Getting data from the web: API access 🎃

.title[
# Getting data from the web: API access 🎃
]
.author[
### INFO 5940 <br /> Cornell University
]

---

# Methods for obtaining data online

---

## Methods for obtaining data online

* Click and download
* Install and play
* API query
* Scraping

---

## Click and download

* `read.csv` or `readr::read_csv`
* `downloader` package or `curl`

---

## Application programming interface (API)

- Representational State Transfer (REST)
- Uniform Resource Location (URL)
- HTTP methods
    - GET
    - POST

---

## Application programming interface (API)

---

## RESTful queries

1. Submit request to server via URL
1. Return result in a structured format
1. Parse results into a local format

---

## Install and play packages

* Packages with R functions written for existing APIs
* Useful because
    * Reproducible
    * Up-to-date (ideally)
    * Ease of access

---

# Using APIs with existing R packages

---

## `manifestoR`

* Collects and organizes political party manifestos from around the world
* Over 1000 parties from 1945 until today in over 50 countries on five continents
* [`manifestoR`](https://github.com/ManifestoProject/manifestoR)

---

## API authentication

* Key/token
* Obtain key
* Store in `.Rprofile`

```r
# in .Rprofile
options(this_is_my_key = "XXXX")

# later, in the R script:
key <- getOption("this_is_my_key")
```

* `usethis::edit_r_profile()`
* Read the documentation - different packages have different storage methods

---

## Load library and set API key

```r
library(manifestoR)

# retrieve API key stored in .Rprofile
mp_setapikey(key = getOption("manifesto_key"))
```

---

## Retrieve the database

```r
(mpds <- mp_maindataset())
```

```
## Connecting to Manifesto Project DB API... 
## Connecting to Manifesto Project DB API... corpus version: 2022-1
```

```
## # A tibble: 4,778 × 174
##    country countryname oecdmem…¹ eumem…² edate        date party party…³ party…⁴
##      <dbl> <chr>           <dbl>   <dbl> <date>      <dbl> <dbl> <chr>   <chr>  
##  1      11 Sweden              0       0 1944-09-17 194409 11220 Commun… "SKP"  
##  2      11 Sweden              0       0 1944-09-17 194409 11320 Social… "SAP"  
##  3      11 Sweden              0       0 1944-09-17 194409 11420 People… "FP"   
##  4      11 Sweden              0       0 1944-09-17 194409 11620 Right … ""     
##  5      11 Sweden              0       0 1944-09-17 194409 11810 Agrari… ""     
##  6      11 Sweden              0       0 1948-09-19 194809 11220 Commun… "SKP"  
##  7      11 Sweden              0       0 1948-09-19 194809 11320 Social… "SAP"  
##  8      11 Sweden              0       0 1948-09-19 194809 11420 People… "FP"   
##  9      11 Sweden              0       0 1948-09-19 194809 11620 Right … ""     
## 10      11 Sweden              0       0 1948-09-19 194809 11810 Agrari… ""     
## # … with 4,768 more rows, 165 more variables: parfam <dbl>, coderid <dbl>,
## #   manual <dbl>, coderyear <dbl>, testresult <dbl>, testeditsim <dbl>,
## #   pervote <dbl>, voteest <dbl>, presvote <dbl>, absseat <dbl>,
## #   totseats <dbl>, progtype <dbl>, datasetorigin <dbl>, corpusversion <chr>,
## #   total <dbl>, peruncod <dbl>, per101 <dbl>, per102 <dbl>, per103 <dbl>,
## #   per104 <dbl>, per105 <dbl>, per106 <dbl>, per107 <dbl>, per108 <dbl>,
## #   per109 <dbl>, per110 <dbl>, per201 <dbl>, per202 <dbl>, per203 <dbl>, …
```

---

---

## Download manifestos

---

## Census data with `tidycensus`

* API to access data from US Census Bureau
    * Decennial census
    * American Community Survey
* Returns tidy data frames with (optional) `sf` geometry
* Search for variables with `load_variables()`

---

## Store API key

```r
library(tidycensus)
```

```r
census_api_key("YOUR API KEY GOES HERE")
```

---

## Obtain data

```r
usa_inc <- get_acs(
  geography = "state",
  variables = c(medincome = "B19013_001"),
  year = 2020
)
usa_inc
```

```
## # A tibble: 52 × 5
##    GEOID NAME                 variable  estimate   moe
##    <chr> <chr>                <chr>        <dbl> <dbl>
##  1 01    Alabama              medincome    52035   377
##  2 02    Alaska               medincome    77790  1134
##  3 04    Arizona              medincome    61529   286
##  4 05    Arkansas             medincome    49475   431
##  5 06    California           medincome    78672   270
##  6 08    Colorado             medincome    75231   379
##  7 09    Connecticut          medincome    79855   587
##  8 10    Delaware             medincome    69110  1112
##  9 11    District of Columbia medincome    90842  1580
## 10 12    Florida              medincome    57703   269
## # … with 42 more rows
```

