Data frames in R represent tabular data, where each column can contain one type of variable (e.g., numeric, character, factor). Each column has a text-based name; rows can also have a name, although by default they are numbered.
We can either construct a data frame by using the data.frame() function, or we can also obtain a data frame as the result of a function that, for example, reads in a data file, such as read.csv().
Let’s use data.frame() to create a simple data frame:
df <- data.frame(
id = c('P01', 'P03', 'P04', 'P07'),
name = c("Alice", "Bob", "Charlie", "David"),
age = c(25, 30, 35, 40),
score = c(90.5, 85.0, 88.5, 92.0)
)
# show the data frame
df id name age score
1 P01 Alice 25 90.5
2 P03 Bob 30 85.0
3 P04 Charlie 35 88.5
4 P07 David 40 92.0We can get information about the data frame’s structure using the str() function:
str(df)'data.frame': 4 obs. of 4 variables:
$ id : chr "P01" "P03" "P04" "P07"
$ name : chr "Alice" "Bob" "Charlie" "David"
$ age : num 25 30 35 40
$ score: num 90.5 85 88.5 92And we can get the names of the columns using the names() (or colnames()) function:
names(df)[1] "id" "name" "age" "score"We can also get the row names using the rownames() function:
rownames(df)[1] "1" "2" "3" "4"We can change the column or row names by assigning new values to them:
colnames(df) <- c("ID", "Name", "Age", "Score")
df ID Name Age Score
1 P01 Alice 25 90.5
2 P03 Bob 30 85.0
3 P04 Charlie 35 88.5
4 P07 David 40 92.0…although generally it’s more convenient to use the dplyr::rename() function instead, as it allows you to rename specific columns without affecting the others.
We can access elements of a data frame using the $ operator, which allows us to select a specific column by name. For example, to access the Age column:
df$Age[1] 25 30 35 40Note that each column of a data frame is an R vector, so when you access a column, you get back a vector.
We can also combine data frames using the rbind() and cbind() functions. The rbind() (“row bind”) function combines data frames by rows (i.e., it adds more rows), while the cbind() (“column bind”) function combines data frames by columns (i.e., it adds more columns).
Note that when using rbind(), the data frames must have the same columns (i.e., the same exact names and types), and when using cbind(), the data frames must have the same number of rows.
df1 <- data.frame(
id = c('P01', 'P03'),
name = c("Alice", "Bob"),
age = c(25, 30),
score = c(90.5, 85.0)
)
df2 <- data.frame(
id = c('P04', 'P07'),
name = c("Charlie", "David"),
age = c(35, 40),
score = c(88.5, 92.0)
)
df <- rbind(df1, df2)
df id name age score
1 P01 Alice 25 90.5
2 P03 Bob 30 85.0
3 P04 Charlie 35 88.5
4 P07 David 40 92.0