R Programming for Data Science

Data Frames and Names

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Reference

R Programming for Data Science by Roger D. Peng, May 31, 2022

Class Picture on September 8, 2022

1 Data Frames

Data frames are used to store tabular data in R. They are an important type of object in R and are used in a variety of statistical modeling applications. Hadley Wickham’s package dplyr has an optimized set of functions designed to work efficiently with data frames.

Data frames are represented as a special type of list where every element of the list has to have the same length. Each element of the list can be thought of as a column and the length of each element of the list is the number of rows.

Unlike matrices, data frames can store different classes of objects in each column. Matrices must have every element be the same class (e.g. all integers or all numeric).

In addition to column names, indicating the names of the variables or predictors, data frames have a special attribute called row.names which indicate information about each row of the data frame.

Data frames are usually created by reading in a dataset using the read.table() or read.csv(). However, data frames can also be created explicitly with the data.frame() function or they can be coerced from other types of objects like lists.

Data frames can be converted to a matrix by calling data.matrix(). While it might seem that the as.matrix() function should be used to coerce a data frame to a matrix, almost always, what you want is the result of data.matrix().

x <- data.frame(foo = 1:4, bar = c(T, T, F, F)) 
x

nrow(x)

[1] 4

ncol(x)

[1] 2

dim(x)

[1] 4 2

attributes(x)

$names
[1] "foo" "bar"

$class
[1] "data.frame"

$row.names
[1] 1 2 3 4

str(x) # structure of x

'data.frame':   4 obs. of  2 variables:
 $ foo: int  1 2 3 4
 $ bar: logi  TRUE TRUE FALSE FALSE

2 Names

R objects can have names, which is very useful for writing readable code and self-describing objects. Here is an example of assigning names to an integer vector.

x <- 1:3
names(x)

NULL

names(x) <- c("New York", "Seattle", "Los Angeles") 
x

   New York     Seattle Los Angeles 
          1           2           3 

names(x)

[1] "New York"    "Seattle"     "Los Angeles"

Lists can also have names, which is often very useful.

x <- list("Los Angeles" = 1, Boston = 2, London = 3) 
x

$`Los Angeles`
[1] 1

$Boston
[1] 2

$London
[1] 3

names(x)

[1] "Los Angeles" "Boston"      "London"     

x[[1]]

[1] 1

x$`Los Angeles`

[1] 1

Matrices can have both column and row names.

m <- matrix(1:4, nrow = 2)
m

     [,1] [,2]
[1,]    1    3
[2,]    2    4

names(m)

NULL

dimnames(m) <- list(c("a", "b"), c("c", "d")) 
m

  c d
a 1 3
b 2 4

colnames(m)

[1] "c" "d"

rownames(m)

[1] "a" "b"

Column names and row names can be set separately using the colnames() and rownames() functions.

colnames(m) <- c("h", "f")
rownames(m) <- c("x", "z")
m

  h f
x 1 3
z 2 4

Note that for data frames, there is a separate function for setting the row names, the row.names() function. Also, data frames do not have column names, they just have names (like lists). So to set the column names of a data frame just use the names() function. Yes, I know its confusing. Here’s a quick summary:

Object	Set column names	Set row names
data frame	names()	row.names()
matrix	colnames()	rownames()