46  R Command Reference

This appendix provides a comprehensive reference for R commands, covering both base R and tidyverse functions.

46.1 Base R Fundamentals

Assignment and Basic Operations

Operation	Syntax	Example
Assignment	<- or =	x <- 5
Print value	Variable name or print()	x or print(x)
Comment	#	# This is a comment
Help	? or help()	?mean
Examples	example()	example(mean)
Search help	?? or help.search()	??regression

Arithmetic Operators

Operator	Description	Example
+	Addition	5 + 3
-	Subtraction	5 - 3
*	Multiplication	5 * 3
/	Division	5 / 3
^ or **	Exponentiation	5^3
%%	Modulo (remainder)	5 %% 3
%/%	Integer division	5 %/% 3

Comparison Operators

Operator	Description	Example
==	Equal to	x == 5
!=	Not equal to	x != 5
<	Less than	x < 5
>	Greater than	x > 5
<=	Less than or equal	x <= 5
>=	Greater than or equal	x >= 5

Logical Operators

Operator	Description	Example
&	AND (element-wise)	x > 0 & x < 10
|	OR (element-wise)	x < 0 | x > 10
!	NOT	!is.na(x)
&&	AND (single value)	cond1 && cond2
||	OR (single value)	cond1 || cond2
%in%	Value in set	x %in% c(1, 2, 3)
xor()	Exclusive OR	xor(TRUE, FALSE)

46.2 Vector Operations

Creating Vectors

Function	Description	Example
c()	Combine values	c(1, 2, 3, 4, 5)
:	Sequence	1:10
seq()	Sequence with step	seq(0, 1, by = 0.1)
seq_len()	Sequence of length n	seq_len(10)
seq_along()	Sequence along object	seq_along(x)
rep()	Repeat values	rep(1, times = 5)
rep()	Repeat each	rep(1:3, each = 2)
vector()	Create empty vector	vector("numeric", 10)

Vector Indexing

Syntax	Description	Example
x[i]	Element at position i	x[3]
x[c(i,j)]	Multiple elements	x[c(1, 3, 5)]
x[-i]	Exclude element	x[-1]
x[condition]	Logical subsetting	x[x > 5]
x[1:n]	Range of elements	x[1:5]
x["name"]	By name	x["first"]

Vector Functions

Function	Description	Example
length()	Number of elements	length(x)
sum()	Sum of elements	sum(x)
mean()	Arithmetic mean	mean(x)
median()	Median value	median(x)
sd()	Standard deviation	sd(x)
var()	Variance	var(x)
min()	Minimum	min(x)
max()	Maximum	max(x)
range()	Range (min and max)	range(x)
quantile()	Quantiles	quantile(x, 0.5)
sort()	Sort values	sort(x)
order()	Indices for sorting	order(x)
rev()	Reverse order	rev(x)
unique()	Unique values	unique(x)
table()	Frequency table	table(x)
cumsum()	Cumulative sum	cumsum(x)
diff()	Differences	diff(x)
which()	Indices where TRUE	which(x > 5)
which.max()	Index of max	which.max(x)
which.min()	Index of min	which.min(x)

46.3 Data Frames

Creating Data Frames

Function	Description	Example
data.frame()	Create data frame	data.frame(x = 1:3, y = c("a", "b", "c"))
tibble()	Create tibble	tibble(x = 1:3, y = c("a", "b", "c"))
as.data.frame()	Convert to data frame	as.data.frame(matrix)
as_tibble()	Convert to tibble	as_tibble(df)

Data Frame Indexing

Syntax	Description	Example
df$col	Column by name	df$age
df[, "col"]	Column as vector	df[, "age"]
df["col"]	Column as data frame	df["age"]
df[i, ]	Row by position	df[1, ]
df[i, j]	Element	df[1, 2]
df[condition, ]	Filter rows	df[df$age > 25, ]

Data Frame Functions

Function	Description	Example
nrow()	Number of rows	nrow(df)
ncol()	Number of columns	ncol(df)
dim()	Dimensions	dim(df)
names()	Column names	names(df)
colnames()	Column names	colnames(df)
rownames()	Row names	rownames(df)
head()	First rows	head(df, 10)
tail()	Last rows	tail(df, 10)
str()	Structure	str(df)
summary()	Summary statistics	summary(df)
glimpse()	Tidyverse structure	glimpse(df)
View()	Open viewer	View(df)

46.4 Reading and Writing Data

Base R I/O

Function	Description	Example
read.csv()	Read CSV	read.csv("file.csv")
read.table()	Read table	read.table("file.txt", header = TRUE)
read.delim()	Read tab-delimited	read.delim("file.tsv")
write.csv()	Write CSV	write.csv(df, "file.csv", row.names = FALSE)
write.table()	Write table	write.table(df, "file.txt")
saveRDS()	Save R object	saveRDS(obj, "file.rds")
readRDS()	Read R object	readRDS("file.rds")
save()	Save multiple objects	save(x, y, file = "data.RData")
load()	Load RData file	load("data.RData")

