R Lists, Matrices and Factors
Lists, matrices and factors let you store data that does not fit in a simple vector.
Which One to Use?
| Structure | Holds | Example |
|---|---|---|
| Vector | Values of one type, in a line | Five students' marks |
| List | Values of any types, even other vectors | One student's name, age and marks |
| Matrix | Values of one type, in rows and columns | Monthly sales of two shops |
| Factor | Categories with a fixed set of levels | Shirt sizes S, M, L |
Lists
A list can hold different types together. Give each part a name:
Example
student <- list(name = "Ali", age = 19, marks = c(80, 72, 91))
student$name [1] "Ali" $age [1] 19 $marks [1] 80 72 91
Getting Items from a List
Use $ with the name, or double brackets [[ ]]:
Example
student$name
student[["marks"]]
mean(student$marks)[1] "Ali" [1] 80 72 91 [1] 81
Single brackets student["marks"] return a smaller list, not the values themselves. Use $ or [[ ]] when you want the actual values to calculate with.
Adding and Removing Items
Assign a new name to add an item. Assign NULL to remove one:
Example
student$city <- "Karachi"
student$age <- NULL
names(student)
length(student)[1] "name" "marks" "city" [1] 3
Many R functions return their results as lists, so you will meet lists often, even if you rarely create them yourself.
Matrices
A matrix is a table of values of one type, with rows and columns. Create it with matrix():
Example
m <- matrix(1:6, nrow = 2)
m
dim(m)[,1] [,2] [,3] [1,] 1 3 5 [2,] 2 4 6 [1] 2 3
By default, R fills the matrix column by column. Add byrow = TRUE to fill it row by row. dim() gives the number of rows and columns.
A Matrix with Names
Here are the sales (in thousands of rupees) of two shops over three months:
Example
sales <- matrix(c(120, 95, 140, 110, 80, 130), nrow = 2, byrow = TRUE,
dimnames = list(c("Shop A", "Shop B"), c("Jan", "Feb", "Mar")))
sales
sales["Shop B", "Feb"]
sales[1, ]Jan Feb Mar Shop A 120 95 140 Shop B 110 80 130 [1] 80 Jan Feb Mar 120 95 140
Inside the brackets, the first number is the row and the second is the column: [row, column]. Leave one empty to get the whole row or column.
Row and Column Totals
Example
rowSums(sales)
colMeans(sales)Shop A Shop B 355 320 Jan Feb Mar 115.0 87.5 135.0
| Function | Gives |
|---|---|
rowSums(), colSums() | Totals of each row or column |
rowMeans(), colMeans() | Averages of each row or column |
t() | Swaps rows and columns |
nrow(), ncol() | Number of rows or columns |
Factors
A factor stores categories. R keeps a list of the possible values, called levels:
Example
sizes <- c("M", "L", "S", "M", "M", "L")
size_factor <- factor(sizes)
size_factor
levels(size_factor)
table(size_factor)[1] M L S M M L Levels: L M S [1] "L" "M" "S" size_factor L M S 2 3 1
table() counts how many times each level appears. A Karachi clothes shop could use this to see which size sells most.
Choosing the Order of Levels
R sorts levels alphabetically, so L came before S. Give the order yourself with levels =:
Example
size_factor <- factor(sizes, levels = c("S", "M", "L"))
table(size_factor)
nlevels(size_factor)size_factor S M L 1 3 2 [1] 3
Factors are important for statistics and charts. They tell R that a column holds groups, not free text.
Exercise
Exercise
You need to store one student's name (text), age (number) and five marks together. Which structure fits best?