020-book_list.Rmd

# Career & Community

## Build Your Career in Data Science
Not R-specific but a great read! 

https://www.manning.com/books/build-a-career-in-data-science


##  Twitter for R Programmers
[Oscar Baruffa](https://twitter.com/OscarBaruffa), [Veerle van Son](https://twitter.com/veerlevanson)

A guide to help R programmers join the very active and friendly community on Twitter.

https://www.t4rstats.com


##  Twitter for Scientists
https://t4scientists.com/

# Blogdown
## blogdown: Creating Websites with R Markdown
https://bookdown.org/yihui/blogdown/

# Bookdown
##  bookdown: Authoring Books and Technical Documents with R Markdown
https://bookdown.org/yihui/bookdown/

##  A Minimal Book Example
https://benmarwick.github.io/bookdown-ort/



# Data Science
## R for Data Science 
Whickham and Grolemund

A really good place to start

https://r4ds.had.co.nz/

## R for Data Science Solutions
Solutions for the hadley and Grolemund R4Ds book

https://jrnold.github.io/r4ds-exercise-solutions/

## Introduction to Data Science 
Rafael A Irizarry 

Pay what you want, minimum $0.00

https://leanpub.com/datasciencebook


## R Programming for Data Science
Roger Peng

https://bookdown.org/rdpeng/rprogdatascience/

## Exploratory Data Analysis… by Roger D. Peng 
Pay what you want, minimum $0.00

https://leanpub.com/exdata

## edav.info/
https://edav.info/

## APS 135: Introduction to Exploratory Data Analysis with R
https://dzchilds.github.io/eda-for-bio/


# Data Visualization

##  ggplot2: Elegant Graphics for Data Analysis
https://ggplot2-book.org/

## ggplot2 in 2 
Lucy D'Agostino McGowan

Pay what you want, minimum $4.99

Really good overview of Ggplot2. Oscar Baruffa made a sped-up [screencast](https://youtu.be/_G7_J8M9588) while working through it. 

https://leanpub.com/ggplot2in2


##  Data Visualization - A practical introduction
https://socviz.co/


## Data Processing & Visualization
https://m-clark.github.io/data-processing-and-visualization/

## Data Visualization in R
Brooke Anderson

https://geanders.github.io/navy_public_health/index.html#prerequisites

## Data Visualization with R
Rob Kabakoff

https://rkabacoff.github.io/datavis/

## R Graphics Cookbook, 2nd edition
https://r-graphics.org/



## plotly Interactive web-based data visualization with R, plotly, and shiny
https://plotly-r.com/

## BBC Visual and Data Journalism cookbook for R graphics
https://bbc.github.io/rcookbook/


## Fundamentals of Data Visualization
https://clauswilke.com/dataviz/

# Distributed computing
## Mastering Spark with R
https://therinspark.com/


# Getting, cleaning and wrangling data
##  A Beginner's Guide to Clean Data - beginners-guide-to-clean-data
https://b-greve.gitbook.io/beginners-guide-to-clean-data/

