select()
This lesson is called select(), part of the R in 3 Months (Fall 2026) course. This lesson is called select(), part of the R in 3 Months (Fall 2026) course.
Transcript
Click on the transcript to go to that point in the video. Please note that transcripts are auto generated and may contain minor inaccuracies.
Loading transcript...
View code shown in video
# Load Packages -----------------------------------------------------------
library(tidyverse)
# Import Data -------------------------------------------------------------
penguins <-
read_csv("penguins.csv")
# select() ----------------------------------------------------------------
penguins
# With select() we can select variables from the larger data frame.
penguins |>
select(bill_length_mm)
# We can also use select() for multiple variables:
penguins |>
select(bill_length_mm, bill_depth_mm)
# select() has several helper functions for selecting variables.
# The contains() function finds any variable with certain text
# in the variable name:
penguins |>
select(contains("bill"))
# The starts_with() function allows us to select variables
# that start with certain text:
penguins |>
select(starts_with("bill"))
# The ends_with() function allows us to select variables that end with certain text:
penguins |>
select(ends_with("mm"))
# We can select a range of columns using the var1:var2 pattern
penguins |>
select(species:bill_length_mm)
# We can drop variables using the -var format:
penguins |>
select(-bill_length_mm)
# We can drop a set of variables using the -(var1:var2) format:
penguins |>
select(-(bill_length_mm:flipper_length_mm))
Your Turn
Copy the code below into your R script file and complete the exercises.
# Load Packages -----------------------------------------------------------
# Load the tidyverse package
library(tidyverse)
# Import Data -------------------------------------------------------------
# Download data from https://rfor.us/penguins
# Copy the data into your Positron project where you downloaded the penguins data
# Overwrite your R code that you created previously with the code below
penguins <- read_csv("penguins.csv")
# select() ----------------------------------------------------------------
# Use select() to keep only the sex variable
# YOUR CODE HERE
# Use select() to keep the island and sex variables
# YOUR CODE HERE
# Use one of the select() helper functions to keep all variables that have the letter s in their names
# YOUR CODE HERE
# Use one of the select() helper functions to keep all variables that start with the letter b
# YOUR CODE HERE
# Use select() to keep the variables from island to the end
# YOUR CODE HERE
# Use the dropping syntax with - to keep the same variables as above (island to the end)
# YOUR CODE HERE
# Drop all variables from bill_length_mm to body_mass_g
# YOUR CODE HERE
Learn More
To learn more about the select() function, check out Chapter 3 of R for Data Science.
Have any questions? Put them below and we will help you out!
Course Content
143 Lessons
1
Welcome to Fundamentals of R
01:20
2
Update Everything
02:26
3
Start a New Project
02:38
4
The Tidyverse
03:24
5
Pipes
03:52
6
select()
04:43
7
mutate()
03:22
8
filter()
10:18
9
Quiz
10
summarize()
05:38
11
Grouped Summaries
04:24
12
arrange()
02:50
13
Create a New Data Frame
03:30
14
Quiz
15
Bring it All Together (Data Wrangling)
07:09
16
Week 2 Project Assignment
13:10
17
Week 2 Coworking Session (Fall 2026)
18
Week 2 Live Session (Fall 2026)
59:16
1
The Grammar of Graphics
04:36
2
Scatterplots
03:40
3
Histograms
04:51
4
Bar Charts
04:53
5
Quiz
6
Setting color and fill Aesthetic Properties
02:43
7
Setting color and fill Scales
05:12
8
Quiz
9
Setting x and y Scales
02:58
10
Adding Text to Plots
05:50
11
Plot Labels
02:59
12
Themes
02:10
13
Facets
02:56
14
Save Plots
02:49
15
Bring it All Together (Data Visualization)
06:14
16
Week 3 Project Assignment
06:02
17
Week 3 Coworking Session (Fall 2026)
18
Week 3 Live Session (Fall 2026)
1:00:46
1
Best Practices in Data Visualization
03:38
2
Tidy Data
02:25
3
Pipe Data in ggplot
08:18
4
Reorder Plots to Highlight Findings
03:50
5
Line Charts
04:13
6
Use Color to Highlight Findings
08:23
7
Declutter
07:53
8
Add Descriptive Labels to Your Plots
09:18
9
Use Titles to Highlight Findings
08:30
10
Use Annotations to Explain
06:35
11
Quiz
12
Week 9 Coworking Session (Fall 2026)
13
Week 9 Live Session (Fall 2026)
59:10
1
Advanced Markdown
07:10
2
Tables
15:48
3
Advanced YAML and Code Chunk Options
05:42
4
Inline R Code
03:42
5
Making Your Reports Shine: Word Edition
05:08
6
Making Your Reports Shine: PDF Edition
07:37
7
Making Your Reports Shine: HTML Edition
06:08
8
Presentations
11:12
9
Dashboards
06:20
10
Websites
08:11
11
Publishing Your Work
02:37
12
Quarto Extensions
06:38
13
Parameterized Reporting, Part 1
07:02
14
Parameterized Reporting, Part 2
04:03
15
Parameterized Reporting, Part 3
06:22
16
Quiz
17
Week 12 Coworking Session (Fall 2026)
18
Week 12 Live Session (Fall 2026)
57:26
1
Working with dates
18:22
2
Working with labelled data
05:35
3
Understanding Documentation Pages
05:20
4
Factors in R
11:18
5
Add citations to Quarto documents
10:42
6
Change titles of facet plots
08:16
7
Population pyramid plot
04:24
8
Crosstabs
06:58
9
Difference between == and %in%
03:17
10
Quarto - rendering and working directories
13:05
11
Regular expressions
You need to be signed-in to comment on this post. Login.
Lilly Yu • September 29, 2026
For the last function where we drop a range of variables, the console still shows me the variables that I dropped: species island bill_length_mm bill_depth_mm flipper_length_mm body_mass_g. Is this correct?
Gracielle Higino Coach • September 30, 2026
Hi Lilly! It depends a bit on what you asked R to show you. The last exercise should still show species, but not
bill_length_mm, for example. Can you share your exact code, please?Lilly Yu • September 30, 2026
I think I figured it out--I had omitted the second parenthesis after the minus sign. Thank you!
Mallik Janthak • October 5, 2026
How do you identify the first column of the data frame without naming it? I was able to use this for the last column in the following exercise.
Use select() to keep the variables from island to the end
penguins |> select(island:last_col())
Gracielle Higino Coach • October 5, 2026
Hi Mallik! I think there's no equivalent to
last_col()for the first column because you can use the index of the column for this (select(1)). The first column will always have an index of 1, whereas the last column’s index depends on the number of variables in your dataset, hence the need for a “shortcut.”