R Course

Cheatsheet

A quick reference — the essential R syntax on a single page. Press Ctrl/Cmd + P to print it.

Variables and Vectors

Variable Assignment
```
x <- 10
y <- 20
total <- x + y
```
Use the <- operator to assign a value to a variable in R.

Creating Vectors

numbers <- c(5, 10, 15, 20)
names <- c("Alice", "Bob")
logical_values <- c(TRUE, FALSE, TRUE)

The c() function concatenates elements into a vector of the same type.

Vectorized Operations

v1 <- c(1, 2, 3)
doubled <- v1 * 2         # c(2, 4, 6)

v2 <- c(10, 20, 30)
sum_vec <- v1 + v2        # c(11, 22, 33)

Mathematical operations applied to a vector are executed element-by-element.

Matrices and Data Frames

Matrix Creation and Access

mat <- matrix(1:6, nrow = 2, ncol = 3)

val <- mat[1, 3]          # Element (row 1, column 3)
row1 <- mat[1, ]          # Entire first row
col2 <- mat[, 2]          # Entire second column

Matrices are two-dimensional and contain elements of the same type.

Data Frame Creation and Filtering

df <- data.frame(
  name = c("Alice", "Bob"),
  grade = c(28, 24)
)

# Extract a column
grades <- df$grade

# Filter rows
good_students <- df[df$grade >= 26, ]

Data Frames can contain columns of different types and represent tabular data.

Control Flow

IF-ELSE Conditionals

score <- 75

if (score >= 60) {
  status <- "Pass"
} else {
  status <- "Fail"
}

Use round parentheses for the condition and curly braces for blocks.

FOR Loop

for (i in 1:5) {
  print(i)
}

v <- c(2, 4, 6)
for (val in v) {
  print(val * 2)
}

Iterates over elements in a sequence or a vector using the 'in' keyword.

Functions and Data Analysis

Defining Functions
```
calculate_tax <- function(amount, rate = 0.22) {
  result <- amount * rate
  return(result)
}
```
Functions can specify default parameters (like rate = 0.22) and use return() to yield a value.

Basic Statistics and NA values

temperatures <- c(22, 25, NA, 21)

# Calculate mean ignoring NA values
mean_temp <- mean(temperatures, na.rm = TRUE)

# Standard Deviation
sd_temp <- sd(temperatures, na.rm = TRUE)

# Complete statistical summary
summary_stats <- summary(temperatures)

The na.rm = TRUE argument specifies to remove missing values (NA) before running calculations.

R · Cheatsheet — eLearner.app

Variables and Vectors

Matrices and Data Frames

Control Flow

Functions and Data Analysis