What are data frames in R?

A data frame is an important data type in R. Data frames are the de facto data structure for tabular data and are used for statistics.

A data frame is a special type of list in which every element has an equal length. In other words, a data frame is a rectangular list.

Data frames have additional attributes, such as rownames(), that are useful for annotating data as subject_id or sample_id.

Characteristics of data frames

• The column names should not be empty.
• The row name should be unique.
• The data stored in a data frame should be numeric, factor(dataType in R), or character type.
• Each column should contain the same number of data items.

Explanation

You can create data frames with the read.csv() or read.table() method.

For example, importing the data into R, let’s assume all the columns in a data frame are of the same type. You can convert the data frame to a matrix with data.matix() or as.matrix().

We can also create a new data frame with the built-in data.frame() function. In addition, we can find the number of rows and columns by using and passing the data frame as an argument, i.e., nrow(frame), ncol(frame).

Built-in methods

Here are some useful built-in methods that help to easily process data frames:

• nrow(): Denotes the number of rows
• ncol(): Denotes the number of columns
• head(): Denotes the first 6 rows
• tail(): Denotes the last 6 rows
• dim(): Gives the dimensions of the data frame, such as the number of rows and columns
• names() or colnames(): Shows the names of the attributes for a data frame
• str(): Defines the structure of the data frame as name, type, etc.
• sapply(dataframe, class): Denotes the class of each column in the data frame

The table below summarizes the one-dimensional and two-dimensional data structures in R by showing the relation of the diversity of data types:

Example

In the example below, we initialize a data frame with 3 columns and 5 rows. The first column represents Index, while the other two are keys and their parallel values.