Data Science Desktop Survival Guide by Graham Williams
Desktop Survival Project Home Preface Data Science Introducing R R Constructs R Tasks R Strings R Read, Write, and Create Data Template Data Exploration Data Wrangling Data Visualisation Statistics ML Template ML Scenarios ML Activities ML Applications ML Algorithms Cluster Analysis Decision Trees Computer Vision Graph Data Privacy Literate Data Science Coding with Style Resources Bibliography Index

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Data Science Through Doing

This book takes a seriously hands on approach to doing data science. Concepts are introduced but usually with an example of the concept with some code. We use R as our language to share these concepts and demonstrate how we execute the concepts in practice. Through this guide new R commands will be introduced. The reader is encouraged to review the command's documentation and understand what the command does. Help is obtained using the ? command as in:

?read_csv

Documentation on a particular package can be obtained using the help= option of library():

library(help=tidyverse)

To learn effectively you are encouraged to run R (e.g., RStudio or Emacs with ESS mode) and to replicate the commands. Check that the output you get is the same and that you understand how it is generated. Try some variations. Explore.