Objects and Functions
This lesson is called Objects and Functions, part of the R in 3 Months (Spring 2025) course. This lesson is called Objects and Functions, part of the R in 3 Months (Spring 2025) 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.
Your Turn
Adapt your code from the last lesson so that it saves the data as an object called penguins_data
Have any questions? Put them below and we will help you out!
Course Content
127 Lessons
1
Welcome to Getting Started with R
00:57
2
Install R
02:05
3
Install RStudio
02:14
4
Files in R
04:33
5
Projects
07:54
6
Packages
02:38
7
Import Data
05:24
8
Objects and Functions
03:16
9
Examine our Data
12:50
10
Import Our Data Again
07:11
11
Getting Help
07:46
12
Week 1 Live Session (Spring 2025)
1:03:11
1
Welcome to Fundamentals of R
01:36
2
Update Everything
02:45
3
Start a New Project
02:16
4
The Tidyverse
03:34
5
Pipes
04:15
6
select()
07:25
7
mutate()
04:25
8
filter()
10:05
9
summarize()
05:59
10
group_by() and summarize()
05:54
11
arrange()
02:07
12
Create a New Data Frame
03:58
13
Bring it All Together (Data Wrangling)
07:29
14
Week 2 Project Assignment
09:39
15
Week 2 Coworking Session (Spring 2025)
16
Week 2 Live Session (Spring 2025)
1:03:24
1
The Grammar of Graphics
04:39
2
Scatterplots
03:46
3
Histograms
05:47
4
Bar Charts
06:37
5
Setting color and fill Aesthetic Properties
02:39
6
Setting color and fill Scales
05:40
7
Setting x and y Scales
03:09
8
Adding Text to Plots
07:32
9
Plot Labels
03:57
10
Themes
02:19
11
Facets
03:12
12
Save Plots
02:57
13
Bring it All Together (Data Visualization)
06:42
14
Week 3 Project Assignment
03:30
15
Week 3 Coworking Session (Spring 2025)
16
Week 3 Live Session (Spring 2025)
1:02:31
1
Downloading and Importing Data
10:32
2
Overview of Tidy Data
05:50
3
Tidy Data Rule #1: Every Column is a Variable
07:43
4
Tidy Data Rule #3: Every Cell is a Single Value
10:04
5
Tidy Data Rule #2: Every Row is an Observation
04:42
6
Week 6 Coworking Session (Spring 2025)
7
Week 6 Live Session (Spring 2025)
1:02:38
1
Best Practices in Data Visualization
03:44
2
Tidy Data
02:25
3
Pipe Data into ggplot
09:54
4
Reorder Plots to Highlight Findings
03:37
5
Line Charts
04:17
6
Use Color to Highlight Findings
09:16
7
Declutter
08:29
8
Add Descriptive Labels to Your Plots
09:10
9
Use Titles to Highlight Findings
08:14
10
Use Annotations to Explain
07:09
11
Week 9 Coworking Session (Spring 2025)
12
Week 9 Live Session (Spring 2025)
59:09
1
Advanced Markdown
06:43
2
Tables
18:36
3
Advanced YAML and Code Chunk Options
05:53
4
Inline R Code
04:42
5
Making Your Reports Shine: Word Edition
04:30
6
Making Your Reports Shine: PDF Edition
06:11
7
Making Your Reports Shine: HTML Edition
06:06
8
Presentations
10:12
9
Dashboards
05:38
10
Websites
06:43
11
Publishing Your Work
04:38
12
Quarto Extensions
05:50
13
Parameterized Reporting, Part 1
10:57
14
Parameterized Reporting, Part 2
05:11
15
Parameterized Reporting, Part 3
07:47
16
Week 12 Coworking Session (Spring 2025)
17
Week 12 Live Session (Spring 2025)
57:01
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Michelle Brodesky • March 13, 2024
I get the following error when trying to create the penguins_data object:
I can create the object if I use "read.csv", however. But, I can see that the tidyverse is loaded, so I'm not sure why the read_csv function can't be found.
David Keyes Founder • March 13, 2024
Can you clarify how you know that the tidyverse is loaded? This error very much sounds like the tidyverse has not been loaded so I want to make sure.
Michelle Brodesky • March 13, 2024
I can see tidyverse in the "packages" tab in the lower right panel of the interface, so I believe that means it's loaded? I can paste a screenshot on Discord if that would be helpful.
Michelle Brodesky • March 13, 2024
I can see tidyverse in the "packages" tab in the lower right panel of the interface, so I believe that means it's loaded? I can paste a screenshot on Discord if that would be helpful.
Libby Heeren Coach • March 13, 2024
Hey, Michelle! All installed packages will show up in the packages pane in RStudio, but only packages that have been loaded with the library() call will have a checkmark in the box next to them. I'll check in with you on Discord for extra help, but another way to check which packages have been loaded is to run loadedNamespaces(). The package you're looking for that contains read_csv() is the readr package.
Michelle Brodesky • March 13, 2024
Thank you! I ran library(tidyverse) and then everything worked as expected.
Derrick Watsala • March 17, 2024
I would like you to help me confirm that once an Object appears in the Environment Panel, it's automatically saved. In this case our object is the penguins_data.
Libby Heeren Coach • March 17, 2024
Hi! When you run
penguins_data <- read_csv("penguins_data.csv")it's saving the data object to your environment. This environment is temporary, so it's not saving a file to your computer, but rather saving an object for you to use during your R session. Thepenguins_dataobject will go away if you restart your R session, for instance.Douglas Ndowo • March 21, 2024
Just to be clear, we see a lot of the word “penguins” in the codes so far just because the dataset we are using actually contains data on penguins 🐧. The word itself has nothing to do with R.
David Keyes Founder • March 22, 2024
Yes, your understanding is correct! We're using data from the
palmerpenguinspackage, which is why you're hearing so much about penguins. If you're interested, here's the backstory of how this dataset came to be.