In an R command window type ?afunc
to get help on a function named afunc
vignette("apackage")
to display documentation for a package
str(obj)
- Display the internals of an object
c()
functiontypeof(myVector)
function to in the vectorv1 <- c(1, 2, 3, 4)
v2 <- c('Apple', 'Banana', 'Cherry', 'Date')
typeof(v2) # character
v2[1] # 1
v2[1:2] # 1 2
v2[-1:-3] # 4
v2[c(TRUE, FALSE, FALSE, FALSE)] # 'Apple'
Function | Description |
---|---|
typeof(vec) |
get the type of the elements |
seq(1, 10) |
generate a vector which is a sequence of ints |
factor()
functionlevel
vector to define orderf1 <- factor(c('DOG', 'CAT', 'MOUSE'))
f2 <- factor(c('SLOW', 'MEDIUM', 'FAST'), levels=c('SLOW', 'MEDIUM', 'FAST'))
list()
functionl1 <- list(name='Will', age=39)
l1$name # 'Will'
l1[[2]] # 39
l1[2] # $age 39
data.frame()
. Optional arg of stringsAsFactors=FALSE
(default true)d1 <- data.frame(letters=c('a', 'b', 'c'), nums=c(1, 2, 3), syms=c('@', '?', '%'))
d1$letters # extract whole letters vector
d1[c("letters", "syms")] # dataframe with letters and syms
d1["letters"] # dataframe with letters
d1[2,1] # 'b' - [row, column]
d1[, 3] # @ ? %
d1[-3] # dataframe excluding syms
matrix()
function taking ncol
or nrow
and optional byrow
argm1 <- matrix(c(1, 2, 3, 4, 5, 6), nrow=2) # 1 3 5
# 2 4 6
m2 <- matrix(c(1, 2, 3, 4, 5, 6), ncol=2, byrow=TRUE) # 1 2 3
# 4 5 6
m3 <- matrix(c(1, 2, 3, 4, 5, 6), ncol=2) # 1 4
# 2 5
# 3 6
m1[1, 2] # 3
m1[1, ] # 1 3 5
m1[, 1] # 1 2
complete.cases - returns a vector of booleans - FALSE if row value is NA
sum(complete.cases(nc$gained))
Function | Description |
---|---|
save.image() |
Save session so it will be reloaded on restarting R |
save(var1, var2, file='/tmp/some_file.rData') |
Save variables var1 , var2 to file |
load('some_file.rData') |
load whatever variables were stored in some_file.rData in the R working directory |
rm(var1, var2) |
delete variables |
ls() |
list all variables |
rm(list=ls()) |
delete all variables |
df <- read.csv('file.csv') |
load a dataframe from CSV file |
write.csv(df, file='file.csv') |
Write dataframe to CSV |
Function | Description |
---|---|
summary(vec) |
Display 5 figure summary and mean (min, q1, median, mean, q3, max) |
summary(c(vec1, vec3) |
side-by-side 6 figure summary for more multiple vars |
mean(vec) |
|
min(vec) |
|
max(vec) |
|
IQR(vec) |
Q3 - Q1 |
range(vec) |
c(min, max) |
diff(dev) |
generate differences of each consecutive pair in a vector |
quantile(vec, prob=seq(0, 1, 0.1)) |
Function | Description |
---|---|
table | |
str |
scale - convert a vector to z-scores sample - take samples of a vector or numbers set.seed(123) - set seed used for PSNG as used in sample
rm - delete a variable
pnorm - gives percentile from critical value
p <- pnorm(1.644854) # p = 0.95
qnorm - gives the critical value from percentile
z <- qnorm(0.95) # z = 1.644854
pt - gives percentile from critical value and degrees of freedom
p <- pt(1.644854, df = 50) # p = 0.9468633
qt - gives percentile from critical value and degrees of freedom
z <- qt(0.9468633, df = 50) # z = 1.644854
pf - gives percentile from critical value and degrees of freedom
p <- pf(10, 2, 100) # pf(10, 2, 100)