r-statistics.co by Selva Prabhakaran

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R Base Functions Cheat Sheet: 100 Functions You Actually Need

These are the 100 base R functions that working data analysts and statisticians use most often. No packages required — everything here ships with R out of the box.

R has over 1,200 base functions, but most programmers rely on the same 100 day after day. This cheat sheet distills those essentials, organized by what you're trying to do. Every function includes a signature, a one-line description, and a runnable example.

Object Inspection (10 Functions)

These are the first functions you reach for when exploring unfamiliar data.

# Function What It Does Example
1 str(x) Show structure compactly str(mtcars)
2 summary(x) Statistical summary summary(iris)
3 class(x) Object class class(Sys.Date())
4 typeof(x) Internal storage type typeof(1L)
5 length(x) Number of elements length(letters)
6 dim(x) Rows and columns dim(mtcars)
7 names(x) Element/column names names(mtcars)
8 head(x, n) First n elements head(mtcars, 3)
9 tail(x, n) Last n elements tail(mtcars, 3)
10 attributes(x) All attributes attributes(mtcars)
# Inspect the built-in mtcars dataset cat("Class:", class(mtcars), "\n") cat("Dimensions:", dim(mtcars), "\n") cat("Columns:", names(mtcars), "\n") str(mtcars)


  






Creating & Combining (15 Functions)



Functions that build data structures from scratch or combine existing ones.







#
Function
What It Does
Example






11
c(...)
Combine into vector
c(1, 2, 3)




12
vector(mode, length)
Create empty vector
vector("numeric", 5)




13
list(...)
Create a list
list(a = 1, b = "two")




14
data.frame(...)
Create data frame
data.frame(x = 1:3)




15
matrix(data, nrow, ncol)
Create matrix
matrix(1:6, nrow = 2)




16
array(data, dim)
Create array
array(1:24, dim = c(2,3,4))




17
factor(x, levels)
Create factor
factor(c("a","b","a"))




18
seq(from, to, by)
Generate sequence
seq(0, 1, by = 0.1)




19
rep(x, times)
Repeat elements
rep(c("a","b"), 3)




20
cbind(...)
Bind columns
cbind(1:3, 4:6)




21
rbind(...)
Bind rows
rbind(1:3, 4:6)




22
append(x, values)
Insert into vector
append(1:3, 99, after = 1)




23
expand.grid(...)
All combinations
expand.grid(x = 1:2, y = c("a","b"))




24
do.call(fun, args)
Call with argument list
do.call(paste, list("a","b"))




25
Recall(...)
Recursive self-call
Used inside recursive functions









  


    
# Building structures
v <- c(10, 20, 30)
m <- matrix(1:9, nrow = 3)
df <- data.frame(id = 1:3, name = c("Alice","Bob","Carol"))
cat("Vector:", v, "\n")
cat("Matrix:\n"); print(m)
cat("Data frame:\n"); print(df)


    


      

      

    


    


  






Subsetting & Searching (12 Functions)



Find, filter, and extract elements from data.







#
Function
What It Does
Example






26
subset(x, ...)
Filter rows/columns
subset(mtcars, mpg > 30)




27
which(x)
Indices of TRUE values
which(c(F, T, T, F))




28
which.min(x)
Index of minimum
which.min(c(5,2,8,1))




29
which.max(x)
Index of maximum
which.max(c(5,2,8,1))




30
match(x, table)
First match positions
match("c", letters)




31
%in%
Membership test
c(1,5) %in% 1:3




32
grep(pattern, x)
Search indices
grep("mpg", names(mtcars))




33
grepl(pattern, x)
Search logical
grepl("^m", names(mtcars))




34
startsWith(x, prefix)
Starts with?
startsWith("hello", "he")




35
endsWith(x, suffix)
Ends with?
endsWith("test.csv", ".csv")




36
Find(f, x)
First matching element
Find(function(x) x>3, 1:10)




37
Position(f, x)
Index of first match
Position(function(x) x>3, 1:10)









  


    
# Finding things in data
x <- c(15, 8, 22, 3, 41, 7)
cat("Values > 10:", x[x > 10], "\n")
cat("Index of max:", which.max(x), "\n")
cat("Is 22 present?", 22 %in% x, "\n")


    


      

      

    


    


  






Math & Statistics (18 Functions)



The core numeric computation toolkit.







