La fonction fct_reorder

Supposons que vous ajoutiez median comme troisième argument à la fonction fct_reorder(). Que fait-elle ?

Cet exercice fait partie du cours

<cours>Communiquer avec les données dans le tidyverse</cours>

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Cet exercice fait partie du cours

<cours>Communiquer avec les données dans le tidyverse</cours>

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In this chapter, you will have a first look at the data you're going to work with throughout this course: the relationship between weekly working hours and monetary compensation in European countries, according to the International Labour Organization (ILO). After that, you'll dive right in and discover a stunning correlation by employing an exploratory visualization. You will then apply a custom look to that graphic – you'll turn an ordinary plot into an aesthetically pleasing and unique data visualization.

Exercise 1: Introduction to the data Exercise 2: Join the two data sets together Exercise 3: Change variable types Exercise 4: Filtering and plotting the data Exercise 5: Filter the data for plotting Exercise 6: Some summary statistics Exercise 7: A basic scatter plot Exercise 8: Add labels to the plot Exercise 9: Custom ggplot2 themes Exercise 10: Apply a default theme Exercise 11: Change the appearance of titles Exercise 12: Alter background color and add margins

Barcharts, scatter plots, and histograms are probably the most common and effective data visualizations. Yet, sometimes, there are even better ways to visually highlight the finding you want to communicate to your audience. So-called "dot plots" make us better grasp and understand changes in data: development over time, for example. In this chapter, you'll build a custom and unique visualization that emphasizes and explains exactly one aspect of the story you want to tell.

Exercise 1: Visualiser des aspects des données avec des facettes Exercise 2: Préparer le jeu de données pour le graphique avec facettes Exercise 3: Ajouter des facettes au graphique Exercise 4: Définir votre propre fonction de thème Exercise 5: Appliquer la nouvelle fonction de thème au graphique Exercise 6: Un graphique personnalisé pour mettre en évidence les évolutions Exercise 7: Un dot plot simple Exercise 8: Ajouter des flèches aux lignes du graphique Exercise 9: Ajouter des étiquettes à chaque pays Exercise 10: Peaufiner le dot plot Exercise 11: La fonction fct_reorder

Exercice actuel

Exercise 12: Réordonner les éléments du graphique Exercise 13: Corriger la position des étiquettes peu esthétiques Exercise 14: Finaliser le graphique pour différents publics et appareils Exercise 15: Modifier la fenêtre d’affichage pour que les étiquettes ne chevauchent pas la bordure du graphique Exercise 16: Optimiser le graphique pour les appareils mobiles

Back in the old days, researchers and data analysts used to generate plots in R and then tediously copy them into their LaTeX or Word documents. Nowadays, whole reports can be produced and reproduced from within R and RStudio, using the RMarkdown language – combining R chunks, formatted prose, tables and plots. In this chapter, you'll take your previous findings, results, and graphics and integrate them into such a report to tell the story that needs to be told.

Exercise 1: What is RMarkdown?Exercise 2: When is a document reproducible?Exercise 3: Introduction to the RMarkdown exercise interface Exercise 4: Formatting with Markdown Exercise 5: Give your document a structure Exercise 6: Change formatting of text snippets Exercise 7: R code in RMarkdown documents Exercise 8: Specify packages in the first code chunk Exercise 9: R code chunk options Exercise 10: Inline code statements Exercise 11: Images in RMarkdown files Exercise 12: Adjusting figure options, optimizing them for mobile devices.Exercise 13: Add auxiliary images

Your boss, your client, or your professor usually expects your results to be accurate and presented in a clear and concise structure. However, coming up with a nicely formatted and unique report on top of that is certainly a plus and RMarkdown can be customized to accomplish this. In this last chapter, you'll take your report from the last chapter and brand it with your own custom and unique style.

Exercise 1: Advanced YAML settings Exercise 2: Change the overall appearance of your report Exercise 3: Add a table of contents Exercise 4: More YAML hacks Exercise 5: Custom stylesheets Exercise 6: CSS selectors Exercise 7: Change style attributes of text elements Exercise 8: Reference the style sheet Exercise 9: Beautiful tables Exercise 10: Beautify a table with kable Exercise 11: Repetition: CSS Exercise 12: Summary