Part 2: Introduction to R

# Part 2: Introduction to R
## #aectRTD workshop
### K. Bret Staudt Willet | Florida State University
### March 4, 2022

---

---

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## Homebase

- **Workshop website:** https://bretsw.github.io/aect22-workshop
- **Workshop code repository:** https://github.com/bretsw/aect22-workshop
- **tidytags R package:** https://github.com/ropensci/tidytags

## Agenda

- **Part 1: Introduction to Networks**
  - Slides: [Part 1 - Networks](1-networks.html)
- **Part 2: Introduction to R**
  - Slides: [Part 2 - R](2-intro-R.html)
- **Part 3: Network Description**
  - Slides: [Part 3 - Description](3-description.html)
- **Part 4: Network Inference**
  - Slides: [Part 4 - Inference](4-inference.html)

## Help

- Ask questions in the Zoom chat!
- Or, reach out directly:
  - Email: [bret.staudtwillet@fsu.edu](mailto:bret.staudtwillet@fsu.edu)
  - Twitter: [@bretsw](https://twitter.com/bretsw)

---

# <svg aria-hidden="true" role="img" viewBox="0 0 581 512" style="height:1em;width:1.13em;vertical-align:-0.125em;margin-left:auto;margin-right:auto;font-size:inherit;fill:#fff;overflow:visible;position:relative;"><path d="M581 226.6C581 119.1 450.9 32 290.5 32S0 119.1 0 226.6C0 322.4 103.3 402 239.4 418.1V480h99.1v-61.5c24.3-2.7 47.6-7.4 69.4-13.9L448 480h112l-67.4-113.7c54.5-35.4 88.4-84.9 88.4-139.7zm-466.8 14.5c0-73.5 98.9-133 220.8-133s211.9 40.7 211.9 133c0 50.1-26.5 85-70.3 106.4-2.4-1.6-4.7-2.9-6.4-3.7-10.2-5.2-27.8-10.5-27.8-10.5s86.6-6.4 86.6-92.7-90.6-87.9-90.6-87.9h-199V361c-74.1-21.5-125.2-67.1-125.2-119.9zm225.1 38.3v-55.6c57.8 0 87.8-6.8 87.8 27.3 0 36.5-38.2 28.3-87.8 28.3zm-.9 72.5H365c10.8 0 18.9 11.7 24 19.2-16.1 1.9-33 2.8-50.6 2.9v-22.1z"/></svg> <br><br> **Part 2:** <br> Introduction to R

---

1. We'll introduce some concepts
1. You'll try some code
1. We'll all discuss together

<div class="caption">
<p><a href="https://xkcd.com/627/" target="_blank">'Tech Support Cheat Sheet' from XKCD</a></p>
</div>

---

---

- It is increasingly used in education

- It is cross-platform, open-source, and freely-available

- It is a programming language and quite flexible

- It is capable of carrying out basic and complex statistical analyses

- It is able to work with data small (*n* = 10) and large (*n* = 1,000,000+) efficiently

- There is a great, inclusive community of users and developers

---

### To download R

- Visit [**cran.r-project.org**](https://cran.r-project.org/) to download R
- Find your operating system (Mac, Windows, or Linux)
- Download the 'latest release' on the page for your operating system and download and install the application

### To download RStudio

- Visit [**rstudio.com**](https://rstudio.com/products/rstudio/download/) to download RStudio
- Find your operating system (Mac, Windows, or Linux)
- Download the 'latest release' on the page for your operating system and download and install the application

---

---

Activities:

1. Running a single RMarkdown chunk  
1. Running another RMarkdown chunk  
1. Rendering an RMarkdown document to a PDF  
1. Creating your first visualization

---

- RMarkdown is a data analysis "notebook" that combines text with code and output
- It is a great file type to use when beginning to use R and to create reproducible analyses
- It is fun to use because you can generate different types of output (Word, PDF, and even web-based)

---

What do you think this code will do?

```r
starwars %>% 
  filter(sex == "female") %>% 
  select(name, hair_color, skin_color, homeworld)
```

---

Let's see!

```r
starwars %>% 
  filter(sex == "female") %>% 
  select(name, hair_color, skin_color, homeworld)
```

```
## # A tibble: 16 × 4
##    name               hair_color skin_color          homeworld
##    <chr>              <chr>      <chr>               <chr>    
##  1 Leia Organa        brown      light               Alderaan 
##  2 Beru Whitesun lars brown      light               Tatooine 
##  3 Mon Mothma         auburn     fair                Chandrila
##  4 Shmi Skywalker     black      fair                Tatooine 
##  5 Ayla Secura        none       blue                Ryloth   
##  6 Adi Gallia         none       dark                Coruscant
##  7 Cordé              brown      light               Naboo    
##  8 Luminara Unduli    black      yellow              Mirial   
##  9 Barriss Offee      black      yellow              Mirial   
## 10 Dormé              brown      light               Naboo    
## 11 Zam Wesell         blonde     fair, green, yellow Zolan    
## 12 Taun We            none       grey                Kamino   
## 13 Jocasta Nu         white      fair                Coruscant
## 14 Shaak Ti           none       red, blue, white    Shili    
## 15 Rey                brown      light               <NA>     
## 16 Padmé Amidala      brown      light               Naboo
```

