich wie folgt lesen:
 gameData$`Year Published`
 ```
 
-You can swap `Year Published` with every column if the set and try it out!
+#### Zeit zum üben! 
+Schreiben Sie den Code, um die Spalte `Mechanics`zu lesen:
 
-Wie du weitere Dateientypen einlesen und benutzen kannst, findest du in diesem [Tutorial von Björn Walther](https://bjoernwalther.com/daten-in-r-importieren/).
+```{r read-mechanics-column, exercise=TRUE}
+
+```
+```{r read-mechanics-column-hint}
+gameData$`Mechanics`
+
+```
+
+Wie Sie weitere Dateientypen einlesen und benutzen kannst, finden Sie in diesem [Tutorial von Björn Walther](https://bjoernwalther.com/daten-in-r-importieren/).
 
 ### Leerstellen beheben
 
@@ -167,7 +177,7 @@ Dieser Befehl entfernt Sonderzeichen in der Spalte "Mechanics".
 
 Diese Beispiele sind allgemeiner Natur, und Sie sollten sie an Ihre spezifischen Daten und Probleme anpassen. Inkonsistenzen und Leerstellen können in verschiedenen Formen auftreten, und es ist wichtig, die geeigneten Methoden für Ihre speziellen Daten anzuwenden. Beachten Sie auch, dass Datenbereinigung oft datenabhängig ist, und eine gründliche Analyse der Daten ist vor der Bereinigung ratsam.
 
-### Jetzt bist du dran! Teste was du in diesem Abschnitt über Daten einlesen gelernt hast:
+### Jetzt sind Sie dran! Testen Sie was Sie in diesem Abschnitt über Daten einlesen gelernt haben:
 
 ```{r second-quiz}
 quiz(
@@ -317,10 +327,114 @@ quiz(
 
 
 ## Ergebnispräsentation
+In diesem Kapitel beschäftigen wir uns mit ausgewählten grafischen Darstellungsmöglichkeiten von Daten und wie man diese in RStudio erstellen kann.
 
 ### Streudiagramm
+Ein Steudiagramm wird häufig verwendet, um einen Zusammenhang zwischen Variablen darzustellen. In RStudio kann man mit Hilfe des plot()-Befehls ein solches Streudiagramm erzeugen. 
+Hier ein Beispiel:
+
+```{r plot}
+plot(gameData[["Year Published"]],gameData[["ID"]],ylab="ID des Spiels", xlab="Veröffentlichung des Spiels", main="Zusammenhang ID und Erstveröffentlichung eines Spiels",xlim=c(1960,2024))
+
+```
+\
+Der Code für dieses Streudiagramms ist grob zusammengefasst: 
+\
+\
+**plot(gameData[["xxx"]],gameData[["yyy"]],xlim=c(a,z))**
+\
+\
+Enthalten sind hier drei Parameter, die beiden Variablen und eine Begrenzung. Wobei xlim eine Begrenzung der x-Achse, und damit die Begrenzung der Werte von "xxx" darstellt, um ein genaueres Bild zu erhalten.
+\
+\
+\
+\
+Erstellen Sie nun anhand des Beispiels ein einfaches Streudiagramm welches den Zusammenhang zwischen "Min Age" und "Complexity Average" darstellt:
+```{r plotExercise, exercise=TRUE}
+
+```
+```{r plotExercise-hint}
+plot(gameData[["Complexity Average"]],gameData[["Min Age"]])
+
+```
+\
+\
+
+### Boxplot-Diagramm
+Ein Boxplot ist ein Diagramm, dass verschiedene Lageparameter und Streuparameter abbildet und damit einen ersten groben Überblick über eine Verteilung gibt. Meistens verwendet man einen Boxplot um schnell eine Übersicht über Median, Quartile, Minimal- und Maximalwerte sowie Ausreißer zu erhalten.
+\
+Folgend ein Beispiel:
+```{r ggplot}
+ggplot(gameData, aes(y = .data[["Play Time"]], group = .data[["Year Published"]], x = .data[["Year Published"]])) + geom_boxplot() + coord_cartesian(xlim = c(2000, 2020))
+
+```
+\
+\
+Anhand des Beispiels nun ein kleines Quiz zur Verdeutlichung der Begrifflichkeiten: \
+```{r quiz-ggplot}
+quiz(
+  question("Was ist der Median im Diagramm?",
+    answer("ein vertikaler Strich"),
+    answer("die Höhe der Box"),
+    answer("ein horizontaler Strich in der Mitter der Box", correct = TRUE),
+    answer("das untere Ende der Box")),
+  
+  question("Was sind die Quartile im Diagramm?(Es sind mehrere Antworten möglich)",
+    answer("das obere Ende der Box", correct = TRUE),
+    answer("Punkte oberhalb der Box"),
+    answer("ein Drittel des vertikalen Strichs"),
+    answer("das untere Ende der Box", correct = TRUE)),
+  
+  question("Was sind die Maximalwerte im Diagramm?",
+    answer("Punkte oberhalb der Box"),
+    answer("die Spitzen des vertikalen Strichs", correct = TRUE),
+    answer("die x-Achse und die y-Achse"),
+    answer("die Flaeche der Box")
+  ),
+  question("An was erkennt man im Diagramm die Ausreißer?",
+    answer("es sind Punkte außerhalb der Box", correct = TRUE),
+    answer("an der Größe der Box"),
+    answer("durch schlechtes Verhalten")
+  
+  )
+)
+```
+\
+\
+Um ein Boxplot-Diagramm zu erstellen, muss man das ggplot2-package installiert haben, der grobe Syntax fürs Diagramm selbst sieht wiefolgt aus:
+\
+**ggplot(gameData, aes(y = .data[["xxx"]], group = .data[["yyy"]], x = .data[["yyy"]])) + geom_boxplot()**
+\
+\
+\
+\
+
+### Säulendiagramme
+Das bekannte Säulendiagramm wird meistens verwendet um eine Veränderung im Laufe der Zeit zu zeigen. Mit Säulendiagrammen kann man Steigerung, Rückgang, Stagnation als auch eine Häufigkeitsverteilung deutlich zeigen. Um ein Säulendiagramm in R mit Häufigkeitsverteilung zu erhalten, gibt man den Befehl:
+\
+\
+**barplot(table(gameData[["xxx"]])** ein und kann um die Achsen näher zu beschreiben noch **xlab=""** und **ylab=""** einfügen.
+\
+\
+Folgend ein Beispiel für ein Säulendiagramm mit Häufigkeitsverteilung:
+\
+```{r barplot}
+barplot(table(gameData[["Min Age"]]), xlab = "Altersfreigabe" , ylab = "Häufigkeit", 
+        main = "Häufigkeit der Altersfreigaben" )
+```
+\
+\
+Geben Sie nun ein Säulendiagramm mit den Werten von "Complexity Average" und Achsenbeschriftung aus:
+\
+```{r barplotExercise, exercise=TRUE}
+
+
+```
+```{r barplotExercise-hint}
+barplot(gameData[["Complexity Average"]], xlab = "Spiel" , ylab = "Score")
+
+```
 
