The Big R-Book: From Data Science to Learning Machines and Big Data
by Philippe J.S. De Brouwer
– Published by John Wiley & Sons –

The Parts of the Book

  1. Introduction: the importance of data science
  2. Starting with R and Elements of Statistics: the basics
  3. Data Import: SQL databases and importing data in R
  4. Data Wrangling: modifying data
  5. Modelling: building robust models and verify them, including popular machine learning techniques
  6. Introduction to Companies: what are companies, financial and management accounting, valuation of financial assets and multi criteria decision analysis
  7. Reporting: from automated slides to interactive websites
  8. Bigger and Faster R: using clusters, programming the GPU, big data, and code optimisation
  9. Appendices: extra code, notes, and levels of measurement

Some Statistics about the Book

  • 803 R code examples or segments and 92 other code sections
  • 145 illustrations
  • 270 boxes with information, warnings, digressions, and further information
  • 8 parts, plus front and back-matter
  • 40 chapters plus 5 appendices, 129 sections, 223 subsections, 128 subsubsections
  • 892 pages of fine print
  • 258,450 words in 34,438 paragraphs

Sample Materials

Samples (note: these samples are generate from the submission to the editor – so, while the words are the same, it might look different in the book itself):

Examples of dynamic websites that are explained in the book:

Educational Materials: R-code, slides and apps

A series of videos based on the book: YouTube Playlist

# Title R-Code Slides Videos Other
1 Introduction p01.R Ch 1: Introduction: The past and the future of science
2 Starting with R and Elements of Statistics p02.R Ch 4: How to install R on Windows / the big R-Book series / ch.4
Ch 4: Getting Started with R (console version)
Ch 4: Getting Started with R (RStudio Version)
Ch 7: The philosophy of the Tidyverse
Ch 7: Getting Started the Tidyverse
elements of Ch 4, 21, and 23: Introduction to Data Science with R
3 Data Import p03.R
4 Data Wrangling p04.R
5 Modelling p05.R elements of Ch 4, 21, and 23: Introduction to Data Science with R
6 Introduction to Companies p06.R
7 Reporting p07.R Ch 36: Interactive Dashboards (example with Covid19) Interactive Apps and Dashboards
R Markdown Examples
Ch 36: a tutorial to build a {shiny} app
8 Bigger and Faster R p08.R
9 Appendices p09.R

Get Your Copy

Available now on your favourite shop. For example:

Citations

Automated citations for each chapter: onlinelibrary.wiley.com.

Here is also the bibtex code for the print-version:
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@book{debrouwer2020,
  title     = {The Big R-Book: From Data Science to Learning Machines and Big Data},
  author    = {Philippe J.S. {De Brouwer}},
  year      = {2020},
  publisher = {John Wiley & Sons, Ltd},
  address   = {New York},
  isbn      = {978-1-119-63272-6}
}
and for the online version:
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@book{debrouwer2020online,
  title     = {The Big R-Book: From Data Science to Learning Machines and Big Data},
  author    = {Philippe J.S. {De Brouwer}},
  year      = {2020},
  publisher = {John Wiley & Sons, Ltd},
  address   = {New York},
  isbn      = {978-1-119-63275-7},
  doi       = {https://doi.org/10.1002/9781119632757},
  url       = {https://onlinelibrary.wiley.com/doi/abs/10.1002/9781119632757},
  eprint    = {https://onlinelibrary.wiley.com/doi/pdf/10.1002/9781119632757}
}