---

What do you think this code will do?

```r
starwars %>% 
  filter(sex %in% c("male", "none"),
         height <= 150) %>% 
  arrange(desc(height)) %>%
  select(name, sex, height, mass, homeworld)
```

---

Let's see!

```r
starwars %>% 
  filter(sex %in% c("male", "none"),
         height <= 150) %>% 
  arrange(height) %>%
  select(name, sex, height, mass, homeworld)
```

```
## # A tibble: 10 × 5
##    name                  sex   height  mass homeworld  
##    <chr>                 <chr>  <int> <dbl> <chr>      
##  1 Yoda                  male      66    17 <NA>       
##  2 Ratts Tyerell         male      79    15 Aleen Minor
##  3 Wicket Systri Warrick male      88    20 Endor      
##  4 Dud Bolt              male      94    45 Vulpter    
##  5 R2-D2                 none      96    32 Naboo      
##  6 R4-P17                none      96    NA <NA>       
##  7 R5-D4                 none      97    32 Tatooine   
##  8 Sebulba               male     112    40 Malastare  
##  9 Gasgano               male     122    NA Troiken    
## 10 Watto                 male     137    NA Toydaria
```

---

# <svg aria-hidden="true" role="img" viewBox="0 0 640 512" style="height:1em;width:1.25em;vertical-align:-0.125em;margin-left:auto;margin-right:auto;font-size:inherit;fill:#fff;overflow:visible;position:relative;"><path d="M278.9 511.5l-61-17.7c-6.4-1.8-10-8.5-8.2-14.9L346.2 8.7c1.8-6.4 8.5-10 14.9-8.2l61 17.7c6.4 1.8 10 8.5 8.2 14.9L293.8 503.3c-1.9 6.4-8.5 10.1-14.9 8.2zm-114-112.2l43.5-46.4c4.6-4.9 4.3-12.7-.8-17.2L117 256l90.6-79.7c5.1-4.5 5.5-12.3.8-17.2l-43.5-46.4c-4.5-4.8-12.1-5.1-17-.5L3.8 247.2c-5.1 4.7-5.1 12.8 0 17.5l144.1 135.1c4.9 4.6 12.5 4.4 17-.5zm327.2.6l144.1-135.1c5.1-4.7 5.1-12.8 0-17.5L492.1 112.1c-4.8-4.5-12.4-4.3-17 .5L431.6 159c-4.6 4.9-4.3 12.7.8 17.2L523 256l-90.6 79.7c-5.1 4.5-5.5 12.3-.8 17.2l43.5 46.4c4.5 4.9 12.1 5.1 17 .6z"/></svg> <br><br> Try it out!

Hop over to [**Workspace 2**](workspace2.Rmd)

---

# <svg aria-hidden="true" role="img" viewBox="0 0 576 512" style="height:1em;width:1.12em;vertical-align:-0.125em;margin-left:auto;margin-right:auto;font-size:inherit;fill:#fff;overflow:visible;position:relative;"><path d="M532 386.2c27.5-27.1 44-61.1 44-98.2 0-80-76.5-146.1-176.2-157.9C368.3 72.5 294.3 32 208 32 93.1 32 0 103.6 0 192c0 37 16.5 71 44 98.2-15.3 30.7-37.3 54.5-37.7 54.9-6.3 6.7-8.1 16.5-4.4 25 3.6 8.5 12 14 21.2 14 53.5 0 96.7-20.2 125.2-38.8 9.2 2.1 18.7 3.7 28.4 4.9C208.1 407.6 281.8 448 368 448c20.8 0 40.8-2.4 59.8-6.8C456.3 459.7 499.4 480 553 480c9.2 0 17.5-5.5 21.2-14 3.6-8.5 1.9-18.3-4.4-25-.4-.3-22.5-24.1-37.8-54.8zm-392.8-92.3L122.1 305c-14.1 9.1-28.5 16.3-43.1 21.4 2.7-4.7 5.4-9.7 8-14.8l15.5-31.1L77.7 256C64.2 242.6 48 220.7 48 192c0-60.7 73.3-112 160-112s160 51.3 160 112-73.3 112-160 112c-16.5 0-33-1.9-49-5.6l-19.8-4.5zM498.3 352l-24.7 24.4 15.5 31.1c2.6 5.1 5.3 10.1 8 14.8-14.6-5.1-29-12.3-43.1-21.4l-17.1-11.1-19.9 4.6c-16 3.7-32.5 5.6-49 5.6-54 0-102.2-20.1-131.3-49.7C338 339.5 416 272.9 416 192c0-3.4-.4-6.7-.7-10C479.7 196.5 528 238.8 528 288c0 28.7-16.2 50.6-29.7 64z"/></svg> <br><br> Quick Check In

**(Five minutes in groups, five minutes together)**

- What challenges did you encounter?
- What successes did you have?
- What questions remain?

