color and fill
This lesson is called color and fill, part of the R in 3 Months (Fall 2022) course. This lesson is called color and fill, part of the R in 3 Months (Fall 2022) course.
Transcript
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Your Turn
Complete the color and fill sections of the data-visualization-exercises.Rmd file.
Learn More
color and fill Resources
You may want to review Chapter 3 from R for Data Science , which includes a section on mapping data to color and fill aesthetics. Chapter 2 of Fundamentals of Data Visualization has a similar discussion. So does Chapter 3 of Data Visualization: A Practical Introduction.
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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Atlang Mompe • April 4, 2021
Hi David, when you do the coord_flip() - can you order the data into ascending or descending by the variable? If so, could you kindly show us how to do so? So for the age_decade by height - what if I wanted to see the tallest age_decade to the shortest age_decade, what would the code look lik?
Thank you, Atty
Kateryn Pino • April 8, 2021
Hi David, In this exercise, Can I drop NAs in the same ggplot code, or I necessarily have to do some data wrangling first? Thanks!
Elan Sykes • October 7, 2021
At this point in the exercise file, my code stopped automatically indenting and the function help tooltips stopped appearing. The commented lines in the code chunk also appear in blue instead of green here. I'm not sure what I did to cause this, and I got the code to work by indenting myself, but it takes a lot longer when it's not running automatically. Did I mess something up that I can change back easily?