Spreadsheets are great for displaying, sorting, and producing quick summaries of data. But more sophisticated data tasks require more sophisticated tools—like the programming language R. R is a powerful and open source language design for statistical computing, and widely used across academia and industry. It can handle much larger datasets than any spreadsheet, can calculate and automate much faster, offers more advanced visualization, and—perhaps best of all—its code is reproducible. Bottom line: R improves your workflow, saving you time and effort while providing meaningful data analysis and reports.
about the book
From Data to Deliverables with R
is a collection of chapters from three Manning books, selected by author and data science practitioner Jonathan Carroll. You’ll start with an overview of common data structures in R and how they relate to spreadsheets, and then explore different ways of combining groups of data. You’ll walk through useful ways to inspect your data with summary statistics and visualization, and learn how to easily generate dynamic reports from your analysis in several formats directly from R. This straightforward sampler is a great first step to transitioning from spreadsheets for your data analysis tasks to more sophisticated, reproducible processes with R.
- “Combining data values” - Chapter 5 from Beyond Spreadsheets with R by Jonathan Carroll
- “Exploring data” - Chapter 3 from Practical Data Science with R, Second Edition by Nina Zumel and John Mount
- “Creating dynamic reports” - Chapter 22 from R in Action, Second Edition by Robert I. Kabacoff
about the author
Dr. Jonathan Carroll
is a data science consultant providing R programming services. He holds a PhD in theoretical physics.