Summary  
This chapter explains how to build a tabular data structure by passing vectors or lists to a function that assembles them into a data frame with column names derived from the variable names.  

General domain of usage  
Data analysis

Good! Now you can see that data frames can be used to connect different data types. In the previous chapter, you considered one of the build-in datasets. How can we create a data frame with our data?

It can be done by using `data.frame()` function. This function receives vectors or lists (which we will consider in the next section) as columns. The names for columns are variable's names. For example, let's create a data frame with abstract information on three people.

# 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)
test # Outputting the data frame

See, the names for columns come from variables names.

In the second part of R Introduction, you will learn about multi-dimensional built-in structures, such as matrices, data frames, and lists.

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.

data.frame() Function

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