Objectifs :
You followed the two days training on the Tidyverse basics and you want to go further into data wrangling, plots production and Rmarkdown reports, then this training is for you !

Programme :
MORNING
Sequence 1 : Various useful functions of the tidyverse
- count observations
- change values based on conditions
- filter values of a variable based on another variable
- separate or unite columns
- detect a character string
- rearrange the levels of a factor based on another variable for a plot (GOODIES)

Sequence 2 : introduction to the map() function to iterate as a replacement for a loop and its application to describing an dataframe

Introduction to the map() function which allows you to apply a function to several elements of an object (here the columns of a dataframe) and application to the synthetic description of a table (for each column, we retrieves the type of the variable, the number of levels, the names of the levels and the number of NA values).

AFTERNOON
Sequence 3 : bulk creation of plots
Use of the map() function to create series of plots in which only the y axis variable changes

Sequence 4 : Annotate charts
- add annotations to the graph with geom_text(), geom_label() and annotate()
- make an interactive graph
- add anova letters on a chart (GOODIES)
- automatic addition of a regression line, the equation and the R2 on the graph (GOODIES)

- Sequence 5: Improve your reports with Rmarkdown
- position and resize a figure, put legends on figures and display a data table.
- insert an automatic summary, bibliographic references, and automatically export the figures to a folder.

Pré-requis :
Bring your computer

Have completed the two-day beginners' module 5.1 System R Level 1 - Start with RStudio,Tidyverse and Rmarkdown to wrangle data and produce plots or have some basic knowledge of the tidyverse (select, mutate, group_by, summarise, pipe operator, ggplot) and Rmarkdown (chunks, narrative, report production).

Méthode pédagogique :
The course uses the user-friendly interface of RStudio, which facilitates the use of R, and the Rmarkdown format, which allows the automatic generation of reports (html, word, pdf) from the code. The teaching method consists of a series of progressive sequences made up of a theoretical contribution, followed by a quiz and then an exercise.

Instructions for sofwares and packages installation, datasets used during the training along with the pdf to take notes on and the rmarkdown template are sent to every participant a week before the training. People with disabilities can contact me so that we can find a way to adapt the training to suit their needs.

Compétences acquises à l'issue de la formation :
At the end of the training, participants will be able to:
- Perform common table manipulation operations such as sorting values, counting observations, changing values of a variable based on conditions, filtering values of a variable based on another variable, separating and uniting data columns, detect a character string and reorganize the levels of a factor according to another variable on a graph
- Apply the map() function to a dataframe to describe variables and generate graphs in bulk
- add annotations on the plot and make an interactive plot
- position and resize a figure, put legends on the figures and display a dataframe and insert an automatic table of content in the report

Les Compétences et capacités visées à l'issue de la formation (fiches RNCP)

Arrêté du 22 février 2019 définissant les compétences des diplômés du doctorat et inscrivant le doctorat au répertoire national de la certification professionnelle. https://www.legifrance.gouv.fr/loda/id/JORFTEXT000038200990/

Bloc 1 : Conception et élaboration d’une démarche de recherche et développement, d’études et prospective

- Disposer d'une expertise scientifique tant générale que spécifique d'un domaine de recherche et de travail déterminé

- Identifier et résoudre des problèmes complexes et nouveaux impliquant une pluralité de domaines, en mobilisant les connaissances et les savoir-faire les plus avancés

Compétences sociales

- Adaptation ; Persévérance ; Résilience ; Gestion du changement et de l'échec ; Engagement

La formation participe à l'objectif suivant :être directement utile pour la réalisation des travaux personnels de recherche