-### Kein Plan
 
 ## Teaminfos
 
diff --git a/tutorial_page.html b/tutorial_page.html
index 0566a86..29b0d8c 100644
--- a/tutorial_page.html
+++ b/tutorial_page.html
@@ -225,9 +225,23 @@ data-lines="0" data-pipe="|&gt;">
 <pre class="text"><code>gameData$`Year Published`</code></pre>
 <script type="application/json" data-ui-opts="1">{"engine":"r","has_checker":false,"caption":"<span data-i18n=\"text.enginecap\" data-i18n-opts=\"{&quot;engine&quot;:&quot;R&quot;}\">R Code<\/span>"}</script>
 </div>
-<p>You can swap <code>Year Published</code> with every column if the set
-and try it out!</p>
-<p>Wie du weitere Dateientypen einlesen und benutzen kannst, findest du
+</div>
+<div id="section-zeit-zum-üben" class="section level4">
+<h4>Zeit zum üben!</h4>
+<p>Schreiben Sie den Code, um die Spalte <code>Mechanics</code>zu
+lesen:</p>
+<div class="tutorial-exercise" data-label="read-mechanics-column"
+data-completion="1" data-diagnostics="1" data-startover="1"
+data-lines="0" data-pipe="|&gt;">
+<script type="application/json" data-ui-opts="1">{"engine":"r","has_checker":false,"caption":"<span data-i18n=\"text.enginecap\" data-i18n-opts=\"{&quot;engine&quot;:&quot;R&quot;}\">R Code<\/span>"}</script>
+</div>
+<div class="tutorial-exercise-support"
+data-label="read-mechanics-column-hint" data-completion="1"
+data-diagnostics="1" data-startover="1" data-lines="0"
+data-pipe="|&gt;">
+<pre class="text"><code>gameData$`Mechanics`</code></pre>
+</div>
+<p>Wie Sie weitere Dateientypen einlesen und benutzen kannst, finden Sie
 in diesem <a
 href="https://bjoernwalther.com/daten-in-r-importieren/">Tutorial von
 Björn Walther</a>.</p>
@@ -331,10 +345,10 @@ Analyse der Daten ist vor der Bereinigung ratsam.</p>
 </div>
 </div>
 <div
-id="section-jetzt-bist-du-dran-teste-was-du-in-diesem-abschnitt-über-daten-einlesen-gelernt-hast"
+id="section-jetzt-sind-sie-dran-testen-sie-was-sie-in-diesem-abschnitt-über-daten-einlesen-gelernt-haben"
 class="section level3">
-<h3>Jetzt bist du dran! Teste was du in diesem Abschnitt über Daten
-einlesen gelernt hast:</h3>
+<h3>Jetzt sind Sie dran! Testen Sie was Sie in diesem Abschnitt über
+Daten einlesen gelernt haben:</h3>
 <div class="panel-heading tutorial-quiz-title"><span data-i18n="text.quiz">Quiz</span></div>
 <div class="panel panel-default tutorial-question-container">
 <div data-label="second-quiz-1" class="tutorial-question panel-body">
@@ -529,11 +543,131 @@ beweisen oder widerlegen.<br />
 </div>
 <div id="section-ergebnispräsentation" class="section level2">
 <h2>Ergebnispräsentation</h2>
+<p>In diesem Kapitel beschäftigen wir uns mit ausgewählten grafischen
+Darstellungsmöglichkeiten von Daten und wie man diese in RStudio
+erstellen kann.</p>
 <div id="section-streudiagramm" class="section level3">
 <h3>Streudiagramm</h3>
+<p>Ein Steudiagramm wird häufig verwendet, um einen Zusammenhang
+zwischen Variablen darzustellen. In RStudio kann man mit Hilfe des
+plot()-Befehls ein solches Streudiagramm erzeugen. Hier ein
+Beispiel:</p>
+<img src="tutorial_page_files/figure-html/plot-1.png" width="624" /><br />
+Der Code für dieses Streudiagramms ist grob zusammengefasst:<br />
+<br />
+<strong>plot(gameData[[“xxx”]],gameData[[“yyy”]],xlim=c(a,z))</strong><br />
+<br />
+Enthalten sind hier drei Parameter, die beiden Variablen und eine
+Begrenzung. Wobei xlim eine Begrenzung der x-Achse, und damit die
+Begrenzung der Werte von “xxx” darstellt, um ein genaueres Bild zu
+erhalten.<br />
+<br />
+<br />
+<br />
+Erstellen Sie nun anhand des Beispiels ein einfaches Streudiagramm
+welches den Zusammenhang zwischen “Min Age” und “Complexity Average”
+darstellt:
+<div class="tutorial-exercise" data-label="plotExercise"
+data-completion="1" data-diagnostics="1" data-startover="1"
+data-lines="0" data-pipe="|&gt;">
+<script type="application/json" data-ui-opts="1">{"engine":"r","has_checker":false,"caption":"<span data-i18n=\"text.enginecap\" data-i18n-opts=\"{&quot;engine&quot;:&quot;R&quot;}\">R Code<\/span>"}</script>
+</div>
+<div class="tutorial-exercise-support" data-label="plotExercise-hint"
+data-completion="1" data-diagnostics="1" data-startover="1"
+data-lines="0" data-pipe="|&gt;">
+<pre class="text"><code>plot(gameData[[&quot;Complexity Average&quot;]],gameData[[&quot;Min Age&quot;]])</code></pre>
+</div>
+<p><br />
+<br />
+</p>
+</div>
+<div id="section-boxplot-diagramm" class="section level3">
+<h3>Boxplot-Diagramm</h3>
+<p>Ein Boxplot ist ein Diagramm, dass verschiedene Lageparameter und
+Streuparameter abbildet und damit einen ersten groben Überblick über
+eine Verteilung gibt. Meistens verwendet man einen Boxplot um schnell
+eine Übersicht über Median, Quartile, Minimal- und Maximalwerte sowie
+Ausreißer zu erhalten.<br />
+Folgend ein Beispiel:
+<img src="tutorial_page_files/figure-html/ggplot-1.png" width="624" /><br />
+<br />
+Anhand des Beispiels nun ein kleines Quiz zur Verdeutlichung der
+Begrifflichkeiten:<br />
+</p>
+<div class="panel-heading tutorial-quiz-title"><span data-i18n="text.quiz">Quiz</span></div>
+<div class="panel panel-default tutorial-question-container">
+<div data-label="quiz-ggplot-1" class="tutorial-question panel-body">
+<div id="quiz-ggplot-1-answer_container" class="shiny-html-output"></div>
+<div id="quiz-ggplot-1-message_container" class="shiny-html-output"></div>
+<div id="quiz-ggplot-1-action_button_container" class="shiny-html-output"></div>
+<script>if (Tutorial.triggerMathJax) Tutorial.triggerMathJax()</script>
+</div>
+</div>
+<div class="panel panel-default tutorial-question-container">
+<div data-label="quiz-ggplot-2" class="tutorial-question panel-body">
+<div id="quiz-ggplot-2-answer_container" class="shiny-html-output"></div>
+<div id="quiz-ggplot-2-message_container" class="shiny-html-output"></div>
+<div id="quiz-ggplot-2-action_button_container" class="shiny-html-output"></div>
+<script>if (Tutorial.triggerMathJax) Tutorial.triggerMathJax()</script>
+</div>
+</div>
+<div class="panel panel-default tutorial-question-container">
+<div data-label="quiz-ggplot-3" class="tutorial-question panel-body">
+<div id="quiz-ggplot-3-answer_container" class="shiny-html-output"></div>
+<div id="quiz-ggplot-3-message_container" class="shiny-html-output"></div>
+<div id="quiz-ggplot-3-action_button_container" class="shiny-html-output"></div>
+<script>if (Tutorial.triggerMathJax) Tutorial.triggerMathJax()</script>
+</div>
+</div>
+<div class="panel panel-default tutorial-question-container">
+<div data-label="quiz-ggplot-4" class="tutorial-question panel-body">
+<div id="quiz-ggplot-4-answer_container" class="shiny-html-output"></div>
+<div id="quiz-ggplot-4-message_container" class="shiny-html-output"></div>
+<div id="quiz-ggplot-4-action_button_container" class="shiny-html-output"></div>
+<script>if (Tutorial.triggerMathJax) Tutorial.triggerMathJax()</script>
+</div>
+</div>
+<p><br />
+<br />
+Um ein Boxplot-Diagramm zu erstellen, muss man das ggplot2-package
+installiert haben, der grobe Syntax fürs Diagramm selbst sieht wiefolgt
+aus:<br />
+<strong>ggplot(gameData, aes(y = .data[[“xxx”]], group = .data[[“yyy”]],
+x = .data[[“yyy”]])) + geom_boxplot()</strong><br />
+<br />
+<br />
+<br />
+</p>
+</div>
+<div id="section-säulendiagramme" class="section level3">
+<h3>Säulendiagramme</h3>
+Das bekannte Säulendiagramm wird meistens verwendet um eine Veränderung
+im Laufe der Zeit zu zeigen. Mit Säulendiagrammen kann man Steigerung,
+Rückgang, Stagnation als auch eine Häufigkeitsverteilung deutlich
+zeigen. Um ein Säulendiagramm in R mit Häufigkeitsverteilung zu
+erhalten, gibt man den Befehl:<br />
+<br />
+<strong>barplot(table(gameData[[“xxx”]])</strong> ein und kann um die
+Achsen näher zu beschreiben noch **xlab=““** und
+<strong>ylab=””</strong> einfügen.<br />
+<br />
+Folgend ein Beispiel für ein Säulendiagramm mit
+Häufigkeitsverteilung:<br />
+<img src="tutorial_page_files/figure-html/barplot-1.png" width="624" /><br />
+<br />
+Geben Sie nun ein Säulendiagramm mit den Werten von”Complexity Average”
+und Achsenbeschriftung aus:<br />
+
+<div class="tutorial-exercise" data-label="barplotExercise"
+data-completion="1" data-diagnostics="1" data-startover="1"
+data-lines="0" data-pipe="|&gt;">
+<script type="application/json" data-ui-opts="1">{"engine":"r","has_checker":false,"caption":"<span data-i18n=\"text.enginecap\" data-i18n-opts=\"{&quot;engine&quot;:&quot;R&quot;}\">R Code<\/span>"}</script>
+</div>
+<div class="tutorial-exercise-support" data-label="barplotExercise-hint"
+data-completion="1" data-diagnostics="1" data-startover="1"
+data-lines="0" data-pipe="|&gt;">
+<pre class="text"><code>barplot(gameData[[&quot;Complexity Average&quot;]], xlab = &quot;Spiel&quot; , ylab = &quot;Score&quot;)</code></pre>
 </div>
-<div id="section-kein-plan" class="section level3">
-<h3>Kein Plan</h3>
 </div>
 </div>
 <div id="section-teaminfos" class="section level2">
@@ -550,6 +684,7 @@ beweisen oder widerlegen.<br />
 <script type="application/shiny-prerendered" data-context="server-start">
 library(learnr)
 library(readxl)
+library("ggplot2")
 options(scipen = 10)
 gameData <- read_excel("bgg_dataset.xlsx", sheet = "Sheet")
 knitr::opts_chunk$set(echo = FALSE)
@@ -585,7 +720,8 @@ output$`tutorial-exercise-install-readxl-output` <- renderUI({
 
