class: center, middle, inverse, title-slide # tidyr & purrr ### Colin Rundel ### 2018-09-19 --- exclude: true --- class: middle count: false # tidyr --- ## Tidy data .footnote[ From R4DS - [tidy data](r4ds.had.co.nz/tidy-data.html) ] <img src="imgs/tidy.png" width="100%" /> --- ## Tidy? ```r tb = readr::read_csv(paste0("https://github.com/tidyverse/", "tidyr/raw/master/vignettes/tb.csv")) tb ``` ``` ## # A tibble: 5,769 x 22 ## iso2 year m04 m514 m014 m1524 m2534 m3544 m4554 m5564 m65 mu f04 ## <chr> <int> <int> <int> <int> <int> <int> <int> <int> <int> <int> <int> <int> ## 1 AD 1989 NA NA NA NA NA NA NA NA NA NA NA ## 2 AD 1990 NA NA NA NA NA NA NA NA NA NA NA ## 3 AD 1991 NA NA NA NA NA NA NA NA NA NA NA ## 4 AD 1992 NA NA NA NA NA NA NA NA NA NA NA ## 5 AD 1993 NA NA NA NA NA NA NA NA NA NA NA ## 6 AD 1994 NA NA NA NA NA NA NA NA NA NA NA ## 7 AD 1996 NA NA 0 0 0 4 1 0 0 NA NA ## 8 AD 1997 NA NA 0 0 1 2 2 1 6 NA NA ## 9 AD 1998 NA NA 0 0 0 1 0 0 0 NA NA ## 10 AD 1999 NA NA 0 0 0 1 1 0 0 NA NA ## # ... with 5,759 more rows, and 9 more variables: f514 <int>, f014 <int>, ## # f1524 <int>, f2534 <int>, f3544 <int>, f4554 <int>, f5564 <int>, f65 <int>, ## # fu <int> ``` --- ## Codebook | Column | Meaning | |--------|:--------------------| | `iso2` | 2 digit iso country code | `year` | year | `m04` | Males, 0 - 4 | `m514` | Males, 5 - 14 | `m014` | Males, 0 - 14 | ... | ... | `m65` | Males, 65+ | `mu` | Males, unknown | ... | ... --- ## Fixing things with tidyr .footnote[ From RStudio's [Data Wrangling Cheat Sheet](https://www.rstudio.com/wp-content/uploads/2015/02/data-wrangling-cheatsheet.pdf) ] .center[ <img src="imgs/hex-tidyr.png" width="15%" /> ] <img src="imgs/tidyr.png" width="100%" /> --- ## Moving columns to rows .pull-left[ ```r tb %>% gather( group, counts, -iso2, -year ) ``` ``` ## # A tibble: 115,380 x 4 ## iso2 year group counts ## <chr> <int> <chr> <int> ## 1 AD 1989 m04 NA ## 2 AD 1990 m04 NA ## 3 AD 1991 m04 NA ## 4 AD 1992 m04 NA ## 5 AD 1993 m04 NA ## 6 AD 1994 m04 NA ## 7 AD 1996 m04 NA ## 8 AD 1997 m04 NA ## 9 AD 1998 m04 NA ## 10 AD 1999 m04 NA ## # ... with 115,370 more rows ``` ] .pull-right[ ```r tb %>% gather( group, counts, -iso2, -year, na.rm = TRUE ) ``` ``` ## # A tibble: 35,750 x 4 ## iso2 year group counts ## * <chr> <int> <chr> <int> ## 1 AD 2005 m04 0 ## 2 AD 2006 m04 0 ## 3 AD 2008 m04 0 ## 4 AE 2006 m04 0 ## 5 AE 2007 m04 0 ## 6 AE 2008 m04 0 ## 7 AG 2007 m04 0 ## 8 AL 2005 m04 0 ## 9 AL 2006 m04 1 ## 10 AL 2007 m04 0 ## # ... with 35,740 more rows ``` ] --- ## Moving columns to rows ```r tb %>% gather(group, counts, -iso2, -year, na.rm = TRUE) %>% separate(group, into = c("gender","age"), 1) ``` ``` ## # A tibble: 35,750 x 5 ## iso2 year gender age counts ## * <chr> <int> <chr> <chr> <int> ## 1 AD 2005 m 04 0 ## 2 AD 2006 m 04 0 ## 3 AD 2008 m 04 0 ## 4 AE 2006 m 04 0 ## 5 AE 2007 m 04 0 ## 6 AE 2008 m 04 0 ## 7 AG 2007 m 04 0 ## 8 AL 2005 m 04 0 ## 9 AL 2006 m 04 1 ## 10 AL 2007 m 04 0 ## # ... with 35,740 more rows ``` --- ## Fixing ages ```r (tb = tb %>% gather(group, counts, -iso2, -year, na.rm=TRUE) %>% separate(group, into = c("gender","age"), 1) %>% mutate( age = case_when( age == "04" ~ "0-4", age == "514" ~ "5-14", age == "014" ~ "0-14", age == "1524" ~ "15-24", age == "2534" ~ "25-34", age == "3544" ~ "35-44", age == "4554" ~ "45-54", age == "5564" ~ "55-64", age == "65" ~ "65+", age == "u" ~ NA_character_ ) ) ) ``` ``` ## # A tibble: 35,750 x 5 ## iso2 year gender age counts ## <chr> <int> <chr> <chr> <int> ## 1 AD 2005 m 0-4 0 ## 2 AD 2006 m 0-4 0 ## 3 AD 2008 m 0-4 0 ## 4 AE 2006 m 0-4 0 ## 5 AE 2007 m 0-4 0 ## 6 AE 2008 m 0-4 0 ## 7 AG 2007 m 0-4 0 ## 8 AL 2005 m 0-4 0 ## 9 AL 2006 m 0-4 1 ## 10 AL 2007 m 0-4 0 ## # ... with 35,740 more rows ``` --- ## Moving rows to columns ```r tb %>% spread(gender, counts) %>% mutate(total = m + f) ``` ``` ## # A tibble: 18,029 x 6 ## iso2 year age f m total ## <chr> <int> <chr> <int> <int> <int> ## 1 AD 1996 0-14 0 0 0 ## 2 AD 1996 15-24 1 0 1 ## 3 AD 1996 25-34 1 0 1 ## 4 AD 1996 35-44 0 4 4 ## 5 AD 1996 45-54 0 1 1 ## 6 AD 1996 55-64 1 0 1 ## 7 AD 1996 65+ 0 0 0 ## 8 AD 1997 0-14 0 0 0 ## 9 AD 1997 15-24 1 0 1 ## 10 AD 1997 25-34 2 1 3 ## # ... with 18,019 more rows ``` --- ## Example 1 The `line` data set is an example included in the `coda` package containing mcmc posterior samples from a linear regression model. Use `tidyr` to adjust the data frame such that you can use `ggplot2` to create trace plots or `dplyr` to calculate summary statistics. ```r library(coda) data(line,package = "coda") d = as_data_frame(line[["line1"]]) d ``` ``` ## # A tibble: 200 x 3 ## alpha beta sigma ## * <dbl> <dbl> <dbl> ## 1 7.17 -1.57 11.2 ## 2 2.95 1.50 4.89 ## 3 3.67 0.628 1.40 ## 4 3.32 1.18 0.663 ## 5 3.71 0.490 1.36 ## 6 3.58 0.207 1.04 ## 7 2.70 0.883 1.29 ## 8 2.96 1.09 0.459 ## 9 3.53 1.07 0.634 ## 10 2.09 1.48 0.913 ## # ... with 190 more rows ``` --- class: middle count: false # Functional Programming --- ## Functional Programming <br/> .medium[ * First order functions * Pure functions * Anonymous functions * Vectorized functions * *Closures* * *Recursion* ] --- class: middle count: false # Apply functions --- ## Apply functions The apply functions are a collection of tools for functional programming in R, they are variations of the `map` function found in many other languages ```r ??apply --- ## ## Help files with alias or concept or title matching ‘apply’ using fuzzy ## matching: ## ## base::apply Apply Functions Over Array Margins ## base::.subset Internal Objects in Package 'base' ## base::by Apply a Function to a Data Frame Split by Factors ## base::eapply Apply a Function Over Values in an Environment ## base::lapply Apply a Function over a List or Vector ## base::mapply Apply a Function to Multiple List or Vector Arguments ## base::rapply Recursively Apply a Function to a List ## base::tapply Apply a Function Over a Ragged Array ``` --- ## lapply Usage: `lapply(X, FUN, ...)` `lapply` returns a list of the same length as `X`, each element of which is the result of applying `FUN` to the corresponding element of `X`. <br/> .pull-left[ ```r lapply(1:8, sqrt) %>% str() ``` ``` ## List of 8 ## $ : num 1 ## $ : num 1.41 ## $ : num 1.73 ## $ : num 2 ## $ : num 2.24 ## $ : num 2.45 ## $ : num 2.65 ## $ : num 2.83 ``` ] .pull-right[ ```r lapply(1:8, function(x) (x+1)^2) %>% str() ``` ``` ## List of 8 ## $ : num 4 ## $ : num 9 ## $ : num 16 ## $ : num 25 ## $ : num 36 ## $ : num 49 ## $ : num 64 ## $ : num 81 ``` ] --- ```r lapply(1:8, function(x, pow) x^pow, pow=3) %>% str() ``` ``` ## List of 8 ## $ : num 1 ## $ : num 8 ## $ : num 27 ## $ : num 64 ## $ : num 125 ## $ : num 216 ## $ : num 343 ## $ : num 512 ``` ```r lapply(1:8, function(x, pow) x^pow, x=2) %>% str() ``` ``` ## List of 8 ## $ : num 2 ## $ : num 4 ## $ : num 8 ## $ : num 16 ## $ : num 32 ## $ : num 64 ## $ : num 128 ## $ : num 256 ``` --- ## sapply Usage: `sapply(X, FUN, ..., simplify = TRUE, USE.NAMES = TRUE)` `sapply` is a *user-friendly* version and wrapper of `lapply`, it is a *simplifying* version of lapply. Whenever possible it will return a vector, matrix, or an array. <br/> ```r sapply(1:8, sqrt) ``` ``` ## [1] 1.000000 1.414214 1.732051 2.000000 2.236068 2.449490 2.645751 2.828427 ``` ```r sapply(1:8, function(x) (x+1)^2) ``` ``` ## [1] 4 9 16 25 36 49 64 81 ``` --- ```r sapply(1:8, function(x) c(x, x^2, x^3, x^4)) ``` ``` ## [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] ## [1,] 1 2 3 4 5 6 7 8 ## [2,] 1 4 9 16 25 36 49 64 ## [3,] 1 8 27 64 125 216 343 512 ## [4,] 1 16 81 256 625 1296 2401 4096 ``` ```r sapply(1:8, function(x) list(x, x^2, x^3, x^4)) ``` ``` ## [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] ## [1,] 1 2 3 4 5 6 7 8 ## [2,] 1 4 9 16 25 36 49 64 ## [3,] 1 8 27 64 125 216 343 512 ## [4,] 1 16 81 256 625 1296 2401 4096 ``` --- ```r sapply(2:6, seq) ``` ``` ## [[1]] ## [1] 1 2 ## ## [[2]] ## [1] 1 2 3 ## ## [[3]] ## [1] 1 2 3 4 ## ## [[4]] ## [1] 1 2 3 4 5 ## ## [[5]] ## [1] 1 2 3 4 5 6 ``` --- ## [ls]apply and data frames We can use these functions with data frames, the key is to remember that a data frame is just a fancy list. ```r df = data.frame(a = 1:6, b = letters[1:6], c = c(TRUE,FALSE)) lapply(df, class) %>% str() ``` ``` ## List of 3 ## $ a: chr "integer" ## $ b: chr "factor" ## $ c: chr "logical" ``` ```r sapply(df, class) ``` ``` ## a b c ## "integer" "factor" "logical" ``` --- ## other less common applies * `apply(X, MARGIN, FUN, ...)` - applies a function over the rows or columns of a data frame, matrix or array * `vapply(X, FUN, FUN.VALUE, ..., USE.NAMES = TRUE)` - is similar to `sapply`, but has a enforced return type and size * `mapply(FUN, ..., MoreArgs = NULL, SIMPLIFY = TRUE, USE.NAMES = TRUE)` - like `sapply` but will iterate over multiple vectors at the same time. * `rapply(object, f, classes = "ANY", deflt = NULL, how = c("unlist", "replace", "list"), ...)` - a recursive version of `lapply`, behavior depends largely on the `how` argument * `eapply(env, FUN, ..., all.names = FALSE, USE.NAMES = TRUE)` - apply a function over an environment. --- ## Example 2 Using the `sw_people` data set in the `repurrrsive` package, extract the name of all of the characters using: * a for loop * an apply function --- class: middle count: false # purrr --- ## purrr .center[ <img src="imgs/purrr.png" width="231" /> ] A tidyverse package which improves the functional programming tools in R, it focuses on *pure* and *type stable* functions. --- ## Map functions Basic functions for looping over an object and returning a value (of a specific type) - replacement for `lapply`/`sapply`/`vapply`. * `map()` - returns a list. * `map_lgl()` - returns a logical vector. * `map_int()` - returns a integer vector. * `map_dbl()` - returns a double vector. * `map_chr()` - returns a character vector. * `map_df()` / `map_dfr()` - returns a data frame by row binding. * `map_dfc()` - returns a data frame by column binding. * `walk()` - returns nothing, call function exclusively for its side effects --- ## Type Consistency R is a weakly / dynamically typed language which means there is no simple way to define a function which enforces the argument or return types. This flexibility can be useful at times, but often it makes it hard to reason about your code and requires more verbose code to handle edge cases. ```r x = list(rnorm(1e3),rnorm(1e3),rnorm(1e3)) ``` ```r map_dbl(x, mean) ``` ``` ## [1] -0.033007651 -0.014825785 0.003632566 ``` ```r map_chr(x, mean) ``` ``` ## [1] "-0.033008" "-0.014826" "0.003633" ``` ```r map_int(x, mean) ``` ``` ## Error: Can't coerce element 1 from a double to a integer ``` --- ## Shortcut - Anonymous Functions An anonymous function is one that is never given a name (assigned to a variable) ```r sapply(1:5, function(x) x