Factors in R
This lesson is called Factors in R, part of the R in 3 Months (Spring 2026) course. This lesson is called Factors in R, part of the R in 3 Months (Spring 2026) course.
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Course Content
148 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 (Spring 2026)
18
Week 2 Live Session (Spring 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 (Spring 2026)
18
Week 3 Live Session (Spring 2026)
1:00:46
1
Downloading and Importing Data
08:13
2
Overview of Tidy Data
05:03
3
Tidy Data Rule #1: Every Column is a Variable
06:26
4
Tidy Data Rule #3: Every Cell is a Single Value
09:27
5
Tidy Data Rule #2: Every Row is an Observation
04:05
6
Quiz
7
Week 6 Coworking Session (Spring 2026)
8
Week 6 Live Session (Spring 2026)
59:31
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 (Spring 2026)
13
Week 9 Live Session (Spring 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 (Spring 2026)
18
Week 12 Live Session (Spring 2026)
57:26
1
Working with labelled data
05:35
2
Understanding Documentation Pages
05:20
3
Factors in R
11:18
4
Add citations to Quarto documents
10:42
5
Change titles of facet plots
08:16
6
Population pyramid plot
04:24
7
Why use Git - example case
06:13
8
How to access data not on GitHub
13:46
9
Dealing with merge conflicts in GitHub Desktop
03:22
10
Crosstabs
06:58
11
Difference between == and %in%
03:17
12
Quarto - rendering and working directories
13:05
13
Using Function Arguments
13:06
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Hilde Karlsen • October 14, 2024
I absolutely love this video! I don't know who the teacher is, but her way of explaining factors versus character strings is so pedagogical. The entire video is very pedagogical, by the way.
I also appreciate that she's demonstrating the difference between using the same variable/arguments for both the fill (legend) and the x-axis. This is incredibly helpful because I struggle with setting the fill/legend correctly. I often wonder what the legend should be when I'm using specific x and y variables.
Thank you so much for this video. Please pass along my compliments to the teacher if you're still in touch with her.<3
Gracielle Higino Coach • October 16, 2024
I'm glad this was helpful, Hilde! Do you think that's what you were looking for? I think this shows a way to set the labels to your variables without using labelled data =D Down the road we can practice how to implement these things in a function so you don't need to do it manually every time. I did send your compliments to Libby, she's really a star ✨
Hilde Karlsen • October 16, 2024
Thank you for sending my compliments to Libby, Gracielle, that means a lot! <3
When it comes to what I am looking for and if this video gave me what I was looking for, I think the answer is both yes and no.
Yes because - as you say it shows a way to set labels to variables without using labelled data, which is good! :-)
No because - I really want to be able to automate the process even more (write fewer lines of code/write code that is not repeating itself, i.e. "dry" code), and as you say, implementing this as a function is what I am really looking for! I would love to be able to write better functions. I have written some functions, but they have mostly been "wrappers" around other functions, such as passing some variables into a ggplot that has a certain look, or passing some variables into a correlation plot/heatmap that has a certain look.
So I am really looking forward to learning more about functions! But if you have some more videos by Libby on your server/in your database, I would absolutely love to see them, because her way of explaining things and giving examples pairs very well with my way of learning and remembering. :-)
Gracielle Higino Coach • October 17, 2024
Exactly! Let's get to the function lesson week and we can work together on it! But keep in mind that "lines of code" is not a metric for good code. Sometimes it's ok to write "essays" of code, as long as you're not repeating yourself. Functions tend to be long because they try to do a lot a once, but you only need to write them once, store them in a separate script, and re-use them as often as you need with a single line of code - which is beautiful.
Hilde Karlsen • October 17, 2024
Ah, I take note of what you are saying, as that makes sense! Thank you for pointing that out to me! I want to write clear and understandable code (and well documented code), and not repeat myself :-)
Sara Parisi • October 17, 2024
Thanks for posting this! Really helpful video.
Gracielle Higino Coach • October 17, 2024
YAY! I'm glad it helped you, Sara!
Mike LeVan • May 28, 2025
This was great! Really helped my understanding of factors and how to order them. Kudos to Libby!