 <script type="application/shiny-prerendered" data-context="server">
 learnr:::store_exercise_cache(structure(list(label = "install-readxl", global_setup = structure(c("library(learnr)", 
-"library(readxl)", "options(scipen = 10)", "gameData <- read_excel(\"bgg_dataset.xlsx\", sheet = \"Sheet\")", 
+"library(readxl)", "library(\"ggplot2\")", "options(scipen = 10)", 
+"gameData <- read_excel(\"bgg_dataset.xlsx\", sheet = \"Sheet\")", 
 "knitr::opts_chunk$set(echo = FALSE)"), chunk_opts = list(label = "setup", 
     include = FALSE)), setup = NULL, chunks = list(list(label = "install-readxl", 
     code = "install.packages(\"readxl\")\nlibrary (readxl)", 
@@ -625,7 +761,8 @@ output$`tutorial-exercise-read-data-output` <- renderUI({
 
 <script type="application/shiny-prerendered" data-context="server">
 learnr:::store_exercise_cache(structure(list(label = "read-data", global_setup = structure(c("library(learnr)", 
-"library(readxl)", "options(scipen = 10)", "gameData <- read_excel(\"bgg_dataset.xlsx\", sheet = \"Sheet\")", 
+"library(readxl)", "library(\"ggplot2\")", "options(scipen = 10)", 
+"gameData <- read_excel(\"bgg_dataset.xlsx\", sheet = \"Sheet\")", 
 "knitr::opts_chunk$set(echo = FALSE)"), chunk_opts = list(label = "setup", 
     include = FALSE)), setup = NULL, chunks = list(list(label = "read-data", 
     code = "gameData <- read_excel(\"bgg_dataset.xlsx\", sheet = \"Sheet\")", 
@@ -665,7 +802,8 @@ output$`tutorial-exercise-show-data-output` <- renderUI({
 
 <script type="application/shiny-prerendered" data-context="server">
 learnr:::store_exercise_cache(structure(list(label = "show-data", global_setup = structure(c("library(learnr)", 
-"library(readxl)", "options(scipen = 10)", "gameData <- read_excel(\"bgg_dataset.xlsx\", sheet = \"Sheet\")", 
+"library(readxl)", "library(\"ggplot2\")", "options(scipen = 10)", 
+"gameData <- read_excel(\"bgg_dataset.xlsx\", sheet = \"Sheet\")", 
 "knitr::opts_chunk$set(echo = FALSE)"), chunk_opts = list(label = "setup", 
     include = FALSE)), setup = NULL, chunks = list(list(label = "show-data", 
     code = "gameData", opts = list(label = "\"show-data\"", exercise = "TRUE"), 
@@ -704,7 +842,8 @@ output$`tutorial-exercise-read-column-output` <- renderUI({
 
 <script type="application/shiny-prerendered" data-context="server">
 learnr:::store_exercise_cache(structure(list(label = "read-column", global_setup = structure(c("library(learnr)", 
-"library(readxl)", "options(scipen = 10)", "gameData <- read_excel(\"bgg_dataset.xlsx\", sheet = \"Sheet\")", 
+"library(readxl)", "library(\"ggplot2\")", "options(scipen = 10)", 
+"gameData <- read_excel(\"bgg_dataset.xlsx\", sheet = \"Sheet\")", 
 "knitr::opts_chunk$set(echo = FALSE)"), chunk_opts = list(label = "setup", 
     include = FALSE)), setup = NULL, chunks = list(list(label = "read-column", 
     code = "gameData$`Year Published`", opts = list(label = "\"read-column\"", 
@@ -734,6 +873,46 @@ learnr:::store_exercise_cache(structure(list(label = "read-column", global_setup
 )))
 </script>
  
+<script type="application/shiny-prerendered" data-context="server">
+`tutorial-exercise-read-mechanics-column-result` <- learnr:::setup_exercise_handler(reactive(req(input$`tutorial-exercise-read-mechanics-column-code-editor`)), session)
+output$`tutorial-exercise-read-mechanics-column-output` <- renderUI({
+  `tutorial-exercise-read-mechanics-column-result`()
+})
+</script>
+
+
+<script type="application/shiny-prerendered" data-context="server">
+learnr:::store_exercise_cache(structure(list(label = "read-mechanics-column", global_setup = structure(c("library(learnr)", 
+"library(readxl)", "library(\"ggplot2\")", "options(scipen = 10)", 
+"gameData <- read_excel(\"bgg_dataset.xlsx\", sheet = \"Sheet\")", 
+"knitr::opts_chunk$set(echo = FALSE)"), chunk_opts = list(label = "setup", 
+    include = FALSE)), setup = NULL, chunks = list(list(label = "read-mechanics-column", 
+    code = "", opts = list(label = "\"read-mechanics-column\"", 
+        exercise = "TRUE"), engine = "r")), code_check = NULL, 
+    error_check = NULL, check = NULL, solution = NULL, tests = NULL, 
+    options = list(eval = FALSE, echo = TRUE, results = "markup", 
+        tidy = FALSE, tidy.opts = NULL, collapse = FALSE, prompt = FALSE, 
+        comment = NA, highlight = FALSE, size = "normalsize", 
+        background = "#F7F7F7", strip.white = TRUE, cache = 0, 
+        cache.path = "tutorial_page_cache/html/", cache.vars = NULL, 
+        cache.lazy = TRUE, dependson = NULL, autodep = FALSE, 
+        cache.rebuild = FALSE, fig.keep = "high", fig.show = "asis", 
+        fig.align = "default", fig.path = "tutorial_page_files/figure-html/", 
+        dev = "png", dev.args = NULL, dpi = 192, fig.ext = "png", 
+        fig.width = 6.5, fig.height = 4, fig.env = "figure", 
+        fig.cap = NULL, fig.scap = NULL, fig.lp = "fig:", fig.subcap = NULL, 
+        fig.pos = "", out.width = 624, out.height = NULL, out.extra = NULL, 
+        fig.retina = 2, external = TRUE, sanitize = FALSE, interval = 1, 
+        aniopts = "controls,loop", warning = TRUE, error = FALSE, 
+        message = TRUE, render = NULL, ref.label = NULL, child = NULL, 
+        engine = "r", split = FALSE, include = TRUE, purl = TRUE, 
+        max.print = 1000, label = "read-mechanics-column", exercise = TRUE, 
+        code = "", out.width.px = 624, out.height.px = 384, params.src = "read-mechanics-column, exercise=TRUE", 
+        fig.num = 0L, exercise.df_print = "paged", exercise.checker = "NULL"), 
+    engine = "r", version = "4"), class = c("r", "tutorial_exercise"
+)))
+</script>
+ 
 <script type="application/shiny-prerendered" data-context="server">
 `tutorial-exercise-remove-empties-column-result` <- learnr:::setup_exercise_handler(reactive(req(input$`tutorial-exercise-remove-empties-column-code-editor`)), session)
 output$`tutorial-exercise-remove-empties-column-output` <- renderUI({
@@ -744,7 +923,8 @@ output$`tutorial-exercise-remove-empties-column-output` <- renderUI({
 
