R

R is a programming language specialized in statistics, designed from the ground up for data processing, analysis, and visualization. It’s difficult to compare its complexity to other statistical packages, but in terms of implementing statistics, it undoubtedly holds an unrivaled position and status. Since 2020, efforts have been made to popularize Julia, but there are aspects of practical statistical analysis where R is hard to replace, hence the continued support and enhancement of R content is planned.

Tutorial

• How to Install R on Ubuntu

Errors

• Solving the ‘unexpected else in else’ Error when Using the else if Statement
• Resolving ‘Warning in install.packages: lib = CProgram FilesRR-361library is not writable’ When Installing Packages
• Fixing the Error: ‘C:\U’ used without hex digits in character string starting ‘C:\U’ When Reading Files or Changing Paths

Tips

• Removing All Variables, Clearing Console Window
• Removing Limit on Number of Digits Displayed
• Checking Current OS Information with Sys.info()
• Checking Current Date and Time with Sys.Date(), Sys.time()
• Defining the Modulo Operator %%
• Using the Pipe Operator %>%,
• Measuring Code Execution Time, Benchmarking with system.time()
• Parallel Processing
• Getting a List of Files in a Directory with list.files()

Data Processing

• Loading Built-in Datasets
• Importing External Data
  • Quickly Reading Data Files with read_csv()
• Converting Numeric Values in Categorical Data to Numeric Data
• Removing NA Values
• Handling Strings
  • Combining a Vector of Strings into One String with collapse
• Filtering Data Conditionally
• Exploring Data Structures with str()
• Comparing Elements of Two Arrays with %in%, intersect(), setdiff()
• Standardizing Data, Viewing Standardized Residuals with rstudent()
• Finding Positions of Maximum and Minimum Values with which()
• Referencing Metadata, Attributes with attr()

Lists and Data Frames

• Various Ways to Reference Lists
• Decomposing Lists, Removing Duplicate Elements with unlist(), unique()
• Sorting Data Frames by Columns
• Transposing Rows and Columns in Data Frames
• Renaming Columns and Rows in Data Frames with names(), dimnames()
• Differences in the start, end Options in the ts() Function and the start, end Options in the window() Function

Computation

• Calculating Quotients and Remainders
• Calculating Matrix Products, Inverses, and Transposes
• Using Bootstrap Functions
• Rounding Up, Down, and to Specific Decimal Places
• Various Distribution Functions
• Calculating Conditional Sums and Averages
• Calculating Derivatives with grad()
• Calculating Definite Integrals with integrate()
• Working with Complex Numbers
• Calculating Jacobian and Hessian Matrices with jacobian(), hessian()
• Calculating Dot Products Between Vectors with %*%, %o%

Visualization

• Drawing Graphs with plot()
  • Plotting Function Graphs
• Drawing Horizontal and Vertical Lines with abline()
• Adding Text to Plots with text()
• Using Symbols in Plots with pch
• Adding Subscripts to Axis Labels with expression()
• Refining Histograms with nclalss
• Adding Legends with legend()
• Using Logarithmic Scaling with log="xy"
• Plotting Points with Colored Borders

ggplot2

The introduction to ggplot2 remains a project to be completed.