Project-oriented workflow

class: center, middle, inverse, title-slide

.title[
# Project-oriented workflow
]
.author[
### Kauê de Sousa
]
.date[
### 2023
]

---

# Content

* Script vs Project
* RStudio project
* Directory structure
* Our workflow

---
class: middle, inverse
# Script vs Project

---
# Script vs Project

## Script

* An R script is simply a text file containing a set of commands and comments. The script can be saved and used later to re-execute the saved commands
* Data analysis in a script-based approach means that you have to set your workplace every time that you need to work on the data
* Sometimes the input files are spread out in different directories and make difficult to others to reproduce the analysis. EVEN FOR YOU IF YOU CHANGE COMPUTER!!

.footnote[
[1] [Read more here](https://www.tidyverse.org/blog/2017/12/workflow-vs-script/)]

---
# Script vs Project

## Project

* A folder on your computer that holds all the files relevant to that particular piece of work
* Any resident R script is written assuming that it will be run from a fresh R process with working directory set to the project directory
* This convention guarantees that the project can be moved around on your computer or onto other computers and will still “just work”

.footnote[
[1] [Read more here](https://r4ds.had.co.nz/workflow-projects.html)]

---

.pull-left[
<img src="img/folder-structure.png" width="80%"/>
]

(**.Rproj**) a file generated by RStudio for the R project in this directory. This is the file that should be opened to work on the project (e.g. clean data, write scripts, write outputs)

(**data**) contains all the input files that are ready to be analysed. In some cases we use a sub-directory called "raw", which may contain some sensitive data and or the raw data

(**script**) contains all the scripts used for the analysis. They are named in order from 01 to `n` scripts. This makes easier for others to know where to start. Old scripts (not relevant for the analysis) are maintained in a sub-directory "old-scripts". You may need them in the future

(**output**) is where all the outputs from the analysis are written.

(**docs**) an optional sub-directory to store the notebooks or report(s)

.footnote[
[1] [See this folder here](https://github.com/AgrDataSci/template-repo-data-analysis)]

---
class: middle, inverse
# RStudio project

---
# RStudio project

Is a context for work on a specific project for data analysis

* automatically sets working directory to project folder
* has a separate workspace and command history
* its easy to share and ensure reproducibility

.footnote[
[1] [Read more here](https://r4ds.had.co.nz/workflow-projects.html#rstudio-projects)
]

---

# **Thank you!**

.pull-right[

<img src="https://img.icons8.com/ios-filled/50/000000/email-open.png" width = "10%">[k.desousa@cgiar.org](mailto:k.desousa@cgiar.org)

[Back to the main page](index.html)
]