# The dim Function in R (4 Examples)

**Basic R Syntax:**

dim(data) |

The dim function of the R programming language **returns the dimension** (e.g. the number of columns and rows) of a matrix, array or data frame. Above, you can see the R code for the application of dim in R.

Continue reading! I’ll provide you with several **example codes and practical tips** in the following article.

## Example 1: Dimension of Matrix or Data Frame

Let’s first create some example data, before we start with the application of dim in R:

set.seed(62626) # Set Seed for reproducibility N <- 500 # Sample size x1 <- round(rnorm(N, 0, 10)) # Create 5 random variables x2 <- round(runif(N, 5, 10)) x3 <- round(runif(N, 1, 3), 1) x4 <- round(runif(N, 10, 20)) x5 <- rpois(N, 5) data <- data.frame(x1, x2, x3, x4, x5) # Data frame with 5 columns head(data) # First 6 rows of data.frame |

**Table 1: First 6 Rows of Our Example Data Frame for the Application of dim in R.**

Table 1 illustrates how our example data.frame looks like. It’s easy to see that the data consists of 5 columns. But how many rows? Let’s check with the dim R function:

dim(data) # Apply dim function to data.frame # 500 5 |

After applying the dim function in R (I use the RStudio interface), we get two numbers back. The first number reflects the number of rows; and the second number reflects the number of columns.

In other words: Our data frame consists of 500 rows and 5 columns.

The same procedure could be applied to a matrix. Let’s convert our data to the matrix format and check if it works:

data_matrix <- as.matrix(data) # Convert data.frame to matrix dim(data_matrix) # Apply dim function to matrix # 500 5 |

Same result as before – perfect!

## Example 2 (Video): dim of a Real Data Frame

In the previous example, I have shown you how to apply dim to a synthetic data set. Do you want to see an example that is based on **more realistic data**? Then you could check out the following video of my YouTube channel *Statistical Programming*. In the video, I’m showing another example for the application of dim to a data frame:

## Example 3: dim of List in R

Sometimes, it is useful to use dim for a list object in R. That task is easily done with a combination of dim() and sapply().

First, let’s create a list in R:

data_list <- list() # Create empty list object data_list[[1]] <- data # First entry of list data_list[[2]] <- data[1:10, ] # Second entry (subset of data) data_list[[3]] <- data[5:67, c(1, 3, 5)] # Third entry (other subset of data) |

Now, let’s extract the dimensions of each list element:

sapply(data_list, dim) # Get dimension of all list entries # [,1] [,2] [,3] # [1,] 500 10 63 # [2,] 5 5 3 |

The combination of dim and sapply returns a matrix to the RStudio console. Each column of this matrix reflects the dimension of one list element:

- List entry 1: 500 rows; 5 columns
- List entry 2: 10 rows; 5 columns
- List entry 3: 63 rows; 3 columns

## Example 4: dim in R Returns NULL – What’s the Problem?

A common mistake is the application of dim to a one dimensional vector or array. Let’s see what happens, when we do this.

I’ll first create an example vector…

vec1 <- c(5, 9, - 20, 3, 17, 18, 2) # Example vector |

…and then I’ll apply the dim function:

dim(vec1) # Apply dim function to vector # NULL |

As you see: That doesn’t work!

In case you want to get the number of entries of a vector, you have to use the length function:

length(vec1) # Get length of vector or array # 7 |

## Further Reading