Summary  
A data frame is a two-dimensional, matrix-like data structure that allows columns to hold different types of values and requires names for each column, enabling indexed access by rows and columns.  

General domain of usage  
Data analysis

Let's move on to Data Frames. In general, the data frame in R is the same matrix allowing us to store values of different types. This aspect is the crucial difference.

Like in matrices, each element of the data frame has its 'address' among rows and columns. But unlike matrices, data frames must have names on their columns.

R provides us with tens of built-in datasets. Some can be represented as matrices (as they contain only numerical data), and some can be defined as data frames. Explore one of them by yourself!

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.

What is a Data Frame?

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