R in 3 Months Fall 2022 Week 4 Live Session
This lesson is called R in 3 Months Fall 2022 Week 4 Live Session, part of the R in 3 Months (Fall 2022) course. This lesson is called R in 3 Months Fall 2022 Week 4 Live Session, part of the R in 3 Months (Fall 2022) course.
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Course Content
142 Lessons
1
Welcome to Getting Started with R
00:57
2
Install R
02:05
3
Install RStudio
02:14
4
Projects
07:54
5
Files in R
04:33
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
Wrapping Up
13
R in 3 Months Fall 2022 - Introductions thread!
14
R in 3 Months Fall 2022 Week 1 Live Session
59:22
1
Getting Started
03:01
2
The Tidyverse
12:11
3
select
05:48
4
mutate
04:08
5
filter
10:26
6
summarize
03:20
7
group_by
02:56
8
count
02:06
9
arrange
03:58
10
Create a New Data Frame
02:42
11
Crosstabs
06:58
12
Wrapping Up
13
R in 3 Months Fall 2022 Week 3 Project Assignment
02:33
14
R in 3 Months Fall 2022 Week 3 Drop-in Session
1:03:00
15
R in 3 Months Fall 2022 Week 3 Live Session
1:01:42
1
An Important Workflow Tip
05:00
2
The Grammar of Graphics
06:08
3
Scatterplots
05:15
4
Histograms
02:31
5
Bar Charts
06:32
6
color and fill
03:58
7
scales
09:14
8
Text and Labels
08:04
9
Plot Labels
06:06
10
Themes
03:56
11
Facets
05:57
12
Save Plots
05:17
13
Wrapping Up
14
You Did It!
15
R in 3 Months Fall 2022 Week 4 Project Assignment
04:32
16
R in 3 Months Fall 2022 Week 4 Drop-in Session
1:02:15
17
R in 3 Months Fall 2022 Week 4 Live Session
1:00:17
1
Welcome, Logistics, Course Materials, and Additional Resources
2
What is Git? What is GitHub?
02:23
3
Why Should You Learn to Use Git and GitHub?
03:04
4
Update Everything
07:34
5
Install Git
04:04
6
Configure Git
02:10
7
Create a Local Git Repository
03:16
8
Commits
06:00
9
Commit History
04:28
10
GitHub Repositories
04:47
11
Connect RStudio and GitHub
05:06
12
Push an RStudio Project to a GitHub Repository
02:57
13
Pull a GitHub Repository to an RStudio Project
02:52
14
Keep RStudio and GitHub in Sync
02:27
15
R in 3 Months Fall 2022 Week 6 Project Assignment
07:55
16
R in 3 Months Fall 2022 Week 6 Drop-in Session
17
R in 3 Months Fall 2022 Week 6 Live Session
1:02:01
1
Overview
2
Importing Data
15:45
3
Tidy Data
08:11
4
Reshaping Data
10:18
5
Dealing with Missing Data
04:56
6
Changing Variable Types
05:30
7
Advanced Variable Creation
19:26
8
Advanced Summarizing
10:00
9
Binding Data Frames
06:50
10
R in 3 Months Fall 2022 Week 7 Drop-in Session
1:06:06
11
R in 3 Months Fall 2022 Week 7 Live Session
1:01:49
1
Data Visualization Best Practices
04:51
2
Tidy Data
04:01
3
Pipe Data Into ggplot
04:50
4
Reorder Plots to Highlight Findings
06:09
5
Line Charts
04:10
6
Use Color to Highlight Findings
08:25
7
Declutter
10:47
8
Use the scales Package for Nicely Formatted Values
03:42
9
Use Direct Labeling
11:43
10
R in 3 Months Fall 2022 Week 9 Project Assignment
11
R in 3 Months Fall 2022 Week 9 Drop-in Session
22:04
12
R in 3 Months Fall 2022 Week 9 Live Session
1:02:50
1
Use Axis Text Wisely
03:15
2
Use Titles to Highlight Findings
03:33
3
Use Color in Titles to Highlight Findings
03:51
4
Use Annotations to Explain
04:52
5
Tweak Spacing
05:11
6
Customize Your Theme
02:48
7
Customize Your Fonts
08:18
8
Try New Plot Types
11:50
9
R in 3 Months Fall 2022 Week 11 Project Assignment
03:23
10
R in 3 Months Fall 2022 Week 11 Drop-in Session
11
R in 3 Months Fall 2022 Week 11 Live Session
57:28
1
Advanced Markdown Text Formatting
10:52
2
Tables
19:33
3
Advanced YAML
11:49
4
Inline R Code
06:57
5
Making Your Reports Shine: Word Edition
06:53
6
Making Your Reports Shine: HTML Edition
06:32
7
Making Your Reports Shine: PDF Edition
08:21
8
Presentations
04:21
9
Dashboards
06:28
10
Other Formats
04:57
11
You Did It!
12
R in 3 Months Fall 2022 Week 12 Drop-in Session
13
R in 3 Months Fall 2022 Week 12 Live Session
1:04:50
1
All R in 3 Months Fall 2022 Videos
2
Reading documentation pages
05:20
3
Working with file paths and RStudio Projects
05:37
4
Styling RMarkdown docs
5
Structuring large projects (and dealing with slow knitting of Rmd files)
03:47
6
Quarto vs RMarkdown
02:56
7
How to get lesson and lecture slides
03:15
8
{lubridate} for working with dates and times
07:28
9
Statistical Tests
10:17
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Nadia Chang • October 17, 2022
Hi Charlie! I just have a question in line 26 of the code of the David's bar chart from Oregon report, the line says: label = paste(population, scales::percent(value)))+
Why do scales function uses "::" or when do I know when to use "::"?