R - Matrix, List, Factor, Data Frame

• Matrix
• Matrix is a vector with dimension attribute (dimension itself is a integer vector of length 2 : nrow and ncol).

 > m <- matrix(1:10, nrow = 2, ncol = 5) # create matrix   
 > m # print matrix  
    [,1] [,2] [,3] [,4] [,5]  
 [1,]  1  3  5  7  9  
 [2,]  2  4  6  8  10  
 > dim(m) # get dimension of m  
 [1] 2 5  
 > attributes(m) # get attributes of m  
 $dim  
 [1] 2 5  

• As you can see, Matrix constructed from column-first order (column-wise).
• Matrix can be created from vector by adding a dimension attribute.

 > m <- 1:10  # vector
 > dim(m) <- c(2,5)  # add dimension attribute to vector, m will become Matrix
 > m  
    [,1] [,2] [,3] [,4] [,5]  
 [1,]  1  3  5  7  9  
 [2,]  2  4  6  8  10  

• Matrix can be created from cbind() or rbind() function.

 > a <- 1:2  
 > b <- 3:4  
 > c <- 5:6  
 > d <- 7:8  
 > e <- 9:10  
 > cbind(a,b,c,d,e)  # create Matrix with cbind()
    a b c d e  
 [1,] 1 3 5 7 9  
 [2,] 2 4 6 8 10  
 > f <- 1:10  # what if the length of the column is different?
 > cbind(a,b,c,d,e,f)  # create Matrix with cbind(), f is length 10
    a b c d e f  
  [1,] 1 3 5 7 9 1  
  [2,] 2 4 6 8 10 2  
  [3,] 1 3 5 7 9 3  
  [4,] 2 4 6 8 10 4  
  [5,] 1 3 5 7 9 5  
  [6,] 2 4 6 8 10 6  
  [7,] 1 3 5 7 9 7  
  [8,] 2 4 6 8 10 8  
  [9,] 1 3 5 7 9 9  
 [10,] 2 4 6 8 10 10  

• How to do multiple operation for matrix?

 > x <- matrix(1:4, 2, 2); y <- matrix(rep(10,4),2,2)  
 > y  
    [,1] [,2]  
 [1,]  10  10  
 [2,]  10  10  
 > x  
    [,1] [,2]  
 [1,]  1  3  
 [2,]  2  4  
 > x * y  # it just do multiple in element-wise 
    [,1] [,2]  
 [1,]  10  30  
 [2,]  20  40  
 > x %*% y  # matrix multiplication
    [,1] [,2]  
 [1,]  40  40  
 [2,]  60  60  

• List
• A special type of vector that contain different classes of objects

 > x <- list(TRUE, "list", 1L)  
 > x  
 [[1]]  
 [1] TRUE  
 [[2]]  
 [1] "list"  
 [[3]]  
 [1] 1  

• Factor
• used for categorical data 

 > x <- factor(c("male","male","female","female"))  # create factor
 > x  # print x
 [1] male  male  female female  
 Levels: female male  
 > table(x)  # call table() to show how many items have in each labels
 x  
 female  male   
    2   2   

• Factor labels have order, you could set order while creating with factor()

 > x <- factor(c("male","male","female","female"), levels = c("male","female"))  
 > x  
 [1] male  male  female female  
 Levels: male female  # order has been changed from example above

• Data Frame
• for storing tabular data, can have different classes of objects in each column.

 > x <- data.frame(sex = c("male","female", "male", "male", "female"), age = 26:30)  
 > x  
    sex age  
 1  male 26  
 2 female 27  
 3  male 28  
 4  male 29  
 5 female 30  

• Use nrow() and ncol() function to get the no. of rows and columns

 > nrow(x)  
 [1] 5  
 > ncol(x)  
 [1] 2  

• How to change column names in data frame? -> use colnames()

 > my_data  
  patients X1 X2 X3 X4 X5  
 1   Bill 1 5 9 13 17  
 2   Gina 2 6 10 14 18  
 3  Kelly 3 7 11 15 19  
 4   Sean 4 8 12 16 20  
 > cnames <- c("patient","age","weight","bp","rating","test")  
 > colnames(my_data) <- cnames  
 > my_data  
  patient age weight bp rating test  
 1  Bill  1   5 9   13  17  
 2  Gina  2   6 10   14  18  
 3  Kelly  3   7 11   15  19  
 4  Sean  4   8 12   16  20  

• Check how much memory the dataset is occupying.

 > object.size(x)  
 1312 bytes  

• Suppose data frame is pretty big and have thousands of rows, probably you could check first several rows using head(). (Use tail() for last n rows)

 > head(x)  # head() function returns first 6 rows
    sex age  
 1  male 26  
 2 female 27  
 3  male 28  
 4  male 29  
 5 female 30  
 > head(x,3)  # specify how many rows you want to see
    sex age  
 1  male 26  
 2 female 27  
 3  male 28  

• Sequence
• There are several ways to create sequence

 > 1:20  
  [1] 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20  
 > seq(1,20)  # seq() does exactly the same thing : does
  [1] 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20  
 > seq(1,20,by=0.5)  # set by argument so that increase by 0.5 each time
  [1] 1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0 5.5 6.0 6.5 7.0 7.5 8.0  
 [16] 8.5 9.0 9.5 10.0 10.5 11.0 11.5 12.0 12.5 13.0 13.5 14.0 14.5 15.0 15.5  
 [31] 16.0 16.5 17.0 17.5 18.0 18.5 19.0 19.5 20.0  

 > x <- seq(1,20,length = 5)  # create with length 5, (values between 1~20)
 > length(x)  
 [1] 5  
 > 1:length(x)  # use length to create vector 
 [1] 1 2 3 4 5   
 > seq_along(x)  # the same as 1:length(x)
 [1] 1 2 3 4 5   
 > rep(1, times = 10)  # rep replicate value 1 for 10 times
  [1] 1 1 1 1 1 1 1 1 1 1  
 > rep(c(0,1,2), times = 5)  # replicate 0,1,2 for 5 times
  [1] 0 1 2 0 1 2 0 1 2 0 1 2 0 1 2  
 > rep(c(0,1,2), each = 5)  # replicate 0 for 5 times and 1 for 5 times...
  [1] 0 0 0 0 0 1 1 1 1 1 2 2 2 2 2  

• Change class

 > yesno <- sample(c("yes","no"), size = 10, replace = TRUE)  
 > class(yesno)  
 [1] "character"  
 > yesnoFactor <- as.factor(yesno)  
 > yesnoFactor  
  [1] yes no yes no yes yes yes no no no   
 > yesnoFactor <- factor(yesno, levels = c("yes","no"))  
 > yesnoFactor  
  [1] yes no yes no yes yes yes no no no   
 Levels: yes no  
 > as.numeric(yesnoFactor)  
  [1] 1 2 1 2 1 1 1 2 2 2