#
Function
What It Does
Example






38
sum(x)
Sum of elements
sum(1:100)




39
mean(x)
Arithmetic mean
mean(mtcars$mpg)




40
median(x)
Median
median(mtcars$mpg)




41
var(x)
Variance
var(mtcars$mpg)




42
sd(x)
Standard deviation
sd(mtcars$mpg)




43
min(x)
Minimum
min(mtcars$mpg)




44
max(x)
Maximum
max(mtcars$mpg)




45
range(x)
Min and max
range(mtcars$mpg)




46
quantile(x, probs)
Quantiles
quantile(mtcars$mpg, c(0.25, 0.75))




47
cor(x, y)
Correlation
cor(mtcars$mpg, mtcars$wt)




48
cumsum(x)
Cumulative sum
cumsum(1:10)




49
diff(x)
Lagged differences
diff(c(1,4,9,16))




50
abs(x)
Absolute value
abs(-5)




51
sqrt(x)
Square root
sqrt(144)




52
round(x, digits)
Round
round(pi, 3)




53
ceiling(x)
Round up
ceiling(3.01)




54
floor(x)
Round down
floor(3.99)




55
log(x)
Natural log
log(exp(5))









  


    
# Quick descriptive stats
x <- mtcars$mpg
cat("Mean:", round(mean(x), 1), "\n")
cat("SD:", round(sd(x), 1), "\n")
cat("Range:", range(x), "\n")
cat("Correlation (mpg vs wt):", round(cor(mtcars$mpg, mtcars$wt), 3), "\n")


    


      

      

    


    


  






Sorting & Ordering (5 Functions)







#
Function
What It Does
Example






56
sort(x)
Sort a vector
sort(c(3,1,4,1,5))




57
order(...)
Sort indices
order(c(3,1,2))




58
rank(x)
Rank values
rank(c(3,1,2))




59
rev(x)
Reverse vector
rev(1:5)




60
unique(x)
Remove duplicates
unique(c(1,1,2,3,3))







String Functions (12 Functions)







#
Function
What It Does
Example






61
paste(...)
Concatenate strings
paste("Hello", "World")




62
paste0(...)
Concatenate without space
paste0("id_", 1:3)




63
sprintf(fmt, ...)
Formatted string
sprintf("%.1f%%", 95.678)




64
nchar(x)
String length
nchar("hello")




65
substr(x, start, stop)
Extract substring
substr("hello", 1, 3)




66
toupper(x)
To uppercase
toupper("hello")




67
tolower(x)
To lowercase
tolower("HELLO")




68
trimws(x)
Trim whitespace
trimws("  hi  ")




69
gsub(pat, rep, x)
Replace all
gsub("[aeiou]", "*", "hello")




70
sub(pat, rep, x)
Replace first
sub("l", "L", "hello")




71
strsplit(x, split)
Split string
strsplit("a,b,c", ",")




72
format(x, ...)
Format for display
format(12345.6, big.mark = ",")









  


    
# String manipulation
x <- "  Hello, World!  "
cat("Trimmed:", trimws(x), "\n")
cat("Upper:", toupper(trimws(x)), "\n")
cat("Replace:", gsub("o", "0", x), "\n")
cat("Split:", unlist(strsplit("a-b-c", "-")), "\n")


    


      

      

    


    


  






Apply Family (8 Functions)







#
Function
What It Does
Example






73
apply(X, MARGIN, FUN)
Over rows/cols of matrix
apply(matrix(1:6,2), 2, sum)




74
lapply(X, FUN)
Over list, return list
lapply(1:3, sqrt)




75
sapply(X, FUN)
Over list, simplify
sapply(1:5, function(x) x^2)




76
vapply(X, FUN, type)
Type-safe sapply
vapply(1:3, sqrt, numeric(1))




