R Notes for Professionalsadmin30/10/2025ProgrammingBooks Share on Facebook Share on X (Twitter) Share on LinkedIn Share on Viber Share on WhatsApp Share on Telegram Share on Email Chapters Getting started with R Language Variables Arithmetic Operators Matrices Formula Reading and writing strings String manipulation with stringi package Classes Lists Hashmaps Creating vectors Date and Time The Date class Date-time classes (POSIXct and POSIXlt) The character class Numeric classes and storage modes The logical class Data frames Split function Reading and writing tabular data in plain-text files (CSV, TSV, etc.) Pipe operators (%>% and others) Linear Models (Regression) data.table Pivot and unpivot with data.table Bar Chart Base Plotting boxplot ggplot2 Factors Pattern Matching and Replacement Run-length encoding Speeding up tough-to-vectorize code Introduction to Geographical Maps Set operations tidyverse Rcpp Random Numbers Generator Parallel processing Subsetting Debugging Installing packages Inspecting packages Creating packages with devtools Using pipe assignment in your own package %<>%: How to ? Arima Models Distribution Functions Shiny spatial analysis sqldf Code profiling Control flow structures Column wise operation JSON RODBC lubridate Time Series and Forecasting strsplit function Web scraping and parsing Generalized linear models Reshaping data between long and wide forms RMarkdown and knitr presentation Scope of variables Performing a Permutation Test xgboost R code vectorization best practices Missing values Hierarchical Linear Modeling *apply family of functions (functionals) Text mining ANOVA Raster and Image Analysis Survival analysis Fault-tolerant/resilient code Reproducible R Fourier Series and Transformations .Rprofile dplyr caret Extracting and Listing Files in Compressed Archives Probability Distributions with R R in LaTeX with knitr Web Crawling in R Creating reports with RMarkdown GPU-accelerated computing heatmap and heatmap.2 Network analysis with the igraph package Functional programming Get user input Spark API (SparkR) Meta: Documentation Guidelines Input and output I/O for foreign tables (Excel, SAS, SPSS, Stata) I/O for database tables I/O for geographic data (shapefiles, etc.) I/O for raster images I/O for R’s binary format Recycling Expression: parse + eval Regular Expression Syntax in R Regular Expressions (regex) Combinatorics Solving ODEs in R Feature Selection in R — Removing Extraneous Features Bibliography in RMD Writing functions in R Color schemes for graphics Hierarchical clustering with hclust Random Forest Algorithm RESTful R Services Machine learning Using texreg to export models in a paper-ready way Publishing Implement State Machine Pattern using S4 Class Reshape using tidyr Modifying strings by substitution Non-standard evaluation and standard evaluation Randomization Object-Oriented Programming in R Coercion Standardize analyses by writing standalone R scripts Analyze tweets with R Natural language processing R Markdown Notebooks (from RStudio) Aggregating data frames Data acquisition R memento by examples Updating R version
