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The book covers various R packages and tools commonly used for data wrangling, including:
Some possible sources to find these papers: gustavo r santos data wrangling with r
Data wrangling is a crucial step in the data science workflow that involves cleaning, transforming, and preparing data for analysis. The book introduces the concept of data wrangling and its importance in data science. The book covers various R packages and tools
– A solid, no‑frills tutorial for R beginners who need to get data into shape quickly. It won’t make you a data wrangling expert, but it will get you confidently using dplyr and tidyr on typical small‑to‑medium datasets. If you prefer a free alternative, start with R for Data Science online. If you like structured, exercise‑driven learning from a single book, this is a reasonable purchase. It won’t make you a data wrangling expert,
In his writings on Medium , Santos emphasizes that data is rarely presented in a clean, "ready-to-model" state. He defines as any activity involving the cleaning, modifying, and organizing of data. Key tasks covered in his workflow include:
I've searched for papers related to "Data Wrangling with R" by Gustavo R. Santos and found a few relevant ones:
Pivoting from "long" to "wide" formats (and vice versa) to meet specific analytical needs.
