Since data frames have names on their columns, you should be able to extract necessary data using them.

There are several ways in R to refer to a particular column using naming. One of them is the same as in vectors and matrices: column name within square brackets (for example, `data[, "col_name"]). The second way is unique for data frames - using the dollar `$` sign. The syntax is `data$col_name` (yes, without quotation marks). For example, you can extract the column `"Age"` from the data frame created in the last chapter.

# Data
name <- c("Alex", "Julia", "Finn")
age <- c(24, 43, 32)
gender <- c("M", "F", "M")
# Creating a data frame
test <- data.frame(name, age, gender)

# Extracting the name column using two ways
test[,"name"]
test$name

The output will be identical for both last lines.
```
[1] "Alex"  "Julia" "Finn" 
[1] "Alex"  "Julia" "Finn" 
```

In the first section, you will learn the two-dimensional structure that is widely used in math. In R, this data type is used not only for math purposes but also has many real-life purposes.

In the second section, you will learn data frames - an 'upgraded' version of the matrix. Unlike matrix, the data frame may contain data of different types. Most real-life tables can be represented as data frames. You will learn how to create/manipulate data frames and extract necessary data.

In the final section, you will learn the lists in R. This data type works as vectors but may contain data of different types.