Tidyverse I/O (readr)

Function	Description	Example
read_csv()	Read CSV (fast)	read_csv("file.csv")
read_tsv()	Read TSV	read_tsv("file.tsv")
read_delim()	Read with delimiter	read_delim("file.txt", delim = "|")
read_fwf()	Read fixed-width	read_fwf("file.txt", col_positions)
write_csv()	Write CSV	write_csv(df, "file.csv")
write_tsv()	Write TSV	write_tsv(df, "file.tsv")

46.5 Tidyverse: dplyr

Core Verbs

Function	Description	Example
filter()	Filter rows	filter(df, age > 25)
select()	Select columns	select(df, name, age)
mutate()	Create/modify columns	mutate(df, age_sq = age^2)
arrange()	Sort rows	arrange(df, age)
summarise()	Summarize data	summarise(df, mean_age = mean(age))
group_by()	Group data	group_by(df, category)

Selection Helpers

Function	Description	Example
starts_with()	Columns starting with	select(df, starts_with("temp"))
ends_with()	Columns ending with	select(df, ends_with("_id"))
contains()	Columns containing	select(df, contains("score"))
matches()	Columns matching regex	select(df, matches("^x[0-9]"))
everything()	All columns	select(df, name, everything())
where()	Columns where condition	select(df, where(is.numeric))
all_of()	All specified columns	select(df, all_of(col_names))
any_of()	Any of specified columns	select(df, any_of(col_names))

Additional dplyr Functions

Function	Description	Example
distinct()	Unique rows	distinct(df, category)
count()	Count occurrences	count(df, category)
slice()	Select rows by position	slice(df, 1:10)
slice_head()	First n rows	slice_head(df, n = 5)
slice_tail()	Last n rows	slice_tail(df, n = 5)
slice_sample()	Random rows	slice_sample(df, n = 10)
slice_max()	Rows with max values	slice_max(df, age, n = 3)
slice_min()	Rows with min values	slice_min(df, age, n = 3)
pull()	Extract column as vector	pull(df, name)
rename()	Rename columns	rename(df, new_name = old_name)
relocate()	Reorder columns	relocate(df, name, .before = age)
across()	Apply to multiple columns	mutate(df, across(where(is.numeric), scale))
rowwise()	Row-wise operations	rowwise(df)
ungroup()	Remove grouping	ungroup(df)
n()	Count in group	summarise(df, count = n())
n_distinct()	Count unique values	summarise(df, unique = n_distinct(x))
first()	First value	summarise(df, first = first(x))
last()	Last value	summarise(df, last = last(x))
nth()	Nth value	summarise(df, third = nth(x, 3))

Joins

Function	Description	Example
left_join()	Keep all left rows	left_join(df1, df2, by = "id")
right_join()	Keep all right rows	right_join(df1, df2, by = "id")
inner_join()	Keep matching rows	inner_join(df1, df2, by = "id")
full_join()	Keep all rows	full_join(df1, df2, by = "id")
semi_join()	Filter left by right	semi_join(df1, df2, by = "id")
anti_join()	Filter left, no match in right	anti_join(df1, df2, by = "id")
bind_rows()	Stack data frames	bind_rows(df1, df2)
bind_cols()	Combine columns	bind_cols(df1, df2)

46.6 Tidyverse: tidyr

Function	Description	Example
pivot_longer()	Wide to long	pivot_longer(df, cols = -id, names_to = "var", values_to = "val")
pivot_wider()	Long to wide	pivot_wider(df, names_from = var, values_from = val)
separate()	Split column	separate(df, col, into = c("a", "b"), sep = "_")
separate_wider_delim()	Split by delimiter	separate_wider_delim(df, col, delim = "_", names = c("a", "b"))
unite()	Combine columns	unite(df, new_col, a, b, sep = "_")
drop_na()	Remove NA rows	drop_na(df)
fill()	Fill NA with previous	fill(df, column, .direction = "down")
replace_na()	Replace NA values	replace_na(df, list(x = 0))
complete()	Complete missing combinations	complete(df, x, y)
expand()	Create all combinations	expand(df, x, y)
nest()	Nest data	nest(df, data = -group)
unnest()	Unnest data	unnest(df, data)

46.7 Tidyverse: ggplot2

Basic Structure

ggplot(data, aes(x = x_var, y = y_var)) +
  geom_*() +
  labs() +
  theme_*()