 <script type="application/shiny-prerendered" data-context="server">
 learnr:::store_exercise_cache(structure(list(label = "remove-empties-column", global_setup = structure(c("library(learnr)", 
-"library(readxl)", "options(scipen = 10)", "gameData <- read_excel(\"bgg_dataset.xlsx\", sheet = \"Sheet\")", 
+"library(readxl)", "library(\"ggplot2\")", "options(scipen = 10)", 
+"gameData <- read_excel(\"bgg_dataset.xlsx\", sheet = \"Sheet\")", 
 "knitr::opts_chunk$set(echo = FALSE)"), chunk_opts = list(label = "setup", 
     include = FALSE)), setup = NULL, chunks = list(list(label = "remove-empties-column", 
     code = "gameData$`Year Published` <- trimws(gameData$`Year Published`)\ngameData$`Year Published`", 
@@ -785,7 +965,8 @@ output$`tutorial-exercise-remove-empties-output` <- renderUI({
 
 <script type="application/shiny-prerendered" data-context="server">
 learnr:::store_exercise_cache(structure(list(label = "remove-empties", global_setup = structure(c("library(learnr)", 
-"library(readxl)", "options(scipen = 10)", "gameData <- read_excel(\"bgg_dataset.xlsx\", sheet = \"Sheet\")", 
+"library(readxl)", "library(\"ggplot2\")", "options(scipen = 10)", 
+"gameData <- read_excel(\"bgg_dataset.xlsx\", sheet = \"Sheet\")", 
 "knitr::opts_chunk$set(echo = FALSE)"), chunk_opts = list(label = "setup", 
     include = FALSE)), setup = NULL, chunks = list(list(label = "remove-empties", 
     code = "gameData <- lapply(gameData, trimws)\ngameData", 
@@ -825,7 +1006,8 @@ output$`tutorial-exercise-to-lowercase-column-output` <- renderUI({
 
 <script type="application/shiny-prerendered" data-context="server">
 learnr:::store_exercise_cache(structure(list(label = "to-lowercase-column", global_setup = structure(c("library(learnr)", 
-"library(readxl)", "options(scipen = 10)", "gameData <- read_excel(\"bgg_dataset.xlsx\", sheet = \"Sheet\")", 
+"library(readxl)", "library(\"ggplot2\")", "options(scipen = 10)", 
+"gameData <- read_excel(\"bgg_dataset.xlsx\", sheet = \"Sheet\")", 
 "knitr::opts_chunk$set(echo = FALSE)"), chunk_opts = list(label = "setup", 
     include = FALSE)), setup = NULL, chunks = list(list(label = "to-lowercase-column", 
     code = "gameData$`Mechanics` <- tolower(gameData$`Mechanics`)\ngameData$`Mechanics`", 
@@ -866,7 +1048,8 @@ output$`tutorial-exercise-replace-variable-output` <- renderUI({
 
 <script type="application/shiny-prerendered" data-context="server">
 learnr:::store_exercise_cache(structure(list(label = "replace-variable", global_setup = structure(c("library(learnr)", 
-"library(readxl)", "options(scipen = 10)", "gameData <- read_excel(\"bgg_dataset.xlsx\", sheet = \"Sheet\")", 
+"library(readxl)", "library(\"ggplot2\")", "options(scipen = 10)", 
+"gameData <- read_excel(\"bgg_dataset.xlsx\", sheet = \"Sheet\")", 
 "knitr::opts_chunk$set(echo = FALSE)"), chunk_opts = list(label = "setup", 
     include = FALSE)), setup = NULL, chunks = list(list(label = "replace-variable", 
     code = "gameData$`Mechanics` <- gsub(\"Action\", \"ACTION\", gameData$`Mechanics`)\ngameData$`Mechanics`", 
@@ -907,7 +1090,8 @@ output$`tutorial-exercise-replace-missing-variable-output` <- renderUI({
 
 <script type="application/shiny-prerendered" data-context="server">
 learnr:::store_exercise_cache(structure(list(label = "replace-missing-variable", global_setup = structure(c("library(learnr)", 
-"library(readxl)", "options(scipen = 10)", "gameData <- read_excel(\"bgg_dataset.xlsx\", sheet = \"Sheet\")", 
+"library(readxl)", "library(\"ggplot2\")", "options(scipen = 10)", 
+"gameData <- read_excel(\"bgg_dataset.xlsx\", sheet = \"Sheet\")", 
 "knitr::opts_chunk$set(echo = FALSE)"), chunk_opts = list(label = "setup", 
     include = FALSE)), setup = NULL, chunks = list(list(label = "replace-missing-variable", 
     code = "gameData$`Rating Average`[is.na(gameData$`Rating Average`)] <- mean(gameData$`Rating Average`, na.rm = TRUE)", 
@@ -947,7 +1131,8 @@ output$`tutorial-exercise-remove-duplicates-output` <- renderUI({
 
 <script type="application/shiny-prerendered" data-context="server">
 learnr:::store_exercise_cache(structure(list(label = "remove-duplicates", global_setup = structure(c("library(learnr)", 
-"library(readxl)", "options(scipen = 10)", "gameData <- read_excel(\"bgg_dataset.xlsx\", sheet = \"Sheet\")", 
+"library(readxl)", "library(\"ggplot2\")", "options(scipen = 10)", 
+"gameData <- read_excel(\"bgg_dataset.xlsx\", sheet = \"Sheet\")", 
 "knitr::opts_chunk$set(echo = FALSE)"), chunk_opts = list(label = "setup", 
     include = FALSE)), setup = NULL, chunks = list(list(label = "remove-duplicates", 
     code = "gameData <- unique(gameData)", opts = list(label = "\"remove-duplicates\"", 
@@ -987,7 +1172,8 @@ output$`tutorial-exercise-replace-special-chars-output` <- renderUI({
 
 <script type="application/shiny-prerendered" data-context="server">
 learnr:::store_exercise_cache(structure(list(label = "replace-special-chars", global_setup = structure(c("library(learnr)", 
-"library(readxl)", "options(scipen = 10)", "gameData <- read_excel(\"bgg_dataset.xlsx\", sheet = \"Sheet\")", 
+"library(readxl)", "library(\"ggplot2\")", "options(scipen = 10)", 
+"gameData <- read_excel(\"bgg_dataset.xlsx\", sheet = \"Sheet\")", 
 "knitr::opts_chunk$set(echo = FALSE)"), chunk_opts = list(label = "setup", 
     include = FALSE)), setup = NULL, chunks = list(list(label = "replace-special-chars", 
     code = "gameData$`Mechanics` <- gsub(\"[^a-zA-Z0-9 ]\", \"\", gameData$`Mechanics`)", 
@@ -1020,19 +1206,19 @@ learnr:::store_exercise_cache(structure(list(label = "replace-special-chars", gl
 <script type="application/shiny-prerendered" data-context="server">
 learnr:::question_prerendered_chunk(structure(list(type = "learnr_radio", label = "second-quiz-1", 
     question = structure("Mit welchem R-Befehl lassen sich Packages installieren?", html = TRUE, class = c("html", 
-    "character")), answers = list(structure(list(id = "lnr_ans_ca20291", 
+    "character")), answers = list(structure(list(id = "lnr_ans_fab16f", 
         option = "install.packages()", value = "install.packages()", 
         label = structure("install.packages()", html = TRUE, class = c("html", 
         "character")), correct = TRUE, message = NULL, type = "literal"), class = c("tutorial_question_answer", 
-    "tutorial_quiz_answer")), structure(list(id = "lnr_ans_d955cae", 
+    "tutorial_quiz_answer")), structure(list(id = "lnr_ans_dcc8b2f", 
         option = "add.packages()", value = "add.packages()", 
         label = structure("add.packages()", html = TRUE, class = c("html", 
         "character")), correct = FALSE, message = NULL, type = "literal"), class = c("tutorial_question_answer", 
-    "tutorial_quiz_answer")), structure(list(id = "lnr_ans_58176ef", 
+    "tutorial_quiz_answer")), structure(list(id = "lnr_ans_4bc2e8c", 
         option = "install.library()", value = "install.library()", 
         label = structure("install.library()", html = TRUE, class = c("html", 
         "character")), correct = FALSE, message = NULL, type = "literal"), class = c("tutorial_question_answer", 
-    "tutorial_quiz_answer")), structure(list(id = "lnr_ans_21ea4fa", 
+    "tutorial_quiz_answer")), structure(list(id = "lnr_ans_1b7cf71", 
         option = "install()", value = "install()", label = structure("install()", html = TRUE, class = c("html", 
         "character")), correct = FALSE, message = NULL, type = "literal"), class = c("tutorial_question_answer", 
     "tutorial_quiz_answer"))), button_labels = list(submit = structure("<span data-i18n=\"button.questionsubmit\">Submit Answer<\u002fspan>", html = TRUE, class = c("html", 
@@ -1043,7 +1229,7 @@ learnr:::question_prerendered_chunk(structure(list(type = "learnr_radio", label
     "character")), message = NULL, post_message = NULL), ids = list(
         answer = "second-quiz-1-answer", question = "second-quiz-1"), 
     loading = NULL, random_answer_order = FALSE, allow_retry = FALSE, 
-    seed = 1369528815.86226, options = list()), class = c("learnr_radio", 
+    seed = 494446241.269756, options = list()), class = c("learnr_radio", 
 "tutorial_question")), session = session)
 </script>
 
