A3 Book section, Chapters in research books
An R Approach to Data Cleaning and Wrangling for Education Research (2024)
Kopra, J., Tikka, S., Heinäniemi, M., López-Pernas, S., & Saqr, M. (2024). An R Approach to Data Cleaning and Wrangling for Education Research. In M. Saqr, & S. López-Pernas (Eds.), Learning Analytics Methods and Tutorials : A Practical Guide Using R (pp. 95-119). Springer. https://doi.org/10.1007/978-3-031-54464-4_4
JYU authors or editors
Publication details
All authors or editors: Kopra, Juho; Tikka, Santtu; Heinäniemi, Merja; López-Pernas, Sonsoles; Saqr, Mohammed
Parent publication: Learning Analytics Methods and Tutorials : A Practical Guide Using R
Parent publication editors: Saqr, Mohammed; López-Pernas, Sonsoles
ISBN: 978-3-031-54463-7
eISBN: 978-3-031-54464-4
Publication year: 2024
Pages range: 95-119
Number of pages in the book: 736
Publisher: Springer
Place of Publication: Cham
Publication country: Switzerland
Publication language: English
DOI: https://doi.org/10.1007/978-3-031-54464-4_4
Publication open access: Openly available
Publication channel open access: Open Access channel
Publication is parallel published (JYX): https://jyx.jyu.fi/handle/123456789/96304
Abstract
Data wrangling, also known as data cleaning and preprocessing, is a critical step in the data analysis process, particularly in the context of learning analytics. This chapter provides an introduction to data wrangling using R and covers topics such as data importing, cleaning, manipulation, and reshaping with a focus on tidy data. Specifically, readers will learn how to read data from different file formats (e.g. CSV, Excel), how to manipulate data using the dplyr package, and how to reshape data using the tidyr package. Additionally, the chapter covers techniques for combining multiple data sources. By the end of the chapter, readers should have a solid understanding of how to perform data wrangling tasks in R.
Keywords: programming; learning; data processing
Free keywords: data wrangling; data cleaning; tidyverse; R programming; learning analytics
Contributing organizations
Ministry reporting: Yes
VIRTA submission year: 2024
Preliminary JUFO rating: 2
