One Page R: A Survival Guide to Data Science with R

Graham Williams
International Visiting Professor
Chinese Academy of Sciences
Shenzhen Institutes of Advanced Technology

Welcome to OnePageR. These chapters weave together a collection of tools for the data scientist. The tools are all part of the R Statistical Software Suite.

Each OnePageR chapter is actually made up of multiple pages! Each page within a chapter is a one page guide that covers a particular aspect of the topic under review.

The OnePageRs can be worked through as a hands-on guide and then used as a reference guide. Each page aims to be a bite sized chunk for hands-on learning, building on what has gone before. Many chapters also have a lecture pack and a laboratory session where a number of tasks can be completed.

The R code sitting behind each OnePageR chapter is also provided and can be easily run standalone to replicate the material presented in the chapter.

The material is always under development! Chapters will change (and hopefully improve) regularly, but links preceded with a * are more well developed. Feedback, suggestions, and ideas are more than welcome.

Refer to the Data Mining Survival Guide or my book on Data Mining with Rattle and R: The Art of Excavating Data for Knowledge Discovery (Use R) for related material.

Many of the initial chapters were developed and tested whilst visiting the Shenzhen Institutes of Technology as an International Visiting Professor of the Chinese Academy of Sciences.

The data used across the chapters is available for download as data.zip.

Enjoy!

  1. Getting Started as a Data Scientist
    1. Getting Started with R and Rattle: *Lecture - *Laboratory
    2. Introducing and Interacting with R: *Lecture - *Laboratory
    3. BasicR - OnePage(R) - Writing R scripts
  2. R for the Data Scientist
    1. A Template for Preparing Data: *OnePageR - *R
    2. A Template for Building Models: *OnePageR - *R
  3. Dealing With Data
    1. Reading Data into R: *OnePageR - *R
    2. Exploring and Summarising Data: *OnePageR - *R
    3. Visualising Data with GGPlot2: *OnePageR - *R
    4. Transforming Data: *OnePageR - *R
  4. Descriptive Analytics
    1. Cluster Analysis: *Lecture - *OnePageR - *R
    2. Association Analysis: *Lecture
  5. Predictive Analytics
    1. Decision Trees: *Lecture - *OnePageR - *R - *Rattle
    2. Ensembles of Decision Trees: *Lecture - *OnePageR - *R
    3. SVM (R)
    4. KernLab (R)
    5. NeuralNetworks (R)
    6. NNet (R)
    7. Evaluating Models: *OnePageR - *R
    8. Evaluation (R)
    9. Scoring (R)
    10. PMML (R) Exporting Models for Deployment
  6. Advanced Analytics
    1. Text Mining: *OnePageR - *R
  7. Advanced R
    1. Strings: OnePageR, R
    2. Dates and Time: (PDF, R) Dates and Time
    3. Spatial Data *OnePageR - *R
    4. (R) Spatial Analysis
    5. Big Data *OnePageR - *R
    6. Plots (PDF, R) Miscellaneous Plots
    7. Functions (PDF, R) Writing Functions in R
    8. Parallel Processing (PDF, R) Parallel Execution
  8. Expert R
    1. Packaging (R) Pulling it Together into a Package
    2. Doing R with Style: *OnePageR - *R
    3. Literate Data Mining with KnitR: *Lecture - *OnePageR - *R

OnePageR is provided under a Creative Commons Attribution-ShareAlike 3.0 Unsupported License allowing access to everyone for any purpose, and is provided at no cost. You can assist in helping cover the costs of providing this material through a $40 PayPal payment. In return we will provide you with a single PDF compilation version of the material. Your support also encourages further development of this resource.


Other great resources for modular approaches to learning R include:


Other Togaware resources:


Local package archive:

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