R Advanced

🧠 Welcome to R Advanced! You’ve built a strong foundation—now it’s time to dive into more powerful and practical tools. In this section, you’ll explore Functions, Importing Statements, and Exploratory Data Analysis (EDA). These skills will help you write clean, reusable code and uncover meaningful insights from complex datasets. Whether you’re analyzing real-world data or building scalable scripts, this is where your R skills truly come to life.

Summary Table

Summary of the R Advanced section.

Concept	Example	Description
Basic function	`greet <- function() { print("Hi") }`	Define a reusable block of code
Parameters	`function(name) { print(name) }`	Accept input values into the function
Return values	`return(x + y)`	Send a result back to the caller
Default values	`function(name = "Guest")`	Provide fallback values for parameters
Named arguments	`fun(b = 2, a = 1)`	Pass arguments by name in any order
Variable arguments	`function(...)`	Accept any number of inputs
Access `...`	`args <- list(...)`	Convert `...` to a list of named arguments
Multiple return values	`return(list(sum = x + y, diff = x - y))`	Return a list to simulate multiple return values
Missing required argument	`fun(x) → fun()`	Error if required arg isn’t provided
Missing parentheses	`function(x` (syntax error)	Missing closing `)` breaks the function
Load a package	`library(ggplot2)`	Make all functions in a package available
Conditional loading	`if (require(pkg)) { ... }`	Load only if available; returns `TRUE/FALSE`
Aliased access	`dplyr::filter()`	Use function without loading full package
Load custom script	`source("utils.R")`	Run code from another R file
Access dataset	`data(mtcars)`	Load built-in dataset
View top rows	`head(mtcars)`	Show first 6 rows
Summary stats	`summary(df)`	Get mean, median, min, max, etc.
Handle NA	`na.omit(df)`	Remove missing data
Impute mean	`df$var[is.na(var)] <- mean(var, na.rm=TRUE)`	Replace NAs with average
Normalize	`(x - min(x)) / (max(x) - min(x))`	Rescale between 0 and 1
Scale (standardize)	`scale(df)`	Mean = 0, SD = 1
Scatter plot	`ggplot(df, aes(x, y)) + geom_point()`	Basic scatterplot using `ggplot2`
Histogram	`geom_histogram(binwidth = 2)`	Show frequency distribution
Import error	`library(badpkg)`	Error if package doesn’t exist
Function not loaded	`select(df)` without `library(dplyr)`	Error if function isn’t available in namespace