A book about R exported from the Stack Overflow Documentation project.
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Description
Contained in this training
Content list
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About
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Chapter 1: Getting started with R Language
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Chapter 2: Variables
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Chapter 3: Arithmetic Operators
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Chapter 4: Matrices
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Chapter 5: Formula
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Chapter 6: Reading and writing strings
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Chapter 7: String manipulation with stringi package
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Chapter 8: Classes
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Chapter 9: Lists
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Chapter 10: Hashmaps
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Chapter 11: Creating vectors
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Chapter 12: Date and Time
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Chapter 13: The Date class
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Chapter 14: Date-time classes (POSIXct and POSIXlt)
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Chapter 15: The character class
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Chapter 16: Numeric classes and storage modes
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Chapter 17: The logical class
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Chapter 18: Data frames
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Chapter 19: Split function
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Chapter 20: Reading and writing tabular data in plain-text files (CSV, TSV, etc.)
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Chapter 21: Pipe operators (%>% and others)
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Chapter 22: Linear Models (Regression)
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Chapter 23: data.table
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Chapter 24: Pivot and unpivot with data.table
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Chapter 25: Bar Chart
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Chapter 26: Base Plotting
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Chapter 27: boxplot
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Chapter 28: ggplot2
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Chapter 29: Factors
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Chapter 30: Pattern Matching and Replacement
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Chapter 31: Run-length encoding
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Chapter 32: Speeding up tough-to-vectorize code
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Chapter 33: Introduction to Geographical Maps
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Chapter 34: Set operations
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Chapter 35: tidyverse
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Chapter 36: Rcpp
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Chapter 37: Random Numbers Generator
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Chapter 38: Parallel processing
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Chapter 39: Subsetting
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Chapter 40: Debugging
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Chapter 41: Installing packages
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Chapter 42: Inspecting packages
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Chapter 43: Creating packages with devtools
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Chapter 44: Using pipe assignment in your own package %<>%: How to ?
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Chapter 45: Arima Models
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Chapter 46: Distribution Functions
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Chapter 47: Shiny
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Chapter 48: spatial analysis
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Chapter 49: sqldf
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Chapter 50: Code profiling
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Chapter 51: Control flow structures
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Chapter 52: Column wise operation
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Chapter 53: JSON
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Chapter 54: RODBC
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Chapter 55: lubridate
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Chapter 56: Time Series and Forecasting
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Chapter 57: strsplit function
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Chapter 58: Web scraping and parsing
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Chapter 59: Generalized linear models
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Chapter 60: Reshaping data between long and wide forms
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Chapter 61: RMarkdown and knitr presentation
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Chapter 62: Scope of variables
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Chapter 63: Performing a Permutation Test
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Chapter 64: xgboost
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Chapter 65: R code vectorization best practices
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Chapter 66: Missing values
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Chapter 67: Hierarchical Linear Modeling
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Chapter 68: *apply family of functions (functionals)
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Chapter 69: Text mining
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Chapter 70: ANOVA
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Chapter 71: Raster and Image Analysis
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Chapter 72: Survival analysis
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Chapter 73: Fault-tolerant/resilient code
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Chapter 74: Reproducible R
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Chapter 75: Fourier Series and Transformations
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Chapter 76: .Rprofile
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Chapter 77: dplyr
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Chapter 78: caret
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Chapter 79: Extracting and Listing Files in Compressed Archives
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Chapter 80: Probability Distributions with R
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Chapter 81: R in LaTeX with knitr
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Chapter 82: Web Crawling in R
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Chapter 83: Creating reports with RMarkdown
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Chapter 84: GPU-accelerated computing
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Chapter 85: heatmap and heatmap.2
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Chapter 86: Network analysis with the igraph package
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Chapter 87: Functional programming
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Chapter 88: Get user input
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Chapter 89: Spark API (SparkR)
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Chapter 90: Meta: Documentation Guidelines
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Chapter 91: Input and output
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Chapter 92: I/O for foreign tables (Excel, SAS, SPSS, Stata)
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Chapter 93: I/O for database tables
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Chapter 94: I/O for geographic data (shapefiles, etc.)
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Chapter 95: I/O for raster images
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Chapter 96: I/O for R's binary format
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Chapter 97: Recycling
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Chapter 98: Expression: parse + eval
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Chapter 99: Regular Expression Syntax in R
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Chapter 100: Regular Expressions (regex)
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Chapter 101: Combinatorics
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Chapter 102: Solving ODEs in R
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Chapter 103: Feature Selection in R -- Removing Extraneous Features
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Chapter 104: Bibliography in RMD
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Chapter 105: Writing functions in R
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Chapter 106: Color schemes for graphics
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Chapter 107: Hierarchical clustering with hclust
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Chapter 108: Random Forest Algorithm
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Chapter 109: RESTful R Services
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Chapter 110: Machine learning
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Chapter 111: Using texreg to export models in a paper-ready way
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Chapter 112: Publishing
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Chapter 113: Implement State Machine Pattern using S4 Class
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Chapter 114: Reshape using tidyr
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Chapter 115: Modifying strings by substitution
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Chapter 116: Non-standard evaluation and standard evaluation
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Chapter 117: Randomization
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Chapter 118: Object-Oriented Programming in R
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Chapter 119: Coercion
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Chapter 120: Standardize analyses by writing standalone R scripts
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Chapter 121: Analyze tweets with R
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Chapter 122: Natural language processing
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Chapter 123: R Markdown Notebooks (from RStudio)
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Chapter 124: Aggregating data frames
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Chapter 125: Data acquisition
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Chapter 126: R memento by examples
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Chapter 127: Updating R version
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Credits
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