@@ -1051,16 +1237,16 @@ learnr:::question_prerendered_chunk(structure(list(type = "learnr_radio", label
 <script type="application/shiny-prerendered" data-context="server">
 learnr:::question_prerendered_chunk(structure(list(type = "learnr_radio", label = "second-quiz-2", 
     question = structure("Mit welchem R-Befehl lassen sich die installierten Packages initialisieren?", html = TRUE, class = c("html", 
-    "character")), answers = list(structure(list(id = "lnr_ans_39f493a", 
+    "character")), answers = list(structure(list(id = "lnr_ans_99fd8c3", 
         option = "use()", value = "use()", label = structure("use()", html = TRUE, class = c("html", 
         "character")), correct = FALSE, message = NULL, type = "literal"), class = c("tutorial_question_answer", 
-    "tutorial_quiz_answer")), structure(list(id = "lnr_ans_e9e5f27", 
+    "tutorial_quiz_answer")), structure(list(id = "lnr_ans_a6a1953", 
         option = "library()", value = "library()", label = structure("library()", html = TRUE, class = c("html", 
         "character")), correct = TRUE, message = NULL, type = "literal"), class = c("tutorial_question_answer", 
-    "tutorial_quiz_answer")), structure(list(id = "lnr_ans_e304c90", 
+    "tutorial_quiz_answer")), structure(list(id = "lnr_ans_9e0048e", 
         option = "init()", value = "init()", label = structure("init()", html = TRUE, class = c("html", 
         "character")), correct = FALSE, message = NULL, type = "literal"), class = c("tutorial_question_answer", 
-    "tutorial_quiz_answer")), structure(list(id = "lnr_ans_b76a78f", 
+    "tutorial_quiz_answer")), structure(list(id = "lnr_ans_b03b3ce", 
         option = "install.packages()", value = "install.packages()", 
         label = structure("install.packages()", html = TRUE, class = c("html", 
         "character")), correct = FALSE, message = NULL, type = "literal"), class = c("tutorial_question_answer", 
@@ -1072,23 +1258,23 @@ learnr:::question_prerendered_chunk(structure(list(type = "learnr_radio", label
     "character")), message = NULL, post_message = NULL), ids = list(
         answer = "second-quiz-2-answer", question = "second-quiz-2"), 
     loading = NULL, random_answer_order = FALSE, allow_retry = FALSE, 
-    seed = 1855370276.13603, options = list()), class = c("learnr_radio", 
+    seed = 973697199.046587, options = list()), class = c("learnr_radio", 
 "tutorial_question")), session = session)
 </script>
  
 <script type="application/shiny-prerendered" data-context="server">
 learnr:::question_prerendered_chunk(structure(list(type = "learnr_radio", label = "second-quiz-3", 
     question = structure("Welcher Packet benutzen wir, um XLSX-Dateien zu lesen?", html = TRUE, class = c("html", 
-    "character")), answers = list(structure(list(id = "lnr_ans_f44c779", 
+    "character")), answers = list(structure(list(id = "lnr_ans_955908", 
         option = "readxl()", value = "readxl()", label = structure("readxl()", html = TRUE, class = c("html", 
         "character")), correct = TRUE, message = NULL, type = "literal"), class = c("tutorial_question_answer", 
-    "tutorial_quiz_answer")), structure(list(id = "lnr_ans_4f8f5e", 
+    "tutorial_quiz_answer")), structure(list(id = "lnr_ans_efd8107", 
         option = "readxls()", value = "readxls()", label = structure("readxls()", html = TRUE, class = c("html", 
         "character")), correct = FALSE, message = NULL, type = "literal"), class = c("tutorial_question_answer", 
-    "tutorial_quiz_answer")), structure(list(id = "lnr_ans_c900e27", 
+    "tutorial_quiz_answer")), structure(list(id = "lnr_ans_f50fd5b", 
         option = "readexcel()", value = "readexcel()", label = structure("readexcel()", html = TRUE, class = c("html", 
         "character")), correct = FALSE, message = NULL, type = "literal"), class = c("tutorial_question_answer", 
-    "tutorial_quiz_answer")), structure(list(id = "lnr_ans_84c70ca", 
+    "tutorial_quiz_answer")), structure(list(id = "lnr_ans_1161587", 
         option = "excelread()", value = "excelread()", label = structure("excelread()", html = TRUE, class = c("html", 
         "character")), correct = FALSE, message = NULL, type = "literal"), class = c("tutorial_question_answer", 
     "tutorial_quiz_answer"))), button_labels = list(submit = structure("<span data-i18n=\"button.questionsubmit\">Submit Answer<\u002fspan>", html = TRUE, class = c("html", 
@@ -1099,7 +1285,7 @@ learnr:::question_prerendered_chunk(structure(list(type = "learnr_radio", label
     "character")), message = NULL, post_message = NULL), ids = list(
         answer = "second-quiz-3-answer", question = "second-quiz-3"), 
     loading = NULL, random_answer_order = FALSE, allow_retry = FALSE, 
-    seed = 1633355848.23941, options = list()), class = c("learnr_radio", 
+    seed = 214373947.900174, options = list()), class = c("learnr_radio", 
 "tutorial_question")), session = session)
 </script>
 
@@ -1107,19 +1293,19 @@ learnr:::question_prerendered_chunk(structure(list(type = "learnr_radio", label
 <script type="application/shiny-prerendered" data-context="server">
 learnr:::question_prerendered_chunk(structure(list(type = "learnr_radio", label = "second-quiz-4", 
     question = structure("Wie lassen sich einzelne Spalten aus dem Datensatz auslesen?", html = TRUE, class = c("html", 
-    "character")), answers = list(structure(list(id = "lnr_ans_90b8a0a", 
+    "character")), answers = list(structure(list(id = "lnr_ans_e0f3b5f", 
         option = "dataset&\\`column\\`", value = "dataset&\\`column\\`", 
         label = structure("dataset&amp;`column`", html = TRUE, class = c("html", 
         "character")), correct = FALSE, message = NULL, type = "literal"), class = c("tutorial_question_answer", 
-    "tutorial_quiz_answer")), structure(list(id = "lnr_ans_d19421d", 
+    "tutorial_quiz_answer")), structure(list(id = "lnr_ans_edcc894", 
         option = "column$dataset", value = "column$dataset", 
         label = structure("column$dataset", html = TRUE, class = c("html", 
         "character")), correct = FALSE, message = NULL, type = "literal"), class = c("tutorial_question_answer", 
-    "tutorial_quiz_answer")), structure(list(id = "lnr_ans_7ec7017", 
+    "tutorial_quiz_answer")), structure(list(id = "lnr_ans_27145ea", 
         option = "dataset%\\`column\\`", value = "dataset%\\`column\\`", 
         label = structure("dataset%`column`", html = TRUE, class = c("html", 
         "character")), correct = FALSE, message = NULL, type = "literal"), class = c("tutorial_question_answer", 
-    "tutorial_quiz_answer")), structure(list(id = "lnr_ans_1b15dce", 
+    "tutorial_quiz_answer")), structure(list(id = "lnr_ans_8066022", 
         option = "dataset$\\`column\\`", value = "dataset$\\`column\\`", 
         label = structure("dataset$`column`", html = TRUE, class = c("html", 
         "character")), correct = TRUE, message = NULL, type = "literal"), class = c("tutorial_question_answer", 
@@ -1131,7 +1317,7 @@ learnr:::question_prerendered_chunk(structure(list(type = "learnr_radio", label
     "character")), message = NULL, post_message = NULL), ids = list(
         answer = "second-quiz-4-answer", question = "second-quiz-4"), 
     loading = NULL, random_answer_order = FALSE, allow_retry = FALSE, 
-    seed = 26102984.9878449, options = list()), class = c("learnr_radio", 
+    seed = 521059730.257363, options = list()), class = c("learnr_radio", 
 "tutorial_question")), session = session)
 </script>
  
