■ The preliminary objective of R is to simply vector
computation
■ Mathematical Operators and most R build-in functions
take vectors as input
🌻 Bi-Operant Math Operations act Element-wise
c(1, 2, 3, 4) * c(1, 10, 100, 1000)[1] 1 20 300 4000
🌻 When the lengths of the vectors are different …
c(100, 200, 300, 400) / 10[1] 10 20 30 40
The shorter vector are repeated silently
c(100, 200, 300, 400) / c(10, 20)[1] 10 10 30 20
There is a warning when …
c(10,20,30,40,50,60,70,80) + c(1,2,3)Warning in c(10, 20, 30, 40, 50, 60, 70, 80) + c(1, 2, 3): longer object length is not a
multiple of shorter object length
[1] 11 22 33 41 52 63 71 82
Logical Operations do comparisons and produce
logical vectors
They compare numerics, strings, factors, Date, …
c(0.1, 0.2, 0.3, 0.4) > c(0, 1, 2, 3)[1] TRUE FALSE FALSE FALSE
shorten vectors are also repeated
c(100, 200, 300, 400) > 250[1] FALSE FALSE TRUE TRUE
❓ what happen if I do …
c(200, 300) > c(100, 200, 300, 400)🌻 Test for equivalence (==) on character and factor
vectors
c('Amy','Bob','Cindy','Danny') == 'Cindy'[1] FALSE FALSE TRUE FALSE
🌻 The Set Comparison Operator : %in%
c('Amy','Bob','Cindy','Danny') %in% c('Danny','Cindy')[1] FALSE FALSE TRUE TRUE
The above is the same as …
c('Amy','Bob','Cindy','Danny') %in% c('Cindy','Danny')[1] FALSE FALSE TRUE TRUE
%in% is not importantbut different from …
c('Amy','Bob','Cindy','Danny') == c('Danny','Cindy')[1] FALSE FALSE FALSE FALSE
== works element wise. thus, the sequence in the rhs
vector of is important❓ What happen if I do …
c('Amy','Bob','Cindy','Danny') == c('Cindy','Danny')🌻 2 Notations of Assignment : = 和
<-
Prob = c(0.1, 0.2, 0.3, 0.4)
Value <- c(120, 100, -50, -60)
Prob * Value[1] 12 20 -15 -24
🌻 Assignment (=) is different from Test for Eq.
(==)
c(0.1, 0.2, 0.3, 0.4) == (1:4)/10[1] TRUE TRUE TRUE TRUE
❓ What happen if you do
c(0.1, 0.2, 0.3, 0.4) = (1:4)/10Most R function take vectors as input (usually the first
argument.)
Some functions produce vectors.
val=c(500,20,75,400)
sum(val)[1] 995
Some functions produce summary statistics
mean(val)[1] 248.8
In addition to the input, most R function take many other arguments
log(val, base=10)[1] 2.699 1.301 1.875 2.602
💡 Arguments of Functions:
■
To be convenient and flexible, most R functions have many arguments with
■ Place cursor on the function name and press F1
to see the online help
■ Arguments can be given either
■ Unnamed-arguments must be in
their exact position
■ Named arguments can be placed in any
order
help(log)Default argument
log(1000)[1] 6.908
Argument by position
log(1000, 10)[1] 3
Argument by names
log(x=1000, base=10)[1] 3
Argument by names in reverse order
log(base=10, x=1000)[1] 3
Quite often we need to cascade several functions, for example
x = 10000
mean(log(sqrt(x), base=10))[1] 2
The %>% would make it easier to
apply a series of functions
sqrt(x) %>% log(10) %>% mean[1] 2