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Week 1: Getting Started with R
- Welcome to Getting Started with R
- Install R
- Install RStudio
- Projects
- Files in R
- Packages
- Import Data
- Objects and Functions
- Examine our Data
- Import Our Data Again
- Getting Help
- Wrapping Up
- R in 3 Months Spring 2022 Week 1 Live Session
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Week 2: Fundamentals of R (RMarkdown)
- Welcome to Fundamentals of R
- RMarkdown Overview
- YAML
- Text
- Code Chunks
- Wrapping Up
- R in 3 Months Spring 2022 Week 2 Project Assignment
- R in 3 Months Spring 2022 Week 2 Office Hours
- R in 3 Months Spring 2022 Week 2 Live Session
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Week 3: Fundamentals of R (Data Wrangling and Analysis)
- Getting Started
- The Tidyverse
- select
- mutate
- filter
- summarize
- group_by
- count
- arrange
- Create a New Data Frame
- Crosstabs
- Wrapping Up
- R in 3 Months Spring 2022 Week 3 Office Hours
- R in 3 Months Spring 2022 Week 3 Live Session
- R in 3 Months Spring 2022 Week 3 Project Assignment
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Week 4: Fundamentals of R (Data Visualization)
- An Important Workflow Tip
- The Grammar of Graphics
- Scatterplots
- Histograms
- Bar Charts
- color and fill
- scales
- Text and Labels
- Plot Labels
- Themes
- Facets
- Save Plots
- Wrapping Up
- You Did It!
- R in 3 Months Spring 2022 Week 4 Office Hours
- R in 3 Months Spring 2022 Week 4 Live Session
- R in 3 Months Spring 2022 Week 4 Project Assignment
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Week 5: Catch-Up Week
- R in 3 Months Spring 2022 Week 5 Office Hours
- R in 3 Months Spring 2022 Week 5 Project Assignment: ASSIGNMENT AMNESTY
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Week 6: Git + GitHub
- What is Git? What is GitHub?
- Why Should You Learn to Use Git and GitHub?
- Update Everything
- Install Git
- Configure Git
- Create a Local Git Repository
- Commits
- Commit History
- GitHub Repositories
- Connect RStudio and GitHub
- Push an RStudio Project to a GitHub Repository
- Pull a GitHub Repository to an RStudio Project
- Keep RStudio and GitHub in Sync
- R in 3 Months Spring 2022 Week 6 Office Hours
- R in 3 Months Spring 2022 Week 6 Live Session
- R in 3 Months Spring 2022 Week 6 Project Assignment
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Week 7: Going Deeper with R (Advanced Data Wrangling, Part 1)
- Overview
- Importing Data
- Tidy Data
- Reshaping Data
- Dealing with Missing Data
- Changing Variable Types
- Advanced Variable Creation
- Advanced Summarizing
- Binding Data Frames
- R in 3 Months Spring 2022 Week 7 Office Hours
- R in 3 Months Spring 2022 Week 7 Project Assignment
- R in 3 Months Spring 2022 Week 7 Live Session
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Week 8: Going Deeper with R (Advanced Data Wrangling, Part 2)
- Functions
- Merging Data
- Renaming Variables
- Quick Interlude to Reorganize our Code
- Exporting Data
- R in 3 Months Spring 2022 Week 8 Office Hours
- R in 3 Months Spring 2022 Week 8 Live Session
- R in 3 Months Spring 2022 Week 8 Project Assignment
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Week 9: Catch-Up Week
- R in 3 Months Spring 2022 Week 9 Office Hours
- R in 3 Months Spring 2022 Week 9 - Assignment Amnesty
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Week 10: Going Deeper with R (Advanced Data Visualization, Part 1)
- Data Visualization Best Practices
- Tidy Data
- Pipe Data Into ggplot
- Reorder Plots to Highlight Findings
- Line Charts
- Use Color to Highlight Findings
- Declutter
- Use the scales Package for Nicely Formatted Values
- Use Direct Labeling
- R in 3 Months Spring 2022 Week 10 Office Hours
- R in 3 Months Spring 2022 Week 10 Live Session
- R in 3 Months Spring 2022 Week 10 Project Assignment
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Week 11: Going Deeper with R (Advanced Data Visualization, Part 2)
- Use Axis Text Wisely
- Use Titles to Highlight Findings
- Use Color in Titles to Highlight Findings
- Use Annotations to Explain
- Tweak Spacing
- Customize Your Theme
- Customize Your Fonts
- Try New Plot Types
- R in 3 Months Spring 2022 Week 11 Live Session
- R in 3 Months Spring 2022 Week 11 Office Hours
- R in 3 Months Spring 2022 Week 11 Project Assignment
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Week 12: Going Deeper with R (Advanced RMarkdown)
- Advanced Markdown Text Formatting
- Tables
- Advanced YAML
- Inline R Code
- Making Your Reports Shine: Word Edition
- Making Your Reports Shine: HTML Edition
- Making Your Reports Shine: PDF Edition
- Presentations
- Dashboards
- Other Formats
- You Did It!
