CRAN-R_RefreshPart2

This post follows the previous part1.

About ggplot

You have a ggplot book, and book website.

About R

You have a RGraphics book.

You have an AdvancedR book.

You have a RetEspace book, web site, book part 2, and web site part 2.

You have a Mathematical Statistics With Applications in R book.

CRAN-R_RefreshPart1

Previously

You read already my first R post, this is a refresher.

Setup

You can find R in CRAN.

Setup Related

You can find related projects in CRAN.

Setup Packages

You can find ReShape2 in GitHub or
install.packages("reshape2")
Reshape2 makes it easy to transform data between wide and long formats. reshape2 is based around two key functions: melt and cast: melt takes wide-format data and melts it into long-format data and cast takes long-format data and casts it into wide-format data.

You can find Dplyr in GitHub or

install.packages("dplyr")

Dplyr is the next iteration of plyr, focussing on only data frames. dplyr is faster and has a more consistent API.

You can find DevTools or

install.packages("devtools")

Devtools makes package development a breeze: it works with R’s existing conventions for code structure, adding efficient tools to support the cycle of package development.

You can find PackRat or

install.packages("packrat") 

A dependency management tool for R to make your R projects more isolated, portable, and reproducible.

You can  find KnitR. Elegant, flexible and fast dynamic report generation that combines R with TeX, Markdown, or HTML.

You can find RMarkdown Website or in GitHub or

install.packages("rmarkdown")

R Markdown lets you insert R code into a markdown document. R then generates a final document that replaces the R code with its results.

You can find Shiny or

install.packages("shiny")

Shiny makes it incredibly easy to build interactive web applications with R.

You can find Ggplot2 or

install.packages("ggplot2")

An enhanced data visualization package for R.

You can find GgVis or

install.packages("ggvis")

Is the next iteration of the popular ggplot2 graphics package. ggvis creates dynamic, interactive data visualizations.

You can find RforGoogleAdWord post.

Setup R-(D)COM

You can find R-(D)COM in CRAN. Also the R-(D)COM installer.

Setup RStudio

You can find it in it RStudio Website.

Setup PowerShell

You can find PowerShell R Interop in Codeplex.

CommandLineWith7zip

Command Line under 7-zip

You can use the command prompt commands.

You can use the proper software.

You can use a good setup.

WindowsEnvironmentVariables

Windows Environment Variables

SYSTEM
SystemDrive=C:
SystemRoot=C:\WINDOWS
APPS
AppsDrive=C:
AppsRoot=C:\Apps
HOME
HOMEDRIVE=C:
HOMEPATH=\Users\root
HOMEROOT=C:\Users
DATA
DataDrive=C:
DataRoot=C:\DATA
SHARE
ShareDrive=C:
ShareRoot=C:\SHARE
OPT
OptDrive=C:
OptRoot=C:\OPT

GrepEmailInTxtFilesRecursively

PowerShell can be used to grep emails from *.txt recursively

Find recursively from root C:\ in all *.txt files emails [any literal]@[any letter]anyNumberOfCharacters.[any letter]from 2 to 6 characters

Get-ChildItem C:\ -include *.txt -rec | Select-String -Pattern "\w+@[a-zA-Z_]+?\.[a-zA-Z]{2,6}" -CaseSensitive