RP: Week 1

####Basic atomic classes of objects

• character
• numeric
• integer
• complex
• logical

####Vector vs List

Vector: objects of the same class

vector(<class>, <length>)

List: can contain objects of different classes

####Numbers

• default double precision real number
• 1L-> explicitly integer 1

• Inf

  1 / 0 = Inf 1 / Inf = 0

• NaN: not a number

  0 / 0 = NaN

####Attributes

• names, dimnames
• dimensions
• class
• length
• other user-defined attributes/metadata
• attributes()

####Assignment

<-

####Integer sequence

1:20

####Creating vectors

• c(0.5, 0.6)
• vector(“numeric”, length = 10)

####Explicit coercion

• as.class function
• Nonsensical coercion results in NAs

####Matrices

• dim()

  return nrow, ncol

• it’s constructed column-wise

• creating from vector

    m <- 1:10
    dim(m) <- c(2,5)
  

• creating by column-binding or row-binding

    cbind()
    rbind()
  

####Factors

• labels
• levels

####Missing values

• NA
• NaN
• is.na()
• is.nan()
• NA values have a class too.
• NaN is NA
• NA is not NaN

####Data frames

• row.names
• read.table() or read.csv()
• data.matrix()

####Names

R objects can have names

names()

List elements can also have names

dimnames()

###Subsetting

• []
• [[]]
• $

####Subsetting a Matrix

drop = FALSE will result in a matrix otherwise will result in a vector(in most case)

####Partial matching

x<-list(aardvark=1:5)
x$a #aardvark
x[["a", exact = FALSE]]

####Reading and writing data

• dput: single object
• dump: multiple objects