- R in 3 Months Spring 2022 Week 12 Office Hours
- R in 3 Months Spring 2022 Week 12 Live Session
- R in 3 Months Spring 2022 Week 12 Project Assignment
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Week 13: Final Assignment
- R in 3 Months Spring 2022 Week 13 Office Hours
- R in 3 Months Spring 2022 Week 13 Live Session
- R in 3 Months Spring 2022 Final Project Assignment
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WEEK 14: Retrospective
R in 3 Months (Spring 2022)
Scatterplots
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This lesson is called Scatterplots, part of the R in 3 Months (Spring 2022) course. This lesson is called Scatterplots, part of the R in 3 Months (Spring 2022) course.
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Transcript
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Your Turn
Complete the scatterplot sections of the data-visualization-exercises.Rmd file.
Learn More
Scatterplot Resources
Claus Wilke talks about scatterplots in Chapter 12 of his book Fundamentals of Data Visualization. Michael Toth also has a long blog post about all of the ins and outs of making scatterplots in ggplot.
You can also find examples of code to make scatterplots on the Data to Viz website , the R Graph Gallery website , and in Chapter 5 of the R Graphics Cookbook.
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Jeff Shandling
April 5, 2021
Getting the following error: Error in loadNamespace(name) : there is no package called ‘farver’ when I add the mapping code, the variables are not auto-populating
Abby Isaacson
April 6, 2021
We may not be there yet, but for axis labeling if we wanted to add units to the labels, is that easy?
Jimmy Frickey
April 26, 2021
Hi David,
Here are 2 versions of code that both produce the scatterplot of height vs weight from nhanes dataset. The first is from your solutions, and the second if following r4ds text. Can you briefly comment on why they both "work"? Is one better than another?
ggplot(data = nhanes, mapping = aes(x = weight, y = height)) + geom_point()
ggplot(data = nhanes) + geom_point(mapping = aes(x = weight, y = height))
Juan Clavijo
October 11, 2021
You mentioned that ggplot will automatically remove observations with missing data. If I'm plotting average test scores for mid-term and final exams, for example, and one student took the final but did not take the mid-term, will ggplot remove that student's data from the graph completely, or will it just plot the final exam and omit the mid-term score that does not exist?
Esther Okoye
April 5, 2022
Hello, Please i cant the data visualization exercise on my studio, do i have to do anything?
Elijah Phillips
October 13, 2022
Where do we get the .rmd file for this?
Ellen Wilson
November 1, 2022
It seems like the clean_names function didn't work for me--when I start typing the code for the scatterplot, it isn't suggesting the variable names. This is what I put for clean_names
And then I got this message (which looks different from what you got)
Rows: 10000 Columns: 22── Column specification ────────────────────────────────────────────────────────────────────────────── Delimiter: "," chr (13): SurveyYr, Gender, AgeDecade, Race1, Education, MaritalStatus, HHIncome, HomeOwn, Work, H... dbl (9): ID, Age, Weight, Height, BMI, DaysPhysHlthBad, DaysMentHlthBad, SleepHrsNight, PhysActiv... ℹ Use
spec()
to retrieve the full column specification for this data. ℹ Specify the column types or setshow_col_types = FALSE
to quiet this message.Oscar Tetteh
March 28, 2023
Please could you email me the nhames data set? This is my mail: bismarktetteh25@gmail.com