1. Intro to R

.title[
# 1. Intro to R
]
.subtitle[
## Analytics Sandbox
]
.author[
### K. Bret Staudt Willet | Florida State University
]
.date[
### January 11, 2023
]

---

# <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="M181.5 197.1l12.9 6.4c5.9 3 12.4 4.5 19.1 4.5c23.5 0 42.6-19.1 42.6-42.6V144c0-35.3-28.7-64-64-64H128c-35.3 0-64 28.7-64 64v21.4c0 23.5 19.1 42.6 42.6 42.6c6.6 0 13.1-1.5 19.1-4.5l12.9-6.4 8.4-4.2L135.1 185c-4.5-3-7.1-8-7.1-13.3V168c0-13.3 10.7-24 24-24h16c13.3 0 24 10.7 24 24v3.7c0 5.3-2.7 10.3-7.1 13.3l-11.8 7.9 8.4 4.2zm-8.6 49.4L160 240l-12.9 6.4c-12.6 6.3-26.5 9.6-40.5 9.6c-3.6 0-7.1-.2-10.6-.6v.6c0 35.3 28.7 64 64 64h64c17.7 0 32 14.3 32 32s-14.3 32-32 32H384V336 320c0-23.7 12.9-44.4 32-55.4c9.4-5.4 20.3-8.6 32-8.6V240c0-26.5 21.5-48 48-48c8.8 0 16 7.2 16 16v32 16 48c0 8.8 7.2 16 16 16s16-7.2 16-16V204.3c0-48.2-30.8-91-76.6-106.3l-8.5-2.8c-8-2.7-12.6-11.1-10.4-19.3s10.3-13.2 18.6-11.6l19.9 4C576 86.1 640 164.2 640 254.9l0 1.1h0c0 123.7-100.3 224-224 224h-1.1H256h-.6C132 480 32 380 32 256.6V256 216.8c-10.1-14.6-16-32.3-16-51.4V144l0-1.4C6.7 139.3 0 130.5 0 120c0-13.3 10.7-24 24-24h2.8C44.8 58.2 83.3 32 128 32h64c44.7 0 83.2 26.2 101.2 64H296c13.3 0 24 10.7 24 24c0 10.5-6.7 19.3-16 22.6l0 1.4v21.4c0 1.4 0 2.8-.1 4.3c12-6.2 25.7-9.6 40.1-9.6h8c17.7 0 32 14.3 32 32s-14.3 32-32 32h-8c-13.3 0-24 10.7-24 24v8h56.4c-15.2 17-24.4 39.4-24.4 64H320c-42.3 0-78.2-27.4-91-65.3c-5.1 .9-10.3 1.3-15.6 1.3c-14.1 0-27.9-3.3-40.5-9.6zM96 160c-8.8 0-16-7.2-16-16s7.2-16 16-16s16 7.2 16 16s-7.2 16-16 16zm144-16c0 8.8-7.2 16-16 16s-16-7.2-16-16s7.2-16 16-16s16 7.2 16 16z"/></svg> <br><br> **Part 1:** <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>

---

# <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> Background <br> on R and RStudio

---

- 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) %>% 
  select(name, sex, height, mass, homeworld) %>%
  arrange(desc(height))
```

---

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
```

---

```r
starwars %>% 
  unnest(starships) %>% 
  select(name, gender, starships) %>%
  head(10)
```

```
## # A tibble: 10 × 3
##    name              gender    starships               
##    <chr>             <chr>     <chr>                   
##  1 Luke Skywalker    masculine X-wing                  
##  2 Luke Skywalker    masculine Imperial shuttle        
##  3 Darth Vader       masculine TIE Advanced x1         
##  4 Biggs Darklighter masculine X-wing                  
##  5 Obi-Wan Kenobi    masculine Jedi starfighter        
##  6 Obi-Wan Kenobi    masculine Trade Federation cruiser
##  7 Obi-Wan Kenobi    masculine Naboo star skiff        
##  8 Obi-Wan Kenobi    masculine Jedi Interceptor        
##  9 Obi-Wan Kenobi    masculine Belbullab-22 starfighter
## 10 Anakin Skywalker  masculine Trade Federation cruiser
```