---

## Visualize data

---

# Twitter API

* REST API
* Streaming API

* [`rtweet`](https://docs.ropensci.org/rtweet/)

---

# Using `rtweet`

```r
library(rtweet)
```

* Requires a Twitter account
* Prompt to authorize application on first usage

---

# Searching tweets

```r
rt <- search_tweets(
  q = "#rstats",
  n = 3000,
  include_rts = FALSE
)
rt
```

```
## # A tibble: 1,021 × 43
##    created_at               id id_str       full_…¹ trunc…² displ…³ entities    
##    <dttm>                <dbl> <chr>        <chr>   <lgl>     <dbl> <list>      
##  1 2022-10-03 13:39:02 1.58e18 15769902220… "Códig… FALSE       165 <named list>
##  2 2022-10-03 09:38:00 1.58e18 15769295627… "I wan… FALSE       135 <named list>
##  3 2022-09-29 00:51:18 1.58e18 15753474632… "The c… FALSE       272 <named list>
##  4 2022-10-05 11:32:28 1.58e18 15776831442… "Me re… FALSE        51 <named list>
##  5 2022-10-05 11:27:54 1.58e18 15776819973… "Wie m… FALSE        95 <named list>
##  6 2022-10-05 11:27:29 1.58e18 15776818927… "Metap… FALSE        71 <named list>
##  7 2022-10-05 11:23:00 1.58e18 15776807620… "🎫 Do… FALSE       285 <named list>
##  8 2022-10-05 11:22:54 1.58e18 15776807400… "Here’… FALSE       210 <named list>
##  9 2022-10-05 11:22:39 1.58e18 15776806760… "Daily… FALSE       198 <named list>
## 10 2022-10-05 11:21:55 1.58e18 15776804886… "Image… FALSE        73 <named list>
## # … with 1,011 more rows, 36 more variables: metadata <list>, source <chr>,
## #   in_reply_to_status_id <dbl>, in_reply_to_status_id_str <chr>,
## #   in_reply_to_user_id <dbl>, in_reply_to_user_id_str <chr>,
## #   in_reply_to_screen_name <chr>, geo <list>, coordinates <list>,
## #   place <list>, contributors <lgl>, is_quote_status <lgl>,
## #   retweet_count <int>, favorite_count <int>, favorited <lgl>,
## #   retweeted <lgl>, possibly_sensitive <lgl>, lang <chr>, …
```

---

# Searching users

```r
countvoncount <- get_timeline(user = "countvoncount", n = 4000)
countvoncount
```

```
## # A tibble: 3,250 × 43
##    created_at               id id_str       full_…¹ trunc…² displ…³ entities    
##    <dttm>                <dbl> <chr>        <chr>   <lgl>     <dbl> <list>      
##  1 2022-10-04 22:52:10 1.58e18 15774918103… Three … FALSE        42 <named list>
##  2 2022-10-04 16:52:10 1.58e18 15774012115… Three … FALSE        40 <named list>
##  3 2022-10-04 11:52:09 1.58e18 15773257125… Three … FALSE        41 <named list>
##  4 2022-10-03 20:52:08 1.58e18 15770992154… Three … FALSE        51 <named list>
##  5 2022-10-03 10:52:08 1.58e18 15769482177… Three … FALSE        42 <named list>
##  6 2022-10-02 22:52:07 1.58e18 15767670198… Three … FALSE        40 <named list>
##  7 2022-10-02 12:52:06 1.58e18 15766160220… Three … FALSE        40 <named list>
##  8 2022-10-01 15:52:04 1.58e18 15762989262… Three … FALSE        36 <named list>
##  9 2022-09-30 22:52:03 1.58e18 15760422298… Three … FALSE        38 <named list>
## 10 2022-09-30 15:52:03 1.58e18 15759365312… Three … FALSE        38 <named list>
## # … with 3,240 more rows, 36 more variables: source <chr>,
## #   in_reply_to_status_id <lgl>, in_reply_to_status_id_str <lgl>,
## #   in_reply_to_user_id <lgl>, in_reply_to_user_id_str <lgl>,
## #   in_reply_to_screen_name <lgl>, geo <list>, coordinates <list>,
## #   place <list>, contributors <lgl>, is_quote_status <lgl>,
## #   retweet_count <int>, favorite_count <int>, favorited <lgl>,
## #   retweeted <lgl>, lang <chr>, possibly_sensitive <list>, …
```

---

# Visualizing tweets

```r
ts_plot(countvoncount, by = "1 week")
```

---

# Visualizing tweets

```r
ts_plot(countvoncount, by = "1 month")
```

---

# Visualizing tweets

.panelset.sideways[

```r
ts_plot(countvoncount, by = "1 week") +
  theme(plot.title = element_text(face = "bold")) +
  labs(
    x = NULL, y = NULL,
    title = "Frequency of @countvoncount Twitter posts",
    subtitle = "Twitter status (tweet) counts aggregated using one week intervals",
    caption = "\nSource: Data collected from Twitter's REST API via rtweet"
  )
```