@@ -1145,7 +1331,8 @@ output$`tutorial-exercise-mean-output` <- renderUI({
 
 <script type="application/shiny-prerendered" data-context="server">
 learnr:::store_exercise_cache(structure(list(label = "mean", global_setup = structure(c("library(learnr)", 
-"library(readxl)", "options(scipen = 10)", "gameData <- read_excel(\"bgg_dataset.xlsx\", sheet = \"Sheet\")", 
+"library(readxl)", "library(\"ggplot2\")", "options(scipen = 10)", 
+"gameData <- read_excel(\"bgg_dataset.xlsx\", sheet = \"Sheet\")", 
 "knitr::opts_chunk$set(echo = FALSE)"), chunk_opts = list(label = "setup", 
     include = FALSE)), setup = NULL, chunks = list(list(label = "mean", 
     code = "\n\n", opts = list(label = "\"mean\"", exercise = "TRUE"), 
@@ -1183,7 +1370,8 @@ output$`tutorial-exercise-median-output` <- renderUI({
 
 <script type="application/shiny-prerendered" data-context="server">
 learnr:::store_exercise_cache(structure(list(label = "median", global_setup = structure(c("library(learnr)", 
-"library(readxl)", "options(scipen = 10)", "gameData <- read_excel(\"bgg_dataset.xlsx\", sheet = \"Sheet\")", 
+"library(readxl)", "library(\"ggplot2\")", "options(scipen = 10)", 
+"gameData <- read_excel(\"bgg_dataset.xlsx\", sheet = \"Sheet\")", 
 "knitr::opts_chunk$set(echo = FALSE)"), chunk_opts = list(label = "setup", 
     include = FALSE)), setup = NULL, chunks = list(list(label = "median", 
     code = "ptime <- gameData[[\"Play Time\"]]", opts = list(
@@ -1223,7 +1411,8 @@ output$`tutorial-exercise-variance-output` <- renderUI({
 
 <script type="application/shiny-prerendered" data-context="server">
 learnr:::store_exercise_cache(structure(list(label = "variance", global_setup = structure(c("library(learnr)", 
-"library(readxl)", "options(scipen = 10)", "gameData <- read_excel(\"bgg_dataset.xlsx\", sheet = \"Sheet\")", 
+"library(readxl)", "library(\"ggplot2\")", "options(scipen = 10)", 
+"gameData <- read_excel(\"bgg_dataset.xlsx\", sheet = \"Sheet\")", 
 "knitr::opts_chunk$set(echo = FALSE)"), chunk_opts = list(label = "setup", 
     include = FALSE)), setup = NULL, chunks = list(list(label = "variance", 
     code = "ptime <- gameData$\"Play Time\"", opts = list(label = "\"variance\"", 
@@ -1263,7 +1452,8 @@ output$`tutorial-exercise-standard-deviation-output` <- renderUI({
 
 <script type="application/shiny-prerendered" data-context="server">
 learnr:::store_exercise_cache(structure(list(label = "standard-deviation", global_setup = structure(c("library(learnr)", 
-"library(readxl)", "options(scipen = 10)", "gameData <- read_excel(\"bgg_dataset.xlsx\", sheet = \"Sheet\")", 
+"library(readxl)", "library(\"ggplot2\")", "options(scipen = 10)", 
+"gameData <- read_excel(\"bgg_dataset.xlsx\", sheet = \"Sheet\")", 
 "knitr::opts_chunk$set(echo = FALSE)"), chunk_opts = list(label = "setup", 
     include = FALSE)), setup = NULL, chunks = list(list(label = "standard-deviation", 
     code = "ptime <- gameData$\"Play Time\"", opts = list(label = "\"standard-deviation\"", 
@@ -1303,7 +1493,8 @@ output$`tutorial-exercise-linear-regression-output` <- renderUI({
 
 <script type="application/shiny-prerendered" data-context="server">
 learnr:::store_exercise_cache(structure(list(label = "linear-regression", global_setup = structure(c("library(learnr)", 
-"library(readxl)", "options(scipen = 10)", "gameData <- read_excel(\"bgg_dataset.xlsx\", sheet = \"Sheet\")", 
+"library(readxl)", "library(\"ggplot2\")", "options(scipen = 10)", 
+"gameData <- read_excel(\"bgg_dataset.xlsx\", sheet = \"Sheet\")", 
 "knitr::opts_chunk$set(echo = FALSE)"), chunk_opts = list(label = "setup", 
     include = FALSE)), setup = NULL, chunks = list(list(label = "linear-regression", 
     code = "raters <- gameData$\"Users Rated\"\nowned <- gameData$\"Owned Users\"", 
@@ -1343,7 +1534,8 @@ output$`tutorial-exercise-lm-plot-output` <- renderUI({
 
 <script type="application/shiny-prerendered" data-context="server">
 learnr:::store_exercise_cache(structure(list(label = "lm-plot", global_setup = structure(c("library(learnr)", 
-"library(readxl)", "options(scipen = 10)", "gameData <- read_excel(\"bgg_dataset.xlsx\", sheet = \"Sheet\")", 
+"library(readxl)", "library(\"ggplot2\")", "options(scipen = 10)", 
+"gameData <- read_excel(\"bgg_dataset.xlsx\", sheet = \"Sheet\")", 
 "knitr::opts_chunk$set(echo = FALSE)"), chunk_opts = list(label = "setup", 
     include = FALSE)), setup = NULL, chunks = list(list(label = "lm-plot", 
     code = "raters <- gameData$\"Users Rated\"\nowned <- gameData$\"Owned Users\"\nx = lm()\nplot(, , pch = 16, col = \"blue\")\n", 
@@ -1377,10 +1569,10 @@ learnr:::store_exercise_cache(structure(list(label = "lm-plot", global_setup = s
 <script type="application/shiny-prerendered" data-context="server">
 learnr:::question_prerendered_chunk(structure(list(type = "learnr_radio", label = "hypothesis-quiz-1", 
     question = structure("Spiele mit hoeherem Complexity Score haben eine niedrigere Anzahl von Owned Users.", html = TRUE, class = c("html", 
-    "character")), answers = list(structure(list(id = "lnr_ans_378b4dc", 
+    "character")), answers = list(structure(list(id = "lnr_ans_8e12fab", 
         option = "Wahr", value = "Wahr", label = structure("Wahr", html = TRUE, class = c("html", 
         "character")), correct = TRUE, message = NULL, type = "literal"), class = c("tutorial_question_answer", 
-    "tutorial_quiz_answer")), structure(list(id = "lnr_ans_25d3c0d", 
+    "tutorial_quiz_answer")), structure(list(id = "lnr_ans_942fbf5", 
         option = "Falsch", value = "Falsch", label = structure("Falsch", html = TRUE, class = c("html", 
         "character")), correct = FALSE, message = NULL, type = "literal"), class = c("tutorial_question_answer", 
     "tutorial_quiz_answer"))), button_labels = list(submit = structure("<span data-i18n=\"button.questionsubmit\">Submit Answer<\u002fspan>", html = TRUE, class = c("html", 
@@ -1391,7 +1583,7 @@ learnr:::question_prerendered_chunk(structure(list(type = "learnr_radio", label
     "character")), message = NULL, post_message = NULL), ids = list(
         answer = "hypothesis-quiz-1-answer", question = "hypothesis-quiz-1"), 
     loading = NULL, random_answer_order = FALSE, allow_retry = FALSE, 
-    seed = 51313380.4761053, options = list()), class = c("learnr_radio", 
+    seed = 991454976.038318, options = list()), class = c("learnr_radio", 
 "tutorial_question")), session = session)
 </script>
 