Geometries

Function	Plot Type	Usage
geom_point()	Scatter plot	Continuous x and y
geom_line()	Line plot	Continuous x and y
geom_smooth()	Smoothed line	Add trend line
geom_bar()	Bar chart	Counts
geom_col()	Bar chart	Values
geom_histogram()	Histogram	Distribution
geom_density()	Density plot	Smooth distribution
geom_boxplot()	Box plot	Distribution by group
geom_violin()	Violin plot	Distribution shape
geom_jitter()	Jittered points	Avoid overplotting
geom_area()	Area plot	Filled area
geom_tile()	Heatmap tiles	Grid data
geom_text()	Text labels	Add text
geom_label()	Text with background	Labeled points
geom_errorbar()	Error bars	Uncertainty
geom_hline()	Horizontal line	Reference line
geom_vline()	Vertical line	Reference line
geom_abline()	Diagonal line	y = a + bx

Aesthetics

Aesthetic	Description	Example
x	X-axis variable	aes(x = var)
y	Y-axis variable	aes(y = var)
color	Point/line color	aes(color = group)
fill	Fill color	aes(fill = group)
size	Point/line size	aes(size = value)
shape	Point shape	aes(shape = group)
linetype	Line type	aes(linetype = group)
alpha	Transparency	aes(alpha = value)
group	Grouping	aes(group = id)

Scales and Labels

Function	Description	Example
labs()	Add labels	labs(title = "Title", x = "X", y = "Y")
scale_x_continuous()	Continuous x scale	scale_x_continuous(limits = c(0, 100))
scale_y_continuous()	Continuous y scale	scale_y_continuous(breaks = seq(0, 10, 2))
scale_x_log10()	Log10 x scale	scale_x_log10()
scale_color_manual()	Manual colors	scale_color_manual(values = c("red", "blue"))
scale_fill_brewer()	ColorBrewer palette	scale_fill_brewer(palette = "Set1")
scale_fill_viridis_d()	Viridis discrete	scale_fill_viridis_d()
coord_flip()	Flip coordinates	coord_flip()
coord_polar()	Polar coordinates	coord_polar()

Faceting

Function	Description	Example
facet_wrap()	Wrap into panels	facet_wrap(~variable)
facet_grid()	Grid of panels	facet_grid(rows ~ cols)

46.8 Statistical Functions

Function	Description	Example
t.test()	T-test	t.test(x, y)
cor()	Correlation	cor(x, y)
cor.test()	Correlation test	cor.test(x, y)
lm()	Linear model	lm(y ~ x, data = df)
glm()	Generalized linear model	glm(y ~ x, family = binomial)
aov()	ANOVA	aov(y ~ group, data = df)
chisq.test()	Chi-squared test	chisq.test(table)
wilcox.test()	Wilcoxon test	wilcox.test(x, y)
ks.test()	Kolmogorov-Smirnov test	ks.test(x, y)
summary()	Model summary	summary(model)
coef()	Model coefficients	coef(model)
residuals()	Model residuals	residuals(model)
predict()	Predictions	predict(model, newdata)

46.9 String Functions (stringr)

Function	Description	Example
str_length()	String length	str_length("hello")
str_sub()	Substring	str_sub("hello", 1, 3)
str_c()	Concatenate	str_c("a", "b", sep = "-")
str_detect()	Detect pattern	str_detect(x, "pattern")
str_replace()	Replace first match	str_replace(x, "old", "new")
str_replace_all()	Replace all matches	str_replace_all(x, "old", "new")
str_split()	Split string	str_split(x, ",")
str_trim()	Remove whitespace	str_trim(x)
str_to_lower()	Lowercase	str_to_lower(x)
str_to_upper()	Uppercase	str_to_upper(x)
str_to_title()	Title case	str_to_title(x)
str_extract()	Extract match	str_extract(x, "[0-9]+")
str_count()	Count matches	str_count(x, "a")

46.10 Control Flow

Conditionals

# if-else
if (condition) {
  # code if TRUE
} else if (other_condition) {
  # code if other TRUE
} else {
  # code if all FALSE
}

# Vectorized if-else
ifelse(condition, value_if_true, value_if_false)

# dplyr case_when
case_when(
  condition1 ~ value1,
  condition2 ~ value2,
  TRUE ~ default_value
)

Loops

# for loop
for (i in 1:10) {
  print(i)
}

# while loop
while (condition) {
  # code
}

# Apply functions (preferred)
lapply(list, function)   # Returns list
sapply(list, function)   # Returns vector
map(list, function)      # purrr, returns list
map_dbl(list, function)  # purrr, returns double vector

46.11 Package Management

Function	Description	Example
install.packages()	Install from CRAN	install.packages("dplyr")
library()	Load package	library(dplyr)
require()	Load (returns TRUE/FALSE)	require(dplyr)
installed.packages()	List installed	installed.packages()
update.packages()	Update all	update.packages()
remove.packages()	Remove package	remove.packages("dplyr")
packageVersion()	Package version	packageVersion("dplyr")