published by Springer International Publishing 2017

Originally published as Datendesign mit R, 2014

www.datavisualisation-r.com

This is a well written book for designers. Part one of the book basics and techniques covers more than the basics. Fig 2.1 is of Elements of a figure. R has the commands to put all these things on a graph.

Typefaces, fonts and symbols again more information than I usually see in an R book.

Part two is the examples. 100 examples are on their web site. The examples talk about good design layout and readability.

One of my favorites is figure 6.3.7 Tree Map. Tree Map is a good way to see proportions. How much is each part of the budget. Small important items do not disappear.

Enjoy this book. I am having fun getting the code to work on other data.

This is a major update. I spent a lot of time going over the last chapters in the book.

Part 3 Data Analysis covers a different way of using ggplot2. Instead of doing analysis then plotting. Do both parts at the same time using ggplot2 plot and other new useful packages.

Chapter 9 covers tidy data. Tidy data has variables in columns and observations in rows. Straight forward but the data doesn’t always come that way. Packages tidyr and dplyr help with tidying up data.

One of things covered in Chapter 10 is pipes and the package magrittr. Using pipes makes for cleaner code.

Chapter 11 Modelling for Visualization. Introduces the new package called broom. broom package takes messy data out put of model functions such as lm, glm, anova and makes them tidy.

The beginning of the book covers aes() and that you need it for your plot and geom() you keep adding them as layers.

This a good book for learning how to use ggplot2 and new techniques for analyzing data.

I had some messy data to turn tidy. Column of data that needed to be separated into two columns. All the directions where obscure and not helpful. Try searching for a regular expression on the web.
One of the things I was puzzled over was \\.+ found out it meant gosub(). Much easier to search on. Delimiter was another puzzling thing until I realized that I could treat it the same as when I read csv files. This is the R code that worked.

The Cox Model and Its Applications published in Springer Briefs in Statistics 2016. Written by Mikhail Nikulin and Hong-Dar Isaac Wu.

I enjoyed reading this book although it has no code examples. I think I can figure out the code from the precise equations.

Cox proportional hazards model is a type of survival analysis. The proportional hazards model was put forward by Sir David Cox in 1972.

Chapter 2 covers the basic concepts for models. Including classical parametric models and how to handle censored data.

Chapter 3 covers the cox proportional hazards model including tampered failure time model.

Chapter 5 is about Cross-effect Models of Survival Functions.

5.2 Parametric Weibull Regression with Hetroscedastic Shape parameter.

There are lots more models. I recommend reading the book with a card you have written on explaining in a way you understand the definitions and symbols used in the book.

Last night I learned what step I was missing to use RStudio and GitHub together. When I needed to push code to GitHub I couldn’t get it to work. This worked:

First make a repository on GitHub.

Then copy the SSH code for cloning repositories.

Open RStudio,make a new project for the repository, go to tools tab, choose version control, pick git.

Next set up the project version control

Paste the SSH clone code in RStudio box for GitHub

Then the rest happens and RStudio is linked to GitHub and you can commit, push and pull.

I am glad I finally figured this out. Going to user groups in beneficial.

Troy Miles wrote jQuery Essentials published by Packt Publishing 2016. This is a good enough book that twice I started a review of it. The code for this book is available to download on packtpub.com

The book has good coverage of the DOM, document object model. I like the section in chapter9 about never modify the DOM in a loop.

Chapter 8 about separation of concerns covers unit tests. Tells you how to use events to decouple code. Break the code into logical units. Separation of Concerns is a useful software architecture pattern.

Practical DevOps by Joakim Verona published by Packt Publishing 2016

I am taking a DevOps class thru Hack Oregon. I found this book useful and recommended it to my class. We are learning how to use Ansible to provision and this book was most helpful. Chapter Seven has code to do Ansible and Docker together. I am working on getting this to work.