@@ -1399,10 +1591,10 @@ learnr:::question_prerendered_chunk(structure(list(type = "learnr_radio", label
 <script type="application/shiny-prerendered" data-context="server">
 learnr:::question_prerendered_chunk(structure(list(type = "learnr_radio", label = "hypothesis-quiz-2", 
     question = structure("Spiele mit hoeherem Complexity Score haben hoehere Play Time.", html = TRUE, class = c("html", 
-    "character")), answers = list(structure(list(id = "lnr_ans_8620b56", 
+    "character")), answers = list(structure(list(id = "lnr_ans_a1be36f", 
         option = "Wahr", value = "Wahr", label = structure("Wahr", html = TRUE, class = c("html", 
         "character")), correct = TRUE, message = NULL, type = "literal"), class = c("tutorial_question_answer", 
-    "tutorial_quiz_answer")), structure(list(id = "lnr_ans_42abe8b", 
+    "tutorial_quiz_answer")), structure(list(id = "lnr_ans_3f08a31", 
         option = "Falsch", value = "Falsch", label = structure("Falsch", html = TRUE, class = c("html", 
         "character")), correct = FALSE, message = NULL, type = "literal"), class = c("tutorial_question_answer", 
     "tutorial_quiz_answer"))), button_labels = list(submit = structure("<span data-i18n=\"button.questionsubmit\">Submit Answer<\u002fspan>", html = TRUE, class = c("html", 
@@ -1413,18 +1605,220 @@ learnr:::question_prerendered_chunk(structure(list(type = "learnr_radio", label
     "character")), message = NULL, post_message = NULL), ids = list(
         answer = "hypothesis-quiz-2-answer", question = "hypothesis-quiz-2"), 
     loading = NULL, random_answer_order = FALSE, allow_retry = FALSE, 
-    seed = 2052683885.04414, options = list()), class = c("learnr_radio", 
+    seed = 1482267074.30977, options = list()), class = c("learnr_radio", 
+"tutorial_question")), session = session)
+</script>
+ 
+<script type="application/shiny-prerendered" data-context="server">
+`tutorial-exercise-plotExercise-result` <- learnr:::setup_exercise_handler(reactive(req(input$`tutorial-exercise-plotExercise-code-editor`)), session)
+output$`tutorial-exercise-plotExercise-output` <- renderUI({
+  `tutorial-exercise-plotExercise-result`()
+})
+</script>
+
+
+<script type="application/shiny-prerendered" data-context="server">
+learnr:::store_exercise_cache(structure(list(label = "plotExercise", global_setup = structure(c("library(learnr)", 
+"library(readxl)", "library(\"ggplot2\")", "options(scipen = 10)", 
+"gameData <- read_excel(\"bgg_dataset.xlsx\", sheet = \"Sheet\")", 
+"knitr::opts_chunk$set(echo = FALSE)"), chunk_opts = list(label = "setup", 
+    include = FALSE)), setup = NULL, chunks = list(list(label = "plotExercise", 
+    code = "", opts = list(label = "\"plotExercise\"", exercise = "TRUE"), 
+    engine = "r")), code_check = NULL, error_check = NULL, check = NULL, 
+    solution = NULL, tests = NULL, options = list(eval = FALSE, 
+        echo = TRUE, results = "markup", tidy = FALSE, tidy.opts = NULL, 
+        collapse = FALSE, prompt = FALSE, comment = NA, highlight = FALSE, 
+        size = "normalsize", background = "#F7F7F7", strip.white = TRUE, 
+        cache = 0, cache.path = "tutorial_page_cache/html/", 
+        cache.vars = NULL, cache.lazy = TRUE, dependson = NULL, 
+        autodep = FALSE, cache.rebuild = FALSE, fig.keep = "high", 
+        fig.show = "asis", fig.align = "default", fig.path = "tutorial_page_files/figure-html/", 
+        dev = "png", dev.args = NULL, dpi = 192, fig.ext = "png", 
+        fig.width = 6.5, fig.height = 4, fig.env = "figure", 
+        fig.cap = NULL, fig.scap = NULL, fig.lp = "fig:", fig.subcap = NULL, 
+        fig.pos = "", out.width = 624, out.height = NULL, out.extra = NULL, 
+        fig.retina = 2, external = TRUE, sanitize = FALSE, interval = 1, 
+        aniopts = "controls,loop", warning = TRUE, error = FALSE, 
+        message = TRUE, render = NULL, ref.label = NULL, child = NULL, 
+        engine = "r", split = FALSE, include = TRUE, purl = TRUE, 
+        max.print = 1000, label = "plotExercise", exercise = TRUE, 
+        code = "", out.width.px = 624, out.height.px = 384, params.src = "plotExercise, exercise=TRUE", 
+        fig.num = 0L, exercise.df_print = "paged", exercise.checker = "NULL"), 
+    engine = "r", version = "4"), class = c("r", "tutorial_exercise"
+)))
+</script>
+ 
+<script type="application/shiny-prerendered" data-context="server">
+learnr:::question_prerendered_chunk(structure(list(type = "learnr_radio", label = "quiz-ggplot-1", 
+    question = structure("Was ist der Median im Diagramm?", html = TRUE, class = c("html", 
+    "character")), answers = list(structure(list(id = "lnr_ans_85c1138", 
+        option = "ein vertikaler Strich", value = "ein vertikaler Strich", 
+        label = structure("ein vertikaler Strich", html = TRUE, class = c("html", 
+        "character")), correct = FALSE, message = NULL, type = "literal"), class = c("tutorial_question_answer", 
+    "tutorial_quiz_answer")), structure(list(id = "lnr_ans_ff90fdf", 
+        option = "die Höhe der Box", value = "die Höhe der Box", 
+        label = structure("die Höhe der Box", html = TRUE, class = c("html", 
+        "character")), correct = FALSE, message = NULL, type = "literal"), class = c("tutorial_question_answer", 
+    "tutorial_quiz_answer")), structure(list(id = "lnr_ans_d199a79", 
+        option = "ein horizontaler Strich in der Mitter der Box", 
+        value = "ein horizontaler Strich in der Mitter der Box", 
+        label = structure("ein horizontaler Strich in der Mitter der Box", html = TRUE, class = c("html", 
+        "character")), correct = TRUE, message = NULL, type = "literal"), class = c("tutorial_question_answer", 
+    "tutorial_quiz_answer")), structure(list(id = "lnr_ans_34eab96", 
+        option = "das untere Ende der Box", value = "das untere Ende der Box", 
+        label = structure("das untere Ende der Box", html = TRUE, class = c("html", 
+        "character")), correct = FALSE, message = NULL, type = "literal"), class = c("tutorial_question_answer", 
+    "tutorial_quiz_answer"))), button_labels = list(submit = structure("<span data-i18n=\"button.questionsubmit\">Submit Answer<\u002fspan>", html = TRUE, class = c("html", 
+    "character")), try_again = structure("<span data-i18n=\"button.questiontryagain\">Try Again<\u002fspan>", html = TRUE, class = c("html", 
+    "character"))), messages = list(correct = structure("Correct!", html = TRUE, class = c("html", 
+    "character")), try_again = structure("Incorrect", html = TRUE, class = c("html", 
+    "character")), incorrect = structure("Incorrect", html = TRUE, class = c("html", 
+    "character")), message = NULL, post_message = NULL), ids = list(
+        answer = "quiz-ggplot-1-answer", question = "quiz-ggplot-1"), 
+    loading = NULL, random_answer_order = FALSE, allow_retry = FALSE, 
+    seed = 870267660.09475, options = list()), class = c("learnr_radio", 
+"tutorial_question")), session = session)
+</script>
+
+
+<script type="application/shiny-prerendered" data-context="server">
+learnr:::question_prerendered_chunk(structure(list(type = "learnr_checkbox", label = "quiz-ggplot-2", 
+    question = structure("Was sind die Quartile im Diagramm?(Es sind mehrere Antworten möglich)", html = TRUE, class = c("html", 
+    "character")), answers = list(structure(list(id = "lnr_ans_5716280", 
+        option = "das obere Ende der Box", value = "das obere Ende der Box", 
+        label = structure("das obere Ende der Box", html = TRUE, class = c("html", 
+        "character")), correct = TRUE, message = NULL, type = "literal"), class = c("tutorial_question_answer", 
+    "tutorial_quiz_answer")), structure(list(id = "lnr_ans_30cc98b", 
+        option = "Punkte oberhalb der Box", value = "Punkte oberhalb der Box", 
+        label = structure("Punkte oberhalb der Box", html = TRUE, class = c("html", 
+        "character")), correct = FALSE, message = NULL, type = "literal"), class = c("tutorial_question_answer", 
+    "tutorial_quiz_answer")), structure(list(id = "lnr_ans_7130847", 
+        option = "ein Drittel des vertikalen Strichs", value = "ein Drittel des vertikalen Strichs", 
+        label = structure("ein Drittel des vertikalen Strichs", html = TRUE, class = c("html", 
+        "character")), correct = FALSE, message = NULL, type = "literal"), class = c("tutorial_question_answer", 
+    "tutorial_quiz_answer")), structure(list(id = "lnr_ans_2c83f9d", 
+        option = "das untere Ende der Box", value = "das untere Ende der Box", 
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+        "character")), correct = TRUE, message = NULL, type = "literal"), class = c("tutorial_question_answer", 
