Levels | Factors
R Introduction: Part I

## Levels

Let's revisit the `Levels` label: you often see it when working with factor outputs. What if you want to view all possible values a factor can take?

To display all levels of a factor, which are the distinct categorical values it holds, use the `levels()` function with the factor variable as the argument. Let's take a look at an example:

Interestingly, you can rearrange these levels without altering the actual data. Nonetheless, we sometimes encounter ordered factor variables. Take height, for instance: one might be classified as tall, medium, or short. This ordering implies tall > medium > short.

R accommodates this by allowing you to specify the `ordered` parameter as `TRUE`. This organizes the variables alphabetically for textual values or numerically for values that are numbers.

While numerical ordering is typically straightforward and desired, alphabetical ordering might not be appropriate. To establish a specific order, you also need to set the `labels` parameter to a vector that lists your values in ascending order.

Let's look at an example for clarity:

Observing the difference is instructive. Try it out for yourself!

Let's say you have a vector of grades ranging from 'A' to 'F'. You're tasked with converting this into an ordered factor with the sequence 'F < D < C < B < A':

1. Convert the `grades` vector to a factor, capturing the required order, and store it in the `grades_f` variable.
2. Display the entire `grades_f` variable.

Everything was clear?

Section 3. Chapter 3

Course Content

R Introduction: Part I

# R Introduction: Part I

## Levels

Let's revisit the `Levels` label: you often see it when working with factor outputs. What if you want to view all possible values a factor can take?

To display all levels of a factor, which are the distinct categorical values it holds, use the `levels()` function with the factor variable as the argument. Let's take a look at an example:

Interestingly, you can rearrange these levels without altering the actual data. Nonetheless, we sometimes encounter ordered factor variables. Take height, for instance: one might be classified as tall, medium, or short. This ordering implies tall > medium > short.

R accommodates this by allowing you to specify the `ordered` parameter as `TRUE`. This organizes the variables alphabetically for textual values or numerically for values that are numbers.

While numerical ordering is typically straightforward and desired, alphabetical ordering might not be appropriate. To establish a specific order, you also need to set the `labels` parameter to a vector that lists your values in ascending order.

Let's look at an example for clarity:

Observing the difference is instructive. Try it out for yourself!

Let's say you have a vector of grades ranging from 'A' to 'F'. You're tasked with converting this into an ordered factor with the sequence 'F < D < C < B < A':

1. Convert the `grades` vector to a factor, capturing the required order, and store it in the `grades_f` variable.
2. Display the entire `grades_f` variable.

Everything was clear?

Section 3. Chapter 3