Learning R

Download free course Learning R, pdf file on 619 pages by Stack Overflow Community.
R is a programming language and free software environment for statistical computing and graphics. It is an unofficial and free R ebook created for educational purposes. All the content is extracted from Stack Overflow Documentation, which is written by many hardworking individuals at Stack Overflow.

Table of contents

  • Getting started with R Language
  • *apply family of functions (functionals)
  • .Rprofile
  • Aggregating data frames
  • Analyze tweets with R
  • Arima Models
  • Arithmetic Operators
  • Bar Chart
  • Base Plotting
  • Bibliography in RMD
  • boxplot
  • caret
  • Classes
  • Cleaning data
  • Code profiling
  • Coercion
  • Color schemes for graphics
  • Column wise operation
  • Combinatorics
  • Control flow structures
  • Creating packages with devtools
  • Creating reports with RMarkdown
  • Creating vectors
  • Data acquisition
  • Data frames
  • data.table
  • Date and Time
  • Date-time classes (POSIXct and POSIXlt)
  • Debugging
  • Distribution Functions
  • dplyr
  • Expression: parse + eval
  • Extracting and Listing Files in Compressed Archives
  • Factors
  • Fault-tolerant/resilient code
  • Feature Selection in R - Removing Extraneous Features
  • Formula
  • Fourier Series and Transformations
  • Functional programming
  • Generalized linear models
  • Get user input
  • ggplot2
  • GPU-accelerated computing
  • Hashmaps
  • heatmap and heatmap.2
  • Hierarchical clustering with hclust
  • Hierarchical Linear Modeling
  • I/O for database tables
  • I/O for foreign tables (Excel, SAS, SPSS, Stata)
  • I/O for geographic data (shapefiles, etc.)
  • I/O for raster images
  • I/O for R's binary format
  • Implement State Machine Pattern using S4 Class
  • Input and output
  • Inspecting packages
  • Installing packages
  • Introduction to Geographical Maps
  • Introspection
  • JSON
  • Linear Models (Regression)
  • Lists
  • lubridate
  • Machine learning
  • Matrices
  • Meta: Documentation Guidelines
  • Missing values
  • Modifying strings by substitution
  • Natural language processing
  • Network analysis with the igraph package
  • Non-standard evaluation and standard evaluation
  • Numeric classes and storage modes
  • Object-Oriented Programming in R
  • Parallel processing
  • Pattern Matching and Replacement
  • Performing a Permutation Test
  • Pipe operators (%>% and others)
  • Pivot and unpivot with data.table
  • Probability Distributions with R
  • Publishing
  • R code vectorization best practices
  • R in LaTeX with knitr
  • R Markdown Notebooks (from RStudio)
  • R memento by examples
  • Random Forest Algorithm
  • Random Numbers Generator
  • Randomization
  • Raster and Image Analysis
  • Rcpp
  • Reading and writing strings
  • Reading and writing tabular data in plain-text files (CSV, TSV, etc.)
  • Recycling
  • Regular Expression Syntax in R
  • Regular Expressions (regex)
  • Reproducible R
  • Reshape using tidyr
  • Reshaping data between long and wide forms
  • RESTful R Services
  • RMarkdown and knitr presentation
  • roxygen2
  • Run-length encoding
  • Scope of variables
  • Set operations
  • Shiny
  • Solving ODEs in R
  • Spark API (SparkR)
  • spatial analysis
  • Speeding up tough-to-vectorize code
  • Split function
  • sqldf
  • Standardize analyses by writing standalone R scripts
  • String manipulation with stringi package
  • strsplit function
  • Subsetting
  • Survival analysis
  • Text mining
  • The character class
  • The Date class
  • The logical class
  • tidyverse
  • Time Series and Forecasting
  • Updating R and the package library
  • Updating R version
  • Using pipe assignment in your own package %<>%: How to ?
  • Using texreg to export models in a paper-ready way
  • Variables
  • Web Crawling in R
  • Web scraping and parsing
  • Writing functions in R
  • xgboost
Pages : 619
Size : 10.2 MB
File type : PDF
Downloads: 45
Created: 2022-02-03
License: CC BY-SA
Author(s): Stack Overflow Community
Learning R

Others Computer science Tutorials

Making Servers Work


Think Complexity

Learning LaTeX

Azure Functions Succinctly

Others related eBooks about Learning R

Marketing and Advertising Using Google

Download free course Marketing and Advertising Using Google, pdf file on 156 pages by Google, Karl Barksdale....

Automated Machine Learning: Methods, Systems, Challenges

This open access book presents the first comprehensive overview of general methods in Automated Machine Learning (AutoML), collects descriptions of existing systems based on these methods, and discusses the first series of international challenges of AutoML systems. ...

Introduction to XSLT

Download training document course in PDF intituled Introduction to XSLT, free tutorial for beginners by Deborah Aleyne Lapeyre and B. Tommie Usdin....

Azure Cognitive Services Succinctly

Download free course Azure Cognitive Services Succinctly, pdf file on 115 pages by by Ed Freitas....


Download free course Pro TBB, pdf file on 754 pages by Michael Voss, Rafael  Asenjo, James Reinders....

Essential Coding Theory

Error-correcting codes (henceforth, just codes) are clever ways of representing data so that one can recover the original information even if parts of it are corrupted. The basic idea is to judiciously introduce redundancy so that the original information can be recovered even when parts of the (r...

Fundamentals of Business Process Management

Download free course Fundamentals of Business Process Management, pdf file on 546 pages by Marlon Dumas, Marcello La Rosa, Jan Mendling, Hajo A. Reijers....

The Next.js Handbook

Download free course The Next.js Handbook, pdf file on 102 pages by Flavio Copes....

LaTeX in 24 Hours

Download free course LaTeX in 24 Hours, pdf file on 309 pages by Dilip Datta....

Information ­technology ­project managers' ­competencies

Download free course Information ­technology ­project managers' ­competencies, pdf file on 269 pages by Carl Marnewick, Wikus Erasmus, Nazeer Joseph....