---

# <svg aria-hidden="true" role="img" viewBox="0 0 512 512" style="height:1em;width:1em;vertical-align:-0.125em;margin-left:auto;margin-right:auto;font-size:inherit;fill:#fff;overflow:visible;position:relative;"><path d="M80 368H16a16 16 0 0 0-16 16v64a16 16 0 0 0 16 16h64a16 16 0 0 0 16-16v-64a16 16 0 0 0-16-16zm0-320H16A16 16 0 0 0 0 64v64a16 16 0 0 0 16 16h64a16 16 0 0 0 16-16V64a16 16 0 0 0-16-16zm0 160H16a16 16 0 0 0-16 16v64a16 16 0 0 0 16 16h64a16 16 0 0 0 16-16v-64a16 16 0 0 0-16-16zm416 176H176a16 16 0 0 0-16 16v32a16 16 0 0 0 16 16h320a16 16 0 0 0 16-16v-32a16 16 0 0 0-16-16zm0-320H176a16 16 0 0 0-16 16v32a16 16 0 0 0 16 16h320a16 16 0 0 0 16-16V80a16 16 0 0 0-16-16zm0 160H176a16 16 0 0 0-16 16v32a16 16 0 0 0 16 16h320a16 16 0 0 0 16-16v-32a16 16 0 0 0-16-16z"/></svg> <br><br> Appendix: <br> Helpful Resources <br> and Troubleshooting

---

# Resources

**Beginners:**
- [RStudio Beginners' Guide](https://education.rstudio.com/learn/beginner/)
- Book: [*Data Science in Education Using R*](https://datascienceineducation.com)
  - See [Chapter 12](https://datascienceineducation.com/c12.html) - Walkthrough 6: Exploring Relationships Using Social Network Analysis With Social Media Data
  - [Physical copy of DSIEUR](https://www.routledge.com/Data-Science-in-Education-Using-R/Estrellado-Freer-Mostipak-Rosenberg-Velasquez/p/book/9780367422257)
  - [Even more resources from DSIEUR](https://datascienceineducation.com/c18.html)

**Intermediates:**
- [RStudio Intermediates' Guide](https://education.rstudio.com/learn/intermediate/)
- [{tidytags} package notes](https://docs.ropensci.org/tidytags/index.html)
- Book: [*R for Data Science*](http://r4ds.had.co.nz/)

**Experts:**
- [RStudio Experts' Guide](https://education.rstudio.com/learn/expert/)
- Book: [*Learning Statistics with R*](https://learningstatisticswithr.com/)
- [*Data Science in Education Using R*](https://datascienceineducation.com)
  - See [Chapter 20.3 Appendix C](https://datascienceineducation.com/c20.html#c20c) - Social Network Influence and Selection Models
- SNA resources: [Dr. Ken Frank's website](https://sites.google.com/msu.edu/kenfrank/social-network-resources)

---

# Troubleshooting

- Try to find out what the specific problem is
  -  Identify what is *not* causing the problem
- "Unplug and plug it back in" - restart R; close and reopen R
- Seek out workshops and other learning opportunities
- Reach out to others! Sharing what is causing an issue can often help to clarify the problem
  - [RStudio Community forum](https://community.rstudio.com/) (highly recommended!)
  - Twitter hashtag: [#RStats](https://twitter.com/search?q=%23RStats&src=typeahead_click&f=live)
  - [Contact Bret!](http://bretsw.com)
- General strategies on learning more: [Chapter 17 of *Data Science in Education Using R*](https://datascienceineducation.com/c17.html)

---

# <svg aria-hidden="true" role="img" viewBox="0 0 640 512" style="height:1em;width:1.25em;vertical-align:-0.125em;margin-left:auto;margin-right:auto;font-size:inherit;fill:#fff;overflow:visible;position:relative;"><path d="M192 160h32V32h-32c-35.35 0-64 28.65-64 64s28.65 64 64 64zM0 416c0 35.35 28.65 64 64 64h32V352H64c-35.35 0-64 28.65-64 64zm337.46-128c-34.91 0-76.16 13.12-104.73 32-24.79 16.38-44.52 32-104.73 32v128l57.53 15.97c26.21 7.28 53.01 13.12 80.31 15.05 32.69 2.31 65.6.67 97.58-6.2C472.9 481.3 512 429.22 512 384c0-64-84.18-96-174.54-96zM491.42 7.19C459.44.32 426.53-1.33 393.84.99c-27.3 1.93-54.1 7.77-80.31 15.04L256 32v128c60.2 0 79.94 15.62 104.73 32 28.57 18.88 69.82 32 104.73 32C555.82 224 640 192 640 128c0-45.22-39.1-97.3-148.58-120.81z"/></svg> <br><br> *Next up* <br> Part 3: <br> Network Description

[`Part 3 slide deck here`](3-description.html)