---

```r
starwars %>% 
  unnest(starships) %>% 
  mutate(vehicles = strsplit(starships, ",")) %>%
  unnest(starships) %>% 
  select(name, gender, starships) %>% 
  group_by(gender) %>% 
  count()
```

```
## # A tibble: 3 × 2
## # Groups:   gender [3]
##   gender        n
##   <chr>     <int>
## 1 feminine      3
## 2 masculine    27
## 3 <NA>          1
```

---

```r
glimpse(starwars)
```

```
## Rows: 87
## Columns: 14
## $ name       <chr> "Luke Skywalker", "C-3PO", "R2-D2", "Darth Vader", "Leia Or…
## $ height     <int> 172, 167, 96, 202, 150, 178, 165, 97, 183, 182, 188, 180, 2…
## $ mass       <dbl> 77.0, 75.0, 32.0, 136.0, 49.0, 120.0, 75.0, 32.0, 84.0, 77.…
## $ hair_color <chr> "blond", NA, NA, "none", "brown", "brown, grey", "brown", N…
## $ skin_color <chr> "fair", "gold", "white, blue", "white", "light", "light", "…
## $ eye_color  <chr> "blue", "yellow", "red", "yellow", "brown", "blue", "blue",…
## $ birth_year <dbl> 19.0, 112.0, 33.0, 41.9, 19.0, 52.0, 47.0, NA, 24.0, 57.0, …
## $ sex        <chr> "male", "none", "none", "male", "female", "male", "female",…
## $ gender     <chr> "masculine", "masculine", "masculine", "masculine", "femini…
## $ homeworld  <chr> "Tatooine", "Tatooine", "Naboo", "Tatooine", "Alderaan", "T…
## $ species    <chr> "Human", "Droid", "Droid", "Human", "Human", "Human", "Huma…
## $ films      <list> <"The Empire Strikes Back", "Revenge of the Sith", "Return…
## $ vehicles   <list> <"Snowspeeder", "Imperial Speeder Bike">, <>, <>, <>, "Imp…
## $ starships  <list> <"X-wing", "Imperial shuttle">, <>, <>, "TIE Advanced x1",…
```

---

```r
starwars %>% 
  ggplot() +
  geom_point(aes(x = mass, y = height, color = gender),
             alpha = 0.5
             ) +
  theme_bw()
```

![](1-intro_files/figure-html/unnamed-chunk-9-1.png)

---

Hop over to [**Workbook 1**](workbooks/workbook1.Rmd)

---

# <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="M40 48C26.7 48 16 58.7 16 72v48c0 13.3 10.7 24 24 24H88c13.3 0 24-10.7 24-24V72c0-13.3-10.7-24-24-24H40zM192 64c-17.7 0-32 14.3-32 32s14.3 32 32 32H480c17.7 0 32-14.3 32-32s-14.3-32-32-32H192zm0 160c-17.7 0-32 14.3-32 32s14.3 32 32 32H480c17.7 0 32-14.3 32-32s-14.3-32-32-32H192zm0 160c-17.7 0-32 14.3-32 32s14.3 32 32 32H480c17.7 0 32-14.3 32-32s-14.3-32-32-32H192zM16 232v48c0 13.3 10.7 24 24 24H88c13.3 0 24-10.7 24-24V232c0-13.3-10.7-24-24-24H40c-13.3 0-24 10.7-24 24zM40 368c-13.3 0-24 10.7-24 24v48c0 13.3 10.7 24 24 24H88c13.3 0 24-10.7 24-24V392c0-13.3-10.7-24-24-24H40z"/></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!](https://bretsw.com)
- General strategies on learning more: [Chapter 17 of *Data Science in Education Using R*](https://datascienceineducation.com/c17.html)