## 21 Recipes for Mining Twitter Data with rtweet
https://rud.is/books/21-recipes/

## Text Mining with R
https://www.tidytextmining.com/

## Spreadsheet Munging Strategies
Great for dealing with messy spreadsheets

https://nacnudus.github.io/spreadsheet-munging-strategies/




# Geospatial

## Geocomputation with R
https://geocompr.robinlovelace.net/

## Spatial Data Science
https://keen-swartz-3146c4.netlify.app/

## Geospatial Health Data: Modeling and Visualization with R-INLA and Shiny
https://www.paulamoraga.com/book-geospatial/

## Introduction to R - R Spatial
https://rspatial.org/intr/index.html


# Machine Learning

##  Hands-On Machine Learning with R
https://bradleyboehmke.github.io/HOML/

## Feature Engineering and Selection: A Practical Approach for Predictive Models
http://www.feat.engineering/index.html


# Network analysis
##  Network Analysis in R Cookbook
http://sachaepskamp.com/files/Cookbook.html

# R Markdown

## Getting used to R, RStudio, and R Markdown
https://bookdown.org/chesterismay/rbasics/

## Introduction to R Markdown
https://m-clark.github.io/Introduction-to-Rmarkdown/

## RMarkdown for Scientists
https://rmd4sci.njtierney.com/

## Pimp my RMD: a few tips for R Markdown
https://holtzy.github.io/Pimp-my-rmd/



# R programming
##  Modern R with the tidyverse
https://b-rodrigues.github.io/modern_R/

##  What They Forgot to Teach You About R
https://rstats.wtf/

## Field Guide to the R Ecosystem
https://fg2re.sellorm.com/

## YaRrr! The Pirate’s Guide to R
https://bookdown.org/ndphillips/YaRrr/

## Advanced R.
http://adv-r.had.co.nz/

## R packages
http://r-pkgs.had.co.nz/


## Efficient R programming
https://csgillespie.github.io/efficientR/

## The Tidyverse Cookbook
https://rstudio-education.github.io/tidyverse-cookbook/

## Hands-On Programming with R
https://rstudio-education.github.io/hopr/

## The R Language
[R Core team](https://stat.ethz.ch/R-manual/R-patched/doc/AUTHORS)
https://stat.ethz.ch/R-manual/R-patched/doc/html/

## R language for programmers
[John D Cook](https://www.johndcook.com/blog/services-2/)
https://www.johndcook.com/blog/r_language_for_programmers/

## R Cookbook - 2nd edition
JD Long, Paul Teetor

Not to be confused with Cookbook for R
https://rc2e.com/index.html

## Cookbook for R
Winston Chang

Not to be confused with R Cookbook
http://www.cookbook-r.com/


## Tidy evaluation
https://tidyeval.tidyverse.org/

## Python to R: The Tidynomicon
http://tidynomicon.tech/



## A sufficient Introduction to R
Derek l. Sonderegger
https://dereksonderegger.github.io/570L/


# Shiny
## A gRadual intRoduction to Shiny
https://laderast.github.io/gradual_shiny/

##  Mastering Shiny
https://mastering-shiny.org/


##  Shiny Production with AWS Book
https://business-science.github.io/shiny-production-with-aws-book/

# Statistics

##  Common statistical tests are linear models: a work through
https://steverxd.github.io/Stat_tests/

## Learning statistics with R: A tutorial for psychology students and other beginners. (Version 0.6.1)
https://learningstatisticswithr-bookdown.netlify.app/

## Answering questions with data
Matthew J. Crump

Looks like a comprehensive stats resource!

https://crumplab.github.io/statistics/

## Forecasting: Principles and Practice
https://otexts.com/fpp2/


## stats545
https://stat545.com/


## An Introduction to Statistical and Data Sciences via R
https://moderndive.com/


# Version control
## Happy Git and GitHub for the useR
https://happygitwithr.com/

# Workflow
##  How I Use R
https://howiuser.com/

## Agile Data Science with R
https://edwinth.github.io/ADSwR/

# Field specific
##  Analyzing Financial and Economic Data with R
https://www.msperlin.com/afedR/

##  Data Science in Education Using R
https://datascienceineducation.com/

## The Plain Person’s Guide to Plain Text Social Science
https://plain-text.co/index.html#introduction

## Technical Foundations of Informatics
https://info201.github.io/

## Practical R for Mass Communication and Journalism
http://www.machlis.com/R4Journalists/index.html

## Computational Genomics with R
http://compgenomr.github.io/book/

## Introduction to Econometrics with R
https://www.econometrics-with-r.org/

# Other compendiums
##  Data Science with R: A Resource Compendium
Another big book of resources!

https://bookdown.org/martin_monkman/DataScienceResources_book/