R, No Tears

Preface

This book is a tutorial on programming R. To follow along and execute the code samples, you will need Docker installed. The Docker container is located on Docker Hub. After you install Docker, you may run the container as follows.

docker run -it \
 -p 8888:8888 \
 -v $HOME/git/books/sphinx/r-intro/source:/root/ipynb \
 oneoffcoder/book-r-intro

This Docker container runs JupyterLab on port 8888. You may access JupyterLab at http://localhost:8888 when the container is running.

The diagram below summarizes the structure of the R book from core language ideas into statistical work, visualization, and applied data science topics.

Read that map as a progression from language fluency into analysis workflows. The later chapters assume you can already shape data and write small functions comfortably.

Core

• 1. Getting Started
  • 1.1. Choose an environment
  • 1.2. Install packages
  • 1.3. Load packages
  • 1.4. Get help
  • 1.5. Keep moving
• 2. Data Types
  • 2.1. Numerics
  • 2.2. Special values
  • 2.3. Characters
  • 2.4. Logicals
• 3. Data Structures
  • 3.1. Vectors
  • 3.2. Matrix
  • 3.3. Lists
  • 3.4. Data Frames
• 4. Control Structures
  • 4.1. if-else
  • 4.2. For loops
  • 4.3. While loops
  • 4.4. Conditions
• 5. Functions
  • 5.1. Optional arguments
  • 5.2. Functions as arguments
  • 5.3. Built-in functions
• 6. Functional Programming
  • 6.1. Mapping
  • 6.2. Reducing
  • 6.3. Filtering
  • 6.4. Map, filter, reduce
• 7. Object-Oriented Programming
  • 7.1. S3
  • 7.2. S4
  • 7.3. R6
• 8. Formulas

Statistics

• 1. Data Manipulation
  • 1.1. dplyr
  • 1.2. tidyr
  • 1.3. purrrr
  • 1.4. readr
• 2. Descriptive Statistics
  • 2.1. Summarization
  • 2.2. Cumulative
  • 2.3. Tables
  • 2.4. Stem
  • 2.5. Histogram
  • 2.6. Density
• 3. Data Distributions
  • 3.1. Normal distribution
  • 3.2. Other distributions
  • 3.3. Normality test
  • 3.4. Comparing two distributions
  • 3.5. Quantile-Quantile Plot
• 4. Hypothesis Testing
  • 4.1. Student’s t-test
  • 4.2. Wilcoxon U-Test
  • 4.3. Correlation
  • 4.4. Chi-squared test
  • 4.5. Analysis of variance

Graphs

• 1. Plotting
  • 1.1. Box plot
  • 1.2. Scatter plot
  • 1.3. Pairs plot
  • 1.4. Line plot
  • 1.5. Pie charts
  • 1.6. Dot charts
  • 1.7. Bar chart
• 2. ggplot2
  • 2.1. Geometries
  • 2.2. Aesthetic mapping
  • 2.3. Position
  • 2.4. Scale
  • 2.5. Coordinate
  • 2.6. Facets
  • 2.7. Labels and annotations
  • 2.8. Choropleth map
  • 2.9. Subplots

Data Science

• 1. Regression
  • 1.1. Simple regression
  • 1.2. Multiple regression
  • 1.3. Comparing models
• 2. Logistic Regression
  • 2.1. Generate data
  • 2.2. Learn model
  • 2.3. Model summary
  • 2.4. Coefficients
  • 2.5. Coefficient odds ratio
  • 2.6. Coefficient confidence intervals
  • 2.7. Odds ratio with confidence intervals
  • 2.8. Fitted values
  • 2.9. R-squared
  • 2.10. Diagnostic plots
• 3. Classification
  • 3.1. Simulate data
  • 3.2. Classification methods
• 4. Clustering
  • 4.1. K-means
  • 4.2. Ward hierarchical clustering
  • 4.3. Model based
  • 4.4. Comparing clustering solutions
  • 4.5. Silhouette score
• 5. Missing Data
  • 5.1. Generate data
  • 5.2. Visualize missingness
  • 5.3. MICE
  • 5.4. Amelia
  • 5.5. missForest
  • 5.6. Hmisc
  • 5.7. mi
• 6. Validation
  • 6.1. Generate data
  • 6.2. Generate missing data
  • 6.3. Split data
  • 6.4. Profile data
  • 6.5. One-hot encoding
  • 6.6. Imputation
  • 6.7. Rescale
  • 6.8. Feature importance
  • 6.9. Feature selection
  • 6.10. Training
  • 6.11. Predicting on validation data

Other

• 1. Miscellaneous
  • 1.1. Listing installed packages
  • 1.2. Installing packages
  • 1.3. Loading packages
  • 1.4. Benchmarking code
  • 1.5. Cheat sheets

About

One-Off Coder is an education, services, and product company. Visit us online to learn how we may help you achieve lifelong success in your personal coding career or with your company’s business goals and objectives.

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Copyright

This work is licensed under a Creative Commons Attribution 4.0 International License by One-Off Coder.



The full source code is available on GitHub.

Cite this book as follows.:

@misc{oneoffcoder_r_programming_2019,
title={R, No Tears},
url={https://r.oneoffcoder.com},
author={One-Off Coder},
year={2019},
month={Nov}}

Author

Jee Vang, Ph.D.

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