77
tapply(X, INDEX, FUN)
By group
tapply(mtcars$mpg, mtcars$cyl, mean)




78
mapply(FUN, ...)
Multiple inputs
mapply(paste, 1:3, c("a","b","c"))




79
Reduce(f, x)
Accumulate
Reduce("+", 1:10)




80
Filter(f, x)
Keep matches
Filter(is.numeric, list(1,"a",3))









  


    
# Apply family showcase
cat("Column means:\n")
print(round(apply(mtcars[,1:4], 2, mean), 1))
cat("\nMPG by cylinder:\n")
print(round(tapply(mtcars$mpg, mtcars$cyl, mean), 1))


    


      

      

    


    


  






IO & File System (10 Functions)







#
Function
What It Does
Example






81
read.csv(file)
Read CSV
read.csv("data.csv")




82
write.csv(x, file)
Write CSV
write.csv(df, "out.csv")




83
readRDS(file)
Read R object
readRDS("model.rds")




84
saveRDS(object, file)
Save R object
saveRDS(fit, "model.rds")




85
readLines(con, n)
Read text lines
readLines("log.txt", 10)




86
writeLines(text, con)
Write text lines
writeLines(c("a","b"), "out.txt")




87
cat(...)
Print to console
cat("value:", 42, "\n")




88
print(x)
Print object
print(head(mtcars))




89
getwd()
Working directory
getwd()




90
file.exists(x)
File exists?
file.exists("data.csv")







Control Flow & Error Handling (10 Functions)







#
Function
What It Does
Example






91
if/else
Conditional
if (x > 0) "pos" else "neg"




92
ifelse(test, yes, no)
Vectorized conditional
ifelse(1:5 > 3, "hi", "lo")




93
switch(expr, ...)
Multi-branch
switch("b", a=1, b=2, c=3)




94
for(var in seq)
Loop
for (i in 1:5) cat(i)




95
while(cond)
While loop
while(x < 10) x <- x + 1




96
tryCatch(expr, ...)
Error handling
tryCatch(log(-1), warning=function(w) NA)




97
try(expr)
Try without stopping
try(log("a"), silent = TRUE)




98
stop(msg)
Throw error
stop("x must be positive")




99
warning(msg)
Issue warning
warning("Unusual value")




100
message(msg)
Print message
message("Processing done")









  


    
# Error handling in practice
safe_log <- function(x) {
  tryCatch(
    log(x),
    warning = function(w) { message("Warning: ", w$message); NA },
    error = function(e) { message("Error: ", e$message); NA }
  )
}
cat("log(10):", safe_log(10), "\n")
cat("log(-1):", safe_log(-1), "\n")
cat("log('a'):", safe_log("a"), "\n")


    


      

      

    


    


  






Summary: The Top 20 You'll Use Daily







Rank
Function
Category






1
c()
Creating




2
str()
Inspection




3
head()
Inspection




4
summary()
Statistics




5
mean()
Statistics




6
length()
Inspection




7
names()
Inspection




8
paste0()
Strings




9
sapply()
Apply




10
which()
Searching




11
cat()
IO




12
read.csv()
IO




13
class()
Inspection




14
ifelse()
Control




15
unique()
Manipulation




16
subset()
Subsetting




17
gsub()
Strings




18
round()
Math




19
sort()
Sorting




20
tryCatch()
Error handling







FAQ



What counts as "base R"? Base R means functions available without loading any packages. These come from the base, utils, stats, grDevices, and graphics packages that ship with every R installation.



Should I learn base R or tidyverse first? Learn base R first. Understanding c(), [, $, apply(), and the type system makes tidyverse code easier to debug and understand. Tidyverse is built on top of base R, not a replacement.



How can I check all arguments a function accepts? Use args(function_name) or ?function_name. For example, args(read.csv) shows all parameters, and ?read.csv opens the full help page with descriptions.



What's Next




        


        
      


      

        

        
© 2016- Selva Prabhakaran.
          This work is licensed under the Creative Commons License.