R Cheat Sheet
Last updated
Hello World & assignment
R's idiomatic assignment operator is <- (the = operator also works).
| Operation | Syntax |
|---|---|
| Print a value | print("Hello, World!") |
| Auto-print (console) | "Hello, World!" |
| Concatenate and print | cat("Hi", name, "\n") |
| Assign (idiomatic) | x <- 5 |
| Assign (also valid) | x = 5 |
| Right assign | 5 -> x |
| Comment | # this is a comment |
| Run a script | Rscript app.R |
Data types & vectors
The vector is R's fundamental data structure; even a single value is a length-1 vector.
| Operation | Syntax |
|---|---|
| Numeric vector | v <- c(1, 2, 3) |
| Character vector | s <- c("a", "b") |
| Logical vector | b <- c(TRUE, FALSE) |
| Integer sequence | 1:10 |
| Sequence with step | seq(0, 1, by = 0.1) |
| Repeat values | rep(0, times = 5) |
| Basic types | numeric, character, logical, integer, complex |
| Check / coerce type | class(x), as.numeric("42") |
Vector operations
Operations are vectorized and apply element-wise; indexing is 1-based.
| Operation | Syntax |
|---|---|
| Access element (1-based) | v[1] |
| Slice a range | v[2:4] |
| Logical filtering | v[v > 2] |
| Drop an element | v[-1] |
| Element-wise math | v * 2, v1 + v2 |
| Length | length(v) |
| Common reducers | sum(v), mean(v), max(v) |
| Sort / reverse | sort(v), rev(v) |
| Named vector | c(a = 1, b = 2) |
Data frames
A data frame is a table of columns, each a vector of equal length.
| Operation | Syntax |
|---|---|
| Create a data frame | df <- data.frame(name = c("Ada"), age = c(30)) |
| First / last rows | head(df), tail(df) |
| Dimensions | nrow(df), ncol(df), dim(df) |
| Column names | names(df), colnames(df) |
| Select a column | df$age or df[["age"]] |
| Select rows / columns | df[1, ], df[, "age"] |
| Filter rows | df[df$age > 18, ] |
| Add a column | df$adult <- df$age >= 18 |
| Summary statistics | summary(df) |
| Structure overview | str(df) |
Factors & lists
Factors store categorical data; lists hold elements of mixed types.
| Operation | Syntax |
|---|---|
| Create a factor | f <- factor(c("low", "high")) |
| Factor levels | levels(f) |
| Ordered factor | factor(x, ordered = TRUE) |
| Count by level | table(f) |
| Create a list | l <- list(name = "Ada", scores = c(1, 2)) |
| Access by name | l$name or l[["name"]] |
| Access by position | l[[1]] |
| Sublist (keeps list) | l[1] |
| Length / names | length(l), names(l) |
Control flow
Conditions go in parentheses and blocks in braces.
| Operation | Syntax |
|---|---|
| If / else if / else | if (x > 0) { ... } else if (x < 0) { ... } else { ... } |
| Vectorized if-else | ifelse(v > 0, "pos", "neg") |
| For loop | for (i in 1:10) { ... } |
| For over a vector | for (x in v) { ... } |
| While loop | while (x < 100) { ... } |
| Repeat with break | repeat { if (done) break } |
| Switch | switch(key, a = 1, b = 2) |
| Logical operators | &&, ||, ! (scalar); &, | (vector) |
Functions
Functions are first-class; the last evaluated expression is returned.
| Operation | Syntax |
|---|---|
| Define a function | add <- function(a, b) { a + b } |
| Explicit return | return(a + b) |
| Default argument | greet <- function(name = "World") { ... } |
| Variadic argument | f <- function(...) { sum(...) } |
| Call by name | box(w = 2, h = 3) |
| Anonymous function | function(x) x * 2 |
| Anonymous (shorthand) | \(x) x * 2 |
| Pass to a higher-order fn | sapply(1:3, function(x) x^2) |
The apply family
Apply a function over data without writing explicit loops.
| Function | What it does |
|---|---|
apply(m, 1, sum) | Apply over matrix rows (1) or columns (2) |
sapply(v, f) | Apply over a vector, simplify to a vector/matrix |
lapply(v, f) | Apply over a vector, always return a list |
vapply(v, f, numeric(1)) | Like sapply but with a checked return type |
mapply(f, a, b) | Apply over multiple vectors in parallel |
tapply(x, group, mean) | Apply a function per group |
Map(f, a, b) | Multivariate apply returning a list |
Reduce(+, v) | Fold a vector with a binary function |
Common data-wrangling & stats functions
Frequently used base functions for summarizing and reshaping data.
| Function | What it does |
|---|---|
mean(v) / median(v) | Average / middle value |
sd(v) / var(v) | Standard deviation / variance |
min(v) / max(v) / range(v) | Smallest / largest / both |
quantile(v) | Quantiles (e.g. quartiles) |
table(x) | Frequency counts of values |
unique(v) / duplicated(v) | Distinct values / duplicate flags |
is.na(v) / na.omit(df) | Find / drop missing values |
aggregate(y ~ g, df, mean) | Summarize y by group g |
order(v) | Index order for sorting |
cor(x, y) | Correlation between two vectors |
The R syntax you reach for most, on one page. This R cheat sheet is a quick reference for the core language - assignment and data types, vectors and vector operations, data frames, factors and lists, control flow, functions, and the apply family used across rstats data analysis.
Everything here is base R and runs on a stock install - no extra packages needed. Copy what you need, or try every snippet live in the R playground - no setup required.
R cheat sheet FAQ
Is this R cheat sheet free?
Yes. This R cheat sheet is completely free, with no sign-up required. Bookmark it and come back whenever you need to look up a vector operation, data-frame method, or stats function.
Are R vectors really 1-indexed?
v[1] returns the first element and v[length(v)] returns the last. Negative indices have a special meaning - v[-1] removes the first element rather than counting from the end. This 1-based convention runs through vectors, lists, and data frames alike.What is a data frame in R?
df[rows, columns], select a column with df$name, and inspect it with str(df) or summary(df).Can I practice R online?
Yes. Open the R playground to run any snippet from this cheat sheet in your browser - no R or RStudio to install. When you want structure, Coddy's free interactive R course takes you from vectors and data frames to the apply family and statistics step by step.
Is this cheat sheet good for beginners?
Yes. It is organized from the most common topics (assignment, vectors, data frames) down to advanced ones (the apply family and stats functions), so you can use the top sections on day one and grow into the rest.
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