Data Wrangling Practice with R

R-Ladies Rome Tutorials
Author

Federica Gazzelloni

Published

September 30, 2024

Welcome to this course designed to introduce you to Data Wrangling Practice with R

Instructor

Course Description

Data Wrangling Practice with R is a tutorial designed for individuals looking to enhance their data manipulation and transformation skills using the R programming language. Data wrangling, a critical step in any data analysis or machine learning pipeline, involves cleaning, structuring, and preparing raw data to ensure its usability for analysis.

We will cover the basics of data wrangling, including data manipulation, data cleaning, and data transformation. We will use the tidyverse meta-package to perform these tasks. By the end of this course, you will be able to wrangle data in R and prepare it for analysis.

Learning Objectives

  • Understand the importance of data wrangling in the data science workflow
  • Learn how to clean and manipulate data using R
  • Learn how to handle missing values, tidy data, and reshape datasets
  • Prepare datasets for analysis and visualization

Prerequisites

This course is designed for beginners. You should have a basic understanding of R and RStudio. If you are new to R, you may want to take an introductory course before taking this course.

Course Outline

  1. Introduction to Data Wrangling
  2. Essential Data Preparation Techniques
  3. Practice with Cardio Data
  4. Data Description
  5. Data Wrangling
  6. Joining Data
  7. Exporting Data
  8. Summary

Course Materials

All course materials will be provided in the form of R scripts and R Quarto/Markdown files. You can download the materials from the GitHub repository https://github.com/Fgazzelloni/20240930-DWPwR.