]

]

---

# Exercise: Practice using `rtweet`

---

# Writing an API function

---

## Writing an API function

* No package for API
* Write your own function!
* [Open Movie Database](http://www.omdbapi.com/)

---

---

## Expected elements

1. Authentication Key/Token
1. Base URL
1. Search Parameters
1. Response Format

---

## Determine the shape of an API request

[Use the documentation](https://www.omdbapi.com/#examples)

```http
http://www.omdbapi.com/?apikey=[apikey]&t=Sharknado&y=2013
```

```
## {
##     "Title": "Sharknado",
##     "Year": "2013",
##     "Rated": "Not Rated",
##     "Released": "11 Jul 2013",
##     "Runtime": "86 min",
##     "Genre": "Action, Adventure, Comedy",
##     "Director": "Anthony C. Ferrante",
##     "Writer": "Thunder Levin",
##     "Actors": "Ian Ziering, Tara Reid, John Heard",
##     "Plot": "When a freak hurricane swamps Los Angeles, nature's deadliest killer rules sea, land, and air as thousands of sharks terrorize the waterlogged populace.",
##     "Language": "English",
##     "Country": "United States",
##     "Awards": "1 win & 2 nominations",
##     "Poster": "https://m.media-amazon.com/images/M/MV5BODcwZWFiNTEtNDgzMC00ZmE2LWExMzYtNzZhZDgzNDc5NDkyXkEyXkFqcGdeQXVyMTQxNzMzNDI@._V1_SX300.jpg",
##     "Ratings": [
##         {
##             "Source": "Internet Movie Database",
##             "Value": "3.3/10"
##         },
##         {
##             "Source": "Rotten Tomatoes",
##             "Value": "74%"
##         }
##     ],
##     "Metascore": "N/A",
##     "imdbRating": "3.3",
##     "imdbVotes": "50,032",
##     "imdbID": "tt2724064",
##     "Type": "movie",
##     "DVD": "03 Sep 2013",
##     "BoxOffice": "N/A",
##     "Production": "N/A",
##     "Website": "N/A",
##     "Response": "True"
## }
## 
```

---

## `httr::GET()`

```r
sharknado <- GET(url = "http://www.omdbapi.com/?",
    query = list(t = "Sharknado",
                 y = 2013,
                 apikey = getOption("omdb_key"))
)
```

---

## JavaScript Object Notation (JSON)

```
## {
##     "Title": "Sharknado",
##     "Year": "2013",
##     "Rated": "Not Rated",
##     "Released": "11 Jul 2013",
##     "Runtime": "86 min",
##     "Genre": "Action, Adventure, Comedy",
##     "Director": "Anthony C. Ferrante",
##     "Writer": "Thunder Levin",
##     "Actors": "Ian Ziering, Tara Reid, John Heard",
##     "Plot": "When a freak hurricane swamps Los Angeles, nature's deadliest killer rules sea, land, and air as thousands of sharks terrorize the waterlogged populace.",
##     "Language": "English",
##     "Country": "United States",
##     "Awards": "1 win & 2 nominations",
##     "Poster": "https://m.media-amazon.com/images/M/MV5BODcwZWFiNTEtNDgzMC00ZmE2LWExMzYtNzZhZDgzNDc5NDkyXkEyXkFqcGdeQXVyMTQxNzMzNDI@._V1_SX300.jpg",
##     "Ratings": [
##         {
##             "Source": "Internet Movie Database",
##             "Value": "3.3/10"
##         },
##         {
##             "Source": "Rotten Tomatoes",
##             "Value": "74%"
##         }
##     ],
##     "Metascore": "N/A",
##     "imdbRating": "3.3",
##     "imdbVotes": "49,884",
##     "imdbID": "tt2724064",
##     "Type": "movie",
##     "DVD": "03 Sep 2013",
##     "BoxOffice": "N/A",
##     "Production": "N/A",
##     "Website": "N/A",
##     "Response": "True"
## }
## 
```

---

## JSON

```r
sharknado_df <- content(sharknado) %>%
  as_tibble()
sharknado_df
```

```
## # A tibble: 2 × 25
##   Title    Year  Rated Relea…¹ Runtime Genre Direc…² Writer Actors Plot  Langu…³
##   <chr>    <chr> <chr> <chr>   <chr>   <chr> <chr>   <chr>  <chr>  <chr> <chr>  
## 1 Sharkna… 2013  Not … 11 Jul… 86 min  Acti… Anthon… Thund… Ian Z… When… English
## 2 Sharkna… 2013  Not … 11 Jul… 86 min  Acti… Anthon… Thund… Ian Z… When… English
## # … with 14 more variables: Country <chr>, Awards <chr>, Poster <chr>,
## #   Ratings <list>, Metascore <chr>, imdbRating <chr>, imdbVotes <chr>,
## #   imdbID <chr>, Type <chr>, DVD <chr>, BoxOffice <chr>, Production <chr>,
## #   Website <chr>, Response <chr>, and abbreviated variable names ¹Released,
## #   ²Director, ³Language
```

---

## Additional information from `GET()`

```r
sharknado$url
```

```
## [1] "http://www.omdbapi.com/?t=Sharknado&y=2013&apikey=[apikey]"
```

```r
status_code(sharknado)
```

```
## [1] 200
```

---

## HTTP status code

Code | Status
-------|--------|
1xx    | Informational
2xx    | Success
3xx    | Redirection
4xx    | Client error (you did something wrong)
5xx    | Server error (server did something wrong)

> [A more intuitive guide](https://www.flickr.com/photos/girliemac/sets/72157628409467125)

---

## Iteration through a set of movies

```r
omdb_api <- function(title, api_key){
  # send GET request
  response <- GET(url = "http://www.omdbapi.com/?",
    query = list(t = title,
                 apikey = api_key)
  )
  
  # parse response to JSON
  response_df <- content(response) %>%
    as_tibble()
  
  # print a message to track progress
  message(glue::glue("Scraping {title}..."))
  
  return(response_df)
}
```

---

## Iteration through a set of movies

```r
sharknados <- c("Sharknado", "Sharknado 2", "Sharknado 3",
                "Sharknado 4", "Sharknado 5")
```

```r
# modify function to delay by one second
omdb_api_slow <- purrr::slowly(f = omdb_api, rate = rate_delay(1))

# iterate over all the films
sharknados_df <- map_dfr(.x = sharknados, .f = omdb_api_slow, api_key = getOption("omdb_key"))
```

```
## Scraping Sharknado...
```

```
## Scraping Sharknado 2...
```

```
## Scraping Sharknado 3...
```

```
## Scraping Sharknado 4...
```

```
## Scraping Sharknado 5...
```

---

## Iteration through a set of movies

```r
sharknados_df
```

```
## # A tibble: 10 × 25
##    Title   Year  Rated Relea…¹ Runtime Genre Direc…² Writer Actors Plot  Langu…³
##    <chr>   <chr> <chr> <chr>   <chr>   <chr> <chr>   <chr>  <chr>  <chr> <chr>  
##  1 Sharkn… 2013  Not … 11 Jul… 86 min  Acti… Anthon… Thund… Ian Z… When… English
##  2 Sharkn… 2013  Not … 11 Jul… 86 min  Acti… Anthon… Thund… Ian Z… When… English
##  3 Sharkn… 2014  TV-14 30 Jul… 95 min  Acti… Anthon… Thund… Ian Z… Fin … English
##  4 Sharkn… 2014  TV-14 30 Jul… 95 min  Acti… Anthon… Thund… Ian Z… Fin … English
##  5 Sharkn… 2015  TV-14 22 Jul… 93 min  Acti… Anthon… Thund… Ian Z… A mo… English
##  6 Sharkn… 2015  TV-14 22 Jul… 93 min  Acti… Anthon… Thund… Ian Z… A mo… English
##  7 Sharkn… 2016  TV-14 31 Jul… 95 min  Acti… Anthon… Thund… Ian Z… Fin,… English
##  8 Sharkn… 2016  TV-14 31 Jul… 95 min  Acti… Anthon… Thund… Ian Z… Fin,… English
##  9 Sharkn… 2017  TV-14 06 Aug… 93 min  Acti… Anthon… Thund… Ian Z… With… English
## 10 Sharkn… 2017  TV-14 06 Aug… 93 min  Acti… Anthon… Thund… Ian Z… With… English
## # … with 14 more variables: Country <chr>, Awards <chr>, Poster <chr>,
## #   Ratings <list>, Metascore <chr>, imdbRating <chr>, imdbVotes <chr>,
## #   imdbID <chr>, Type <chr>, DVD <chr>, BoxOffice <chr>, Production <chr>,
## #   Website <chr>, Response <chr>, and abbreviated variable names ¹Released,
## #   ²Director, ³Language
```

---

## Messy API responses

```r
content(sharknado) %>%
  as_tibble()
```

---

## Whoops

```
## List of 25
##  $ Title     : chr "Sharknado"
##  $ Year      : chr "2013"
##  $ Rated     : chr "Not Rated"
##  $ Released  : chr "11 Jul 2013"
##  $ Runtime   : chr "86 min"
##  $ Genre     : chr "Action, Adventure, Comedy"
##  $ Director  : chr "Anthony C. Ferrante"
##  $ Writer    : chr "Thunder Levin"
##  $ Actors    : chr "Ian Ziering, Tara Reid, John Heard"
##  $ Plot      : chr "When a freak hurricane swamps Los Angeles, nature's deadliest killer rules sea, land, and air as thousands of s"| __truncated__
##  $ Language  : chr "English"
##  $ Country   : chr "United States"
##  $ Awards    : chr "1 win & 2 nominations"
##  $ Poster    : chr "https://m.media-amazon.com/images/M/MV5BODcwZWFiNTEtNDgzMC00ZmE2LWExMzYtNzZhZDgzNDc5NDkyXkEyXkFqcGdeQXVyMTQxNzM"| __truncated__
##  $ Ratings   :List of 2
##   ..$ :List of 2
##   .. ..$ Source: chr "Internet Movie Database"
##   .. ..$ Value : chr "3.3/10"
##   ..$ :List of 2
##   .. ..$ Source: chr "Rotten Tomatoes"
##   .. ..$ Value : chr "74%"
##  $ Metascore : chr "N/A"
##  $ imdbRating: chr "3.3"
##  $ imdbVotes : chr "49,884"
##  $ imdbID    : chr "tt2724064"
##  $ Type      : chr "movie"
##  $ DVD       : chr "03 Sep 2013"
##  $ BoxOffice : chr "N/A"
##  $ Production: chr "N/A"
##  $ Website   : chr "N/A"
##  $ Response  : chr "True"
```

---

# Rectangling messy data

---

## Rectangling and `tidyr`

.task[
Art and craft of taking a deeply nested list and taming it into a tidy data set of rows and columns
]

* `unnest_longer()` - each row contains multiple observations
* `unnest_wider()` - each row contains a single observation
* `unnest_auto()` - make an educated guess
* `hoist()` - extract a specific element
  
---

## `unnest_wider()` and `hoist()`

```r
str(gh_users, list.len = 3)
```

```
## List of 6
##  $ :List of 30
##   ..$ login              : chr "gaborcsardi"
##   ..$ id                 : int 660288
##   ..$ avatar_url         : chr "https://avatars.githubusercontent.com/u/660288?v=3"
##   .. [list output truncated]
##  $ :List of 30
##   ..$ login              : chr "jennybc"
##   ..$ id                 : int 599454
##   ..$ avatar_url         : chr "https://avatars.githubusercontent.com/u/599454?v=3"
##   .. [list output truncated]
##  $ :List of 30
##   ..$ login              : chr "jtleek"
##   ..$ id                 : int 1571674
##   ..$ avatar_url         : chr "https://avatars.githubusercontent.com/u/1571674?v=3"
##   .. [list output truncated]
##   [list output truncated]
```

---

## `unnest_wider()` and `hoist()`

```r
(users <- tibble(user = gh_users))
```

```
## # A tibble: 6 × 1
##   user             
##   <list>           
## 1 <named list [30]>
## 2 <named list [30]>
## 3 <named list [30]>
## 4 <named list [30]>
## 5 <named list [30]>
## 6 <named list [30]>
```

```r
names(users$user[[1]])
```

```
##  [1] "login"               "id"                  "avatar_url"         
##  [4] "gravatar_id"         "url"                 "html_url"           
##  [7] "followers_url"       "following_url"       "gists_url"          
## [10] "starred_url"         "subscriptions_url"   "organizations_url"  
## [13] "repos_url"           "events_url"          "received_events_url"
## [16] "type"                "site_admin"          "name"               
## [19] "company"             "blog"                "location"           
## [22] "email"               "hireable"            "bio"                
## [25] "public_repos"        "public_gists"        "followers"          
## [28] "following"           "created_at"          "updated_at"
```

---

## `unnest_wider()`

```r
users %>%
  unnest_wider(col = user)
```

```
## # A tibble: 6 × 30
##   login         id avata…¹ grava…² url   html_…³ follo…⁴ follo…⁵ gists…⁶ starr…⁷
##   <chr>      <int> <chr>   <chr>   <chr> <chr>   <chr>   <chr>   <chr>   <chr>  
## 1 gaborcsa… 6.60e5 https:… ""      http… https:… https:… https:… https:… https:…
## 2 jennybc   5.99e5 https:… ""      http… https:… https:… https:… https:… https:…
## 3 jtleek    1.57e6 https:… ""      http… https:… https:… https:… https:… https:…
## 4 juliasil… 1.25e7 https:… ""      http… https:… https:… https:… https:… https:…
## 5 leeper    3.51e6 https:… ""      http… https:… https:… https:… https:… https:…
## 6 masalmon  8.36e6 https:… ""      http… https:… https:… https:… https:… https:…
## # … with 20 more variables: subscriptions_url <chr>, organizations_url <chr>,
## #   repos_url <chr>, events_url <chr>, received_events_url <chr>, type <chr>,
## #   site_admin <lgl>, name <chr>, company <chr>, blog <chr>, location <chr>,
## #   email <chr>, hireable <lgl>, bio <chr>, public_repos <int>,
## #   public_gists <int>, followers <int>, following <int>, created_at <chr>,
## #   updated_at <chr>, and abbreviated variable names ¹avatar_url, ²gravatar_id,
## #   ³html_url, ⁴followers_url, ⁵following_url, ⁶gists_url, ⁷starred_url
```

---

## `hoist()`

```r
users %>%
  hoist(
    .col = user,
    followers = "followers",
    login = "login",
    url = "html_url"
  )
```

```
## # A tibble: 6 × 4
##   followers login       url                            user             
##       <int> <chr>       <chr>                          <list>           
## 1       303 gaborcsardi https://github.com/gaborcsardi <named list [27]>
## 2       780 jennybc     https://github.com/jennybc     <named list [27]>
## 3      3958 jtleek      https://github.com/jtleek      <named list [27]>
## 4       115 juliasilge  https://github.com/juliasilge  <named list [27]>
## 5       213 leeper      https://github.com/leeper      <named list [27]>
## 6        34 masalmon    https://github.com/masalmon    <named list [27]>
```

---

## `gh_repos` and nested list structures

```r
(repos <- tibble(repo = gh_repos))
```

```
## # A tibble: 6 × 1
##   repo       
##   <list>     
## 1 <list [30]>
## 2 <list [30]>
## 3 <list [30]>
## 4 <list [26]>
## 5 <list [30]>
## 6 <list [30]>
```

---

## `unnest_longer()`

```r
repos <- repos %>%
  unnest_longer(col = repo)
repos
```

```
## # A tibble: 176 × 1
##    repo             
##    <list>           
##  1 <named list [68]>
##  2 <named list [68]>
##  3 <named list [68]>
##  4 <named list [68]>
##  5 <named list [68]>
##  6 <named list [68]>
##  7 <named list [68]>
##  8 <named list [68]>
##  9 <named list [68]>
## 10 <named list [68]>
## # … with 166 more rows
```

---

## `unnest_longer()`

```r
repos %>%
  hoist(
    .col = repo,
    login = c("owner", "login"),
    name = "name",
    homepage = "homepage",
    watchers = "watchers_count"
  )
```

```
## # A tibble: 176 × 5
##    login       name        homepage watchers repo             
##    <chr>       <chr>       <chr>       <int> <list>           
##  1 gaborcsardi after       <NA>            5 <named list [65]>
##  2 gaborcsardi argufy      <NA>           19 <named list [65]>
##  3 gaborcsardi ask         <NA>            5 <named list [65]>
##  4 gaborcsardi baseimports <NA>            0 <named list [65]>
##  5 gaborcsardi citest      <NA>            0 <named list [65]>
##  6 gaborcsardi clisymbols  ""             18 <named list [65]>
##  7 gaborcsardi cmaker      <NA>            0 <named list [65]>
##  8 gaborcsardi cmark       <NA>            0 <named list [65]>
##  9 gaborcsardi conditions  <NA>            0 <named list [65]>
## 10 gaborcsardi crayon      <NA>           52 <named list [65]>
## # … with 166 more rows
```

---

```r
*tibble(repo = gh_repos)
```
]
 
.panel2-gh-repos-auto-auto[

```
## # A tibble: 6 × 1
##   repo       
##   <list>     
## 1 <list [30]>
## 2 <list [30]>
## 3 <list [30]>
## 4 <list [26]>
## 5 <list [30]>
## 6 <list [30]>
```
]

---
count: false

```r
tibble(repo = gh_repos) %>%
* unnest_auto(col = repo)
```
]
 
.panel2-gh-repos-auto-auto[

---
count: false

```r
tibble(repo = gh_repos) %>%
  unnest_auto(col = repo) %>%
* unnest_auto(col = repo)
```
]
 
.panel2-gh-repos-auto-auto[

```
## # A tibble: 176 × 68
##         id name  full_name owner        private html_url description fork  url  
##      <int> <chr> <chr>     <list>       <lgl>   <chr>    <chr>       <lgl> <chr>
##  1  6.12e7 after gaborcsa… <named list> FALSE   https:/… Run Code i… FALSE http…
##  2  4.05e7 argu… gaborcsa… <named list> FALSE   https:/… Declarativ… FALSE http…
##  3  3.64e7 ask   gaborcsa… <named list> FALSE   https:/… Friendly C… FALSE http…
##  4  3.49e7 base… gaborcsa… <named list> FALSE   https:/… Do we get … FALSE http…
##  5  6.16e7 cite… gaborcsa… <named list> FALSE   https:/… Test R pac… TRUE  http…
##  6  3.39e7 clis… gaborcsa… <named list> FALSE   https:/… Unicode sy… FALSE http…
##  7  3.72e7 cmak… gaborcsa… <named list> FALSE   https:/… port of cm… TRUE  http…
##  8  6.80e7 cmark gaborcsa… <named list> FALSE   https:/… CommonMark… TRUE  http…
##  9  6.32e7 cond… gaborcsa… <named list> FALSE   https:/… <NA>        TRUE  http…
## 10  2.43e7 cray… gaborcsa… <named list> FALSE   https:/… R package … FALSE http…
## # … with 166 more rows, and 59 more variables: forks_url <chr>, keys_url <chr>,
## #   collaborators_url <chr>, teams_url <chr>, hooks_url <chr>,
## #   issue_events_url <chr>, events_url <chr>, assignees_url <chr>,
## #   branches_url <chr>, tags_url <chr>, blobs_url <chr>, git_tags_url <chr>,
## #   git_refs_url <chr>, trees_url <chr>, statuses_url <chr>,
## #   languages_url <chr>, stargazers_url <chr>, contributors_url <chr>,
## #   subscribers_url <chr>, subscription_url <chr>, commits_url <chr>, …
```
]

---

## ASOIAF characters

```r
chars <- tibble(char = got_chars)
chars
```

```
## # A tibble: 30 × 1
##    char             
##    <list>           
##  1 <named list [18]>
##  2 <named list [18]>
##  3 <named list [18]>
##  4 <named list [18]>
##  5 <named list [18]>
##  6 <named list [18]>
##  7 <named list [18]>
##  8 <named list [18]>
##  9 <named list [18]>
## 10 <named list [18]>
## # … with 20 more rows
```

---

## ASOIAF characters

```r
chars2 <- chars %>%
  unnest_wider(col = char)
chars2
```

```
## # A tibble: 30 × 18
##    url           id name  gender culture born  died  alive titles aliases father
##    <chr>      <int> <chr> <chr>  <chr>   <chr> <chr> <lgl> <list> <list>  <chr> 
##  1 https://w…  1022 Theo… Male   "Ironb… "In … ""    TRUE  <chr>  <chr>   ""    
##  2 https://w…  1052 Tyri… Male   ""      "In … ""    TRUE  <chr>  <chr>   ""    
##  3 https://w…  1074 Vict… Male   "Ironb… "In … ""    TRUE  <chr>  <chr>   ""    
##  4 https://w…  1109 Will  Male   ""      ""    "In … FALSE <chr>  <chr>   ""    
##  5 https://w…  1166 Areo… Male   "Norvo… "In … ""    TRUE  <chr>  <chr>   ""    
##  6 https://w…  1267 Chett Male   ""      "At … "In … FALSE <chr>  <chr>   ""    
##  7 https://w…  1295 Cres… Male   ""      "In … "In … FALSE <chr>  <chr>   ""    
##  8 https://w…   130 Aria… Female "Dorni… "In … ""    TRUE  <chr>  <chr>   ""    
##  9 https://w…  1303 Daen… Female "Valyr… "In … ""    TRUE  <chr>  <chr>   ""    
## 10 https://w…  1319 Davo… Male   "Weste… "In … ""    TRUE  <chr>  <chr>   ""    
## # … with 20 more rows, and 7 more variables: mother <chr>, spouse <chr>,
## #   allegiances <list>, books <list>, povBooks <list>, tvSeries <list>,
## #   playedBy <list>
```

---

## Nested list objects

```r
chars2 %>%
  select(where(is.list))
```

```
## # A tibble: 30 × 7
##    titles    aliases    allegiances books     povBooks  tvSeries  playedBy 
##    <list>    <list>     <list>      <list>    <list>    <list>    <list>   
##  1 <chr [3]> <chr [4]>  <chr [1]>   <chr [3]> <chr [2]> <chr [6]> <chr [1]>
##  2 <chr [2]> <chr [11]> <chr [1]>   <chr [2]> <chr [4]> <chr [6]> <chr [1]>
##  3 <chr [2]> <chr [1]>  <chr [1]>   <chr [3]> <chr [2]> <chr [1]> <chr [1]>
##  4 <chr [1]> <chr [1]>  <NULL>      <chr [1]> <chr [1]> <chr [1]> <chr [1]>
##  5 <chr [1]> <chr [1]>  <chr [1]>   <chr [3]> <chr [2]> <chr [2]> <chr [1]>
##  6 <chr [1]> <chr [1]>  <NULL>      <chr [2]> <chr [1]> <chr [1]> <chr [1]>
##  7 <chr [1]> <chr [1]>  <NULL>      <chr [2]> <chr [1]> <chr [1]> <chr [1]>
##  8 <chr [1]> <chr [1]>  <chr [1]>   <chr [4]> <chr [1]> <chr [1]> <chr [1]>
##  9 <chr [5]> <chr [11]> <chr [1]>   <chr [1]> <chr [4]> <chr [6]> <chr [1]>
## 10 <chr [4]> <chr [5]>  <chr [2]>   <chr [1]> <chr [3]> <chr [5]> <chr [1]>
## # … with 20 more rows
```

---

## Choose your own adventure

---

# Every appearance per book/season

---

```r
*select(
* .data = chars2,
* name, books, tvSeries
*) 
```
]
 
.panel2-got-appearances-auto[

```
## # A tibble: 30 × 3
##    name               books     tvSeries 
##    <chr>              <list>    <list>   
##  1 Theon Greyjoy      <chr [3]> <chr [6]>
##  2 Tyrion Lannister   <chr [2]> <chr [6]>
##  3 Victarion Greyjoy  <chr [3]> <chr [1]>
##  4 Will               <chr [1]> <chr [1]>
##  5 Areo Hotah         <chr [3]> <chr [2]>
##  6 Chett              <chr [2]> <chr [1]>
##  7 Cressen            <chr [2]> <chr [1]>
##  8 Arianne Martell    <chr [4]> <chr [1]>
##  9 Daenerys Targaryen <chr [1]> <chr [6]>
## 10 Davos Seaworth     <chr [1]> <chr [5]>
## # … with 20 more rows
```
]

---
count: false
 
## Every appearance per book/season
.panel1-got-appearances-auto[

```r
select(
  .data = chars2,
  name, books, tvSeries
) %>%
* pivot_longer(
*   cols = c(books, tvSeries),
*   names_to = "media",
*   values_to = "value"
* )
```
]
 
.panel2-got-appearances-auto[

```
## # A tibble: 60 × 3
##    name              media    value    
##    <chr>             <chr>    <list>   
##  1 Theon Greyjoy     books    <chr [3]>
##  2 Theon Greyjoy     tvSeries <chr [6]>
##  3 Tyrion Lannister  books    <chr [2]>
##  4 Tyrion Lannister  tvSeries <chr [6]>
##  5 Victarion Greyjoy books    <chr [3]>
##  6 Victarion Greyjoy tvSeries <chr [1]>
##  7 Will              books    <chr [1]>
##  8 Will              tvSeries <chr [1]>
##  9 Areo Hotah        books    <chr [3]>
## 10 Areo Hotah        tvSeries <chr [2]>
## # … with 50 more rows
```
]

---
count: false
 
## Every appearance per book/season
.panel1-got-appearances-auto[

```r
select(
  .data = chars2,
  name, books, tvSeries
) %>%
  pivot_longer(
    cols = c(books, tvSeries),
    names_to = "media",
    values_to = "value"
  ) %>%
* unnest_longer(col = value)
```
]
 
.panel2-got-appearances-auto[

```
## # A tibble: 180 × 3
##    name             media    value            
##    <chr>            <chr>    <chr>            
##  1 Theon Greyjoy    books    A Game of Thrones
##  2 Theon Greyjoy    books    A Storm of Swords
##  3 Theon Greyjoy    books    A Feast for Crows
##  4 Theon Greyjoy    tvSeries Season 1         
##  5 Theon Greyjoy    tvSeries Season 2         
##  6 Theon Greyjoy    tvSeries Season 3         
##  7 Theon Greyjoy    tvSeries Season 4         
##  8 Theon Greyjoy    tvSeries Season 5         
##  9 Theon Greyjoy    tvSeries Season 6         
## 10 Tyrion Lannister books    A Feast for Crows
## # … with 170 more rows
```
]

---

# Match character's title to their name

---

count: false
 
## Match character's title to their name
.panel1-got-title-name-auto[

```r
*select(
* .data = chars2,
* name,
* title = titles
*) 
```
]
 
.panel2-got-title-name-auto[

```
## # A tibble: 30 × 2
##    name               title    
##    <chr>              <list>   
##  1 Theon Greyjoy      <chr [3]>
##  2 Tyrion Lannister   <chr [2]>
##  3 Victarion Greyjoy  <chr [2]>
##  4 Will               <chr [1]>
##  5 Areo Hotah         <chr [1]>
##  6 Chett              <chr [1]>
##  7 Cressen            <chr [1]>
##  8 Arianne Martell    <chr [1]>
##  9 Daenerys Targaryen <chr [5]>
## 10 Davos Seaworth     <chr [4]>
## # … with 20 more rows
```
]

---
count: false
 
## Match character's title to their name
.panel1-got-title-name-auto[

```r
select(
  .data = chars2,
  name,
  title = titles
) %>%
* unnest_longer(col = title)
```
]
 
.panel2-got-title-name-auto[

```
## # A tibble: 60 × 2
##    name              title                                                 
##    <chr>             <chr>                                                 
##  1 Theon Greyjoy     "Prince of Winterfell"                                
##  2 Theon Greyjoy     "Captain of Sea Bitch"                                
##  3 Theon Greyjoy     "Lord of the Iron Islands (by law of the green lands)"
##  4 Tyrion Lannister  "Acting Hand of the King (former)"                    
##  5 Tyrion Lannister  "Master of Coin (former)"                             
##  6 Victarion Greyjoy "Lord Captain of the Iron Fleet"                      
##  7 Victarion Greyjoy "Master of the Iron Victory"                          
##  8 Will              ""                                                    
##  9 Areo Hotah        "Captain of the Guard at Sunspear"                    
## 10 Chett             ""                                                    
## # … with 50 more rows
```
]

---

# May the force be with you