Duration: 5 weeks
Target Audience: R users with basic knowledge and data handling experience aiming to master data manipulation techniques.
Week 1: Introduction to Data Manipulation in R
- Overview of dplyr, tidyr, stringr, and lubridate packages.
- Importance of data wrangling in analysis workflows.
- Assignment: Load a dataset and perform basic dplyr operations (filter, select).
Week 2: Data Transformation with dplyr and tidyr
- Key dplyr functions: mutate, group_by, summarise, arrange.
- Reshaping data with tidyr: pivot_longer, pivot_wider.
- Assignment: Transform and reshape a dataset using dplyr and tidyr.
Week 3: String Manipulation with stringr
- Regular expressions, string detection, replacement, splitting.
- Cleaning text data in real-world scenarios.
- Assignment: Clean a dataset with inconsistent text entries using stringr.
Week 4: Date and Time Handling with lubridate
- Parsing dates, extracting components, date arithmetic.
- Managing time series data effectively.
- Assignment: Manipulate a dataset with date-time variables (e.g., sales data).
Week 5: Capstone Project
- Combine dplyr, tidyr, stringr, and lubridate to clean and transform a complex dataset.
- Present a cleaned dataset with a summary report.
- Final review and feedback.
