Changing Variable Types
This lesson is called Changing Variable Types, part of the R in 3 Months (Fall 2022) course. This lesson is called Changing Variable Types, part of the R in 3 Months (Fall 2022) course.
Transcript
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Your Turn
Convert the
number_of_studentsvariable to numeric by usingas.numeric()Make sure you can use your
number_of_studentsvariable to count the total number of students in Oregon
Learn More
The best place to learn more about changing variable types is Chapter 20 of R for Data Science. Be warned that the chapter is dense, but it goes over, in greater depth, various variable (technically, vector) types, how to change them, etc.
Have any questions? Put them below and we will help you out!
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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Hannah Ridenour LaFrance • December 14, 2022
I changed some of my variables to numeric in order to run a correlation test, but when I attempt to run cor.test, I get the error message that "'x' must be a numeric vector" even though both x and y are reading as dbl variables. My code is here: https://github.com/herlafrance/NBV_HRL2022RCourse/blob/master/VSA_2022_HRL_NBV_ongoing_project.Rmd with the issues in question occurring from lines 195-222. I'm wondering if there's something going on with na values? Not sure what the remaining roadblock is.