+    "tutorial_quiz_answer"))), button_labels = list(submit = structure("<span data-i18n=\"button.questionsubmit\">Submit Answer<\u002fspan>", html = TRUE, class = c("html", 
+    "character")), try_again = structure("<span data-i18n=\"button.questiontryagain\">Try Again<\u002fspan>", html = TRUE, class = c("html", 
+    "character"))), messages = list(correct = structure("Correct!", html = TRUE, class = c("html", 
+    "character")), try_again = structure("Incorrect. Be sure to select every correct answer.", html = TRUE, class = c("html", 
+    "character")), incorrect = structure("Incorrect", html = TRUE, class = c("html", 
+    "character")), message = NULL, post_message = NULL), ids = list(
+        answer = "quiz-ggplot-2-answer", question = "quiz-ggplot-2"), 
+    loading = NULL, random_answer_order = FALSE, allow_retry = FALSE, 
+    seed = 1462519502.81896, options = list()), class = c("learnr_checkbox", 
+"tutorial_question")), session = session)
+</script>
+ 
+<script type="application/shiny-prerendered" data-context="server">
+learnr:::question_prerendered_chunk(structure(list(type = "learnr_radio", label = "quiz-ggplot-3", 
+    question = structure("Was sind die Maximalwerte im Diagramm?", html = TRUE, class = c("html", 
+    "character")), answers = list(structure(list(id = "lnr_ans_4112e80", 
+        option = "Punkte oberhalb der Box", value = "Punkte oberhalb der Box", 
+        label = structure("Punkte oberhalb der Box", html = TRUE, class = c("html", 
+        "character")), correct = FALSE, message = NULL, type = "literal"), class = c("tutorial_question_answer", 
+    "tutorial_quiz_answer")), structure(list(id = "lnr_ans_6dd8e61", 
+        option = "die Spitzen des vertikalen Strichs", value = "die Spitzen des vertikalen Strichs", 
+        label = structure("die Spitzen des vertikalen Strichs", html = TRUE, class = c("html", 
+        "character")), correct = TRUE, message = NULL, type = "literal"), class = c("tutorial_question_answer", 
+    "tutorial_quiz_answer")), structure(list(id = "lnr_ans_281ac0", 
+        option = "die x-Achse und die y-Achse", value = "die x-Achse und die y-Achse", 
+        label = structure("die x-Achse und die y-Achse", html = TRUE, class = c("html", 
+        "character")), correct = FALSE, message = NULL, type = "literal"), class = c("tutorial_question_answer", 
+    "tutorial_quiz_answer")), structure(list(id = "lnr_ans_6443f54", 
+        option = "die Flaeche der Box", value = "die Flaeche der Box", 
+        label = structure("die Flaeche der Box", html = TRUE, class = c("html", 
+        "character")), correct = FALSE, message = NULL, type = "literal"), class = c("tutorial_question_answer", 
+    "tutorial_quiz_answer"))), button_labels = list(submit = structure("<span data-i18n=\"button.questionsubmit\">Submit Answer<\u002fspan>", html = TRUE, class = c("html", 
+    "character")), try_again = structure("<span data-i18n=\"button.questiontryagain\">Try Again<\u002fspan>", html = TRUE, class = c("html", 
+    "character"))), messages = list(correct = structure("Correct!", html = TRUE, class = c("html", 
+    "character")), try_again = structure("Incorrect", html = TRUE, class = c("html", 
+    "character")), incorrect = structure("Incorrect", html = TRUE, class = c("html", 
+    "character")), message = NULL, post_message = NULL), ids = list(
+        answer = "quiz-ggplot-3-answer", question = "quiz-ggplot-3"), 
+    loading = NULL, random_answer_order = FALSE, allow_retry = FALSE, 
+    seed = 126669168.941015, options = list()), class = c("learnr_radio", 
+"tutorial_question")), session = session)
+</script>
+
+
+<script type="application/shiny-prerendered" data-context="server">
+learnr:::question_prerendered_chunk(structure(list(type = "learnr_radio", label = "quiz-ggplot-4", 
+    question = structure("An was erkennt man im Diagramm die Ausreißer?", html = TRUE, class = c("html", 
+    "character")), answers = list(structure(list(id = "lnr_ans_e5a5eb", 
+        option = "es sind Punkte außerhalb der Box", value = "es sind Punkte außerhalb der Box", 
+        label = structure("es sind Punkte außerhalb der Box", html = TRUE, class = c("html", 
+        "character")), correct = TRUE, message = NULL, type = "literal"), class = c("tutorial_question_answer", 
+    "tutorial_quiz_answer")), structure(list(id = "lnr_ans_87ebf77", 
+        option = "an der Größe der Box", value = "an der Größe der Box", 
+        label = structure("an der Größe der Box", html = TRUE, class = c("html", 
+        "character")), correct = FALSE, message = NULL, type = "literal"), class = c("tutorial_question_answer", 
+    "tutorial_quiz_answer")), structure(list(id = "lnr_ans_9f074f3", 
+        option = "durch schlechtes Verhalten", value = "durch schlechtes Verhalten", 
+        label = structure("durch schlechtes Verhalten", html = TRUE, class = c("html", 
+        "character")), correct = FALSE, message = NULL, type = "literal"), class = c("tutorial_question_answer", 
+    "tutorial_quiz_answer"))), button_labels = list(submit = structure("<span data-i18n=\"button.questionsubmit\">Submit Answer<\u002fspan>", html = TRUE, class = c("html", 
+    "character")), try_again = structure("<span data-i18n=\"button.questiontryagain\">Try Again<\u002fspan>", html = TRUE, class = c("html", 
+    "character"))), messages = list(correct = structure("Correct!", html = TRUE, class = c("html", 
+    "character")), try_again = structure("Incorrect", html = TRUE, class = c("html", 
+    "character")), incorrect = structure("Incorrect", html = TRUE, class = c("html", 
+    "character")), message = NULL, post_message = NULL), ids = list(
+        answer = "quiz-ggplot-4-answer", question = "quiz-ggplot-4"), 
+    loading = NULL, random_answer_order = FALSE, allow_retry = FALSE, 
+    seed = 1482607067.80961, options = list()), class = c("learnr_radio", 
 "tutorial_question")), session = session)
 </script>
+ 
+<script type="application/shiny-prerendered" data-context="server">
+`tutorial-exercise-barplotExercise-result` <- learnr:::setup_exercise_handler(reactive(req(input$`tutorial-exercise-barplotExercise-code-editor`)), session)
+output$`tutorial-exercise-barplotExercise-output` <- renderUI({
+  `tutorial-exercise-barplotExercise-result`()
+})
+</script>
+
+
+<script type="application/shiny-prerendered" data-context="server">
+learnr:::store_exercise_cache(structure(list(label = "barplotExercise", global_setup = structure(c("library(learnr)", 
+"library(readxl)", "library(\"ggplot2\")", "options(scipen = 10)", 
+"gameData <- read_excel(\"bgg_dataset.xlsx\", sheet = \"Sheet\")", 
+"knitr::opts_chunk$set(echo = FALSE)"), chunk_opts = list(label = "setup", 
+    include = FALSE)), setup = NULL, chunks = list(list(label = "barplotExercise", 
+    code = "\n", opts = list(label = "\"barplotExercise\"", exercise = "TRUE"), 
+    engine = "r")), code_check = NULL, error_check = NULL, check = NULL, 
+    solution = NULL, tests = NULL, options = list(eval = FALSE, 
+        echo = TRUE, results = "markup", tidy = FALSE, tidy.opts = NULL, 
+        collapse = FALSE, prompt = FALSE, comment = NA, highlight = FALSE, 
+        size = "normalsize", background = "#F7F7F7", strip.white = TRUE, 
+        cache = 0, cache.path = "tutorial_page_cache/html/", 
+        cache.vars = NULL, cache.lazy = TRUE, dependson = NULL, 
+        autodep = FALSE, cache.rebuild = FALSE, fig.keep = "high", 
+        fig.show = "asis", fig.align = "default", fig.path = "tutorial_page_files/figure-html/", 
+        dev = "png", dev.args = NULL, dpi = 192, fig.ext = "png", 
+        fig.width = 6.5, fig.height = 4, fig.env = "figure", 
+        fig.cap = NULL, fig.scap = NULL, fig.lp = "fig:", fig.subcap = NULL, 
+        fig.pos = "", out.width = 624, out.height = NULL, out.extra = NULL, 
+        fig.retina = 2, external = TRUE, sanitize = FALSE, interval = 1, 
+        aniopts = "controls,loop", warning = TRUE, error = FALSE, 
+        message = TRUE, render = NULL, ref.label = NULL, child = NULL, 
+        engine = "r", split = FALSE, include = TRUE, purl = TRUE, 
+        max.print = 1000, label = "barplotExercise", exercise = TRUE, 
+        code = c("", ""), out.width.px = 624, out.height.px = 384, 
+        params.src = "barplotExercise, exercise=TRUE", fig.num = 0L, 
+        exercise.df_print = "paged", exercise.checker = "NULL"), 
+    engine = "r", version = "4"), class = c("r", "tutorial_exercise"
+)))
+</script>
 </p>
 <!--html_preserve-->
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literal 0
HcmV?d00001

-- 
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