Data Wrangling in R
Data is often messy, requiring cleaning and restructuring before it can be reliably used in a program or project. In this course, learners will augment their understanding of base R using an open-source set of packages intended for data cleaning and wrangling, the tidyverse. After installing this package, learners will practice working with functions that allow data to be selected, filtered, summarized, rearranged, and otherwise transformed according to analyst-vetted best practices.
6 hours of instruction
Data is often messy, requiring cleaning and restructuring before it can be reliably used in a program or project. In this course, learners will augment their understanding of base R using an open-source set of packages intended for data cleaning and wrangling, the tidyverse. After installing this package, learners will practice working with functions that allow data to be selected, filtered, summarized, rearranged, and otherwise transformed according to analyst-vetted best practices.
OBJECTIVES
- Define the functions that provide verbs for the language of data manipulation
- Summarize columns using the group by function
- Transform messy data to tidy data using tidyr package
PREREQUISITES
Learners should be comfortable implementing conditional statements, for loops, and while loops in R.
SYLLABUS & TOPICS COVERED
- Data Wrangling
- Data wrangling basics
- Use dplyr for data wrangling
- Data Summarization And Transformation
- Tidy data best practices
- Transform data with tidyr
SOFTWARE REQUIREMENTS
You will have access to an R-based Posit Cloud environment for this course. No additional download or installation is required.
