R Programming Language Assignment for Multiverse of Languages: Intro to R Workshop.

Before you begin, ensure that you have the necessary R packages installed. To do this, run the install_packages.R script provided in the repository: Rscript install_packages.R

This script will install the required packages locally.

First, fork this repository to your GitHub account. Then, clone your forked repository to your local machine:

git clone https://github.com/your-username/your-forked-repo.git

cd your-forked-repo

Inside the repository, you'll find three folders: tasks/basics.R, tasks/loops.R, and tasks/dataset.R. Each folder contains R script files with tasks for you to complete. Start with basics.R and proceed to loops.R, and finally dataset.R.

Each task is worth a certain number of points. The tasks in basics.R and loops.R together are worth 50 points, while the dataset.R task is also worth 50 points. You can check your progress and score by running main.R.

To complete a task:

• Open the relevant R script (e.g., tasks/basics.R) and follow the instructions.
• Write meaningful comments and code to solve each task.
• Save your script.

After completing the tasks in basics.R and loops.R, you can use main.R to check if your solutions are correct. Run the following command in your R environment:

RScript main.R or source("main.R")

This will evaluate the tasks in basics.R and loops.R and display your score in the terminal.

Once you have completed all the tasks, including the dataset.R task, create a pull request (PR) to the original repository. Make sure to include:

• Screenshots of any plots or charts you generated.
• A description of the changes you made.
• The score shown in the terminal after running main.R.

Your PR will be reviewed and evaluated for the dataset.R task.

• install_packages.R: Installs required R packages.
• tasks/basics.R: Basic R programming tasks worth 50 points.
• tasks/loops.R: Loop-related R tasks worth 50 points.
• tasks/dataset.R: Data analysis and visualization task (reviewed by the owner).

This README.md file provides users with detailed instructions on how to set up the project, complete the tasks, check their score, and create a meaningful pull request. Feel free to include this README.md file in your repository.