Bring it All Together (Data Wrangling)
This lesson is called Bring it All Together (Data Wrangling), part of the R in 3 Months (Spring 2025) course. This lesson is called Bring it All Together (Data Wrangling), part of the R in 3 Months (Spring 2025) course.
Transcript
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View code shown in video
# Load Packages -----------------------------------------------------------
library(tidyverse)
library(janitor)
# Import Data -------------------------------------------------------------
# Data from https://github.com/rstudio/r-community-survey
survey_data <- read_tsv("2020-combined-survey-final.tsv") |>
clean_names()
survey_data |>
select(contains("enjoy"))
survey_data |>
filter(is.na(qr_enjoyment)) |>
select(qr_enjoyment)
survey_data |>
glimpse()
avg_r_enjoyment <- survey_data |>
drop_na(qr_enjoyment) |>
group_by(qcountry) |>
summarize(avg_enjoyment = mean(qr_enjoyment),
n = n()) |>
filter(n >= 10) |>
arrange(desc(avg_enjoyment))Learn More
If you want to see a visual representation of how the various dplyr functions you've learned in this section of the course work, check out the Tidy Data Tutor website.
A less visual, though equally useful, approach is the tidylog package. It gives you feedback on each step of your pipeline, showing the data was transformed.
Have any questions? Put them below and we will help you out!
Course Content
127 Lessons
1
Welcome to Getting Started with R
00:57
2
Install R
02:05
3
Install RStudio
02:14
4
Files in R
04:33
5
Projects
07:54
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
Week 1 Live Session (Spring 2025)
1:03:11
1
Welcome to Fundamentals of R
01:36
2
Update Everything
02:45
3
Start a New Project
02:16
4
The Tidyverse
03:34
5
Pipes
04:15
6
select()
07:25
7
mutate()
04:25
8
filter()
10:05
9
summarize()
05:59
10
group_by() and summarize()
05:54
11
arrange()
02:07
12
Create a New Data Frame
03:58
13
Bring it All Together (Data Wrangling)
07:29
14
Week 2 Project Assignment
09:39
15
Week 2 Coworking Session (Spring 2025)
16
Week 2 Live Session (Spring 2025)
1:03:24
1
The Grammar of Graphics
04:39
2
Scatterplots
03:46
3
Histograms
05:47
4
Bar Charts
06:37
5
Setting color and fill Aesthetic Properties
02:39
6
Setting color and fill Scales
05:40
7
Setting x and y Scales
03:09
8
Adding Text to Plots
07:32
9
Plot Labels
03:57
10
Themes
02:19
11
Facets
03:12
12
Save Plots
02:57
13
Bring it All Together (Data Visualization)
06:42
14
Week 3 Project Assignment
03:30
15
Week 3 Coworking Session (Spring 2025)
16
Week 3 Live Session (Spring 2025)
1:02:31
1
Downloading and Importing Data
10:32
2
Overview of Tidy Data
05:50
3
Tidy Data Rule #1: Every Column is a Variable
07:43
4
Tidy Data Rule #3: Every Cell is a Single Value
10:04
5
Tidy Data Rule #2: Every Row is an Observation
04:42
6
Week 6 Coworking Session (Spring 2025)
7
Week 6 Live Session (Spring 2025)
1:02:38
1
Best Practices in Data Visualization
03:44
2
Tidy Data
02:25
3
Pipe Data into ggplot
09:54
4
Reorder Plots to Highlight Findings
03:37
5
Line Charts
04:17
6
Use Color to Highlight Findings
09:16
7
Declutter
08:29
8
Add Descriptive Labels to Your Plots
09:10
9
Use Titles to Highlight Findings
08:14
10
Use Annotations to Explain
07:09
11
Week 9 Coworking Session (Spring 2025)
12
Week 9 Live Session (Spring 2025)
59:09
1
Advanced Markdown
06:43
2
Tables
18:36
3
Advanced YAML and Code Chunk Options
05:53
4
Inline R Code
04:42
5
Making Your Reports Shine: Word Edition
04:30
6
Making Your Reports Shine: PDF Edition
06:11
7
Making Your Reports Shine: HTML Edition
06:06
8
Presentations
10:12
9
Dashboards
05:38
10
Websites
06:43
11
Publishing Your Work
04:38
12
Quarto Extensions
05:50
13
Parameterized Reporting, Part 1
10:57
14
Parameterized Reporting, Part 2
05:11
15
Parameterized Reporting, Part 3
07:47
16
Week 12 Coworking Session (Spring 2025)
17
Week 12 Live Session (Spring 2025)
57:01
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Valliappan Muthu • May 17, 2024
Similar to select (var1:var2) is there a way to do drop_na (var1:var2)?
David Keyes Founder • May 17, 2024
I believe you can select a range in
drop_na()though I've never actually tried it myself. Give it a shot and let me know if it works!Valliappan Muthu • May 17, 2024
Hi. It works!
but the problem is I had one or more missing data in almost all observations, and I had zero observations after drop_na, Probably I need to recode NA to something else for a meaningful analysis.
David Keyes Founder • May 18, 2024
Yes, sounds more like an issue with your data at this point!
Zachary Li • December 20, 2024
Hi, David, where is the link to download 2020-combined-survey-final as mentioned in the lecture? Thank you for your time.
David Keyes Founder • December 20, 2024
You can find the data itself here. It is part of this GitHub repo. Hope that helps!
Gaurab Pradhan • March 15, 2025
Is there a read Excel function in the tidyverse package, or do I need to install the readxl package?
Gracielle Higino Coach • March 16, 2025
Hi Gaurab! The
{readxl}package is part of the Tidyverse! If you install{tidyverse},{readxl}will be installed as well. However, as it's not a "core" Tidyverse package, you still might need to load it separately.Gaurab Pradhan • March 18, 2025
Thanks Gracielle