Selecting columns

Why select columns?

It is a good practice to only use relevant information for analysis. Selecting only specific columns can make your work more efficient, easier to manage, reduce complexity, improve performance, and protect sensitive data. You can always go back and choose other columns if necessary.

What we’ll learn in this section

A step-by-step way to think about data

Before we learn how to select columns in R, we’ll quickly learn about an operator known as the pipe operator. It is represented using two characters on the keyboard placed together like this: |> The pipe operator connects previous steps to the next step.

Whenever you see |> , say “and then”.

This allows us to think about code in a human readable and step-by-step way. We will use this approach to write some code.

You’ll find the | key above the enter key. To use it, press Shift + | .

The > key is before the ? . To use it, press Shift + > .

By combining them, we can type: |>

Selecting columns with column names

In tidyverse , we can select columns from a dataset using the select function.

Syntax

You can read the following syntax like “take the dataset, and then select column1 and column2”.

 dataset |>
  select(column1, column2) 

Now it is your turn to practice. Let’s try the next two exercises. For the first exercise, you simply have to click the run button. For the second exercise, you’ll type in the column names separated by a comma.

 flowers |>
  select(season, sunlight) 

Good work! Next, we’ll learn how to select columns using column positions.

Selecting columns using column positions

We can also select columns using numbers to indicate their positions. For example, to choose the first column, we can use select(1) . To select more columns, we can separate them with commas.

 flowers |>
  select(2, 4) 

Next, we’ll learn how to select a range of columns.

Selecting a range of columns

We can select a range of columns using the colon symbol and also known as the : operator.

 flowers |>
  select(1:3) 

Unselecting columns

If you want to unselect columns, you can use the - operator.

To unselect multiple columns, we wrap them with the c() function.

Selecting Columns based on Data Type

You can select columns based on their data type. For example, to select all columns that are numeric, you can use the where function and wrap it around is.numeric .

Selecting numeric columns

 dataset |>
  select(where(is.numeric)) 

Selecting character columns

 dataset |>
  select(where(is.character)) 

 flowers |>
  select(where(is.character)) 

You have reached the end of this section. Let’s review what we’ve learned!

Review

Great job! We have made our first steps in selecting columns in R. Selecting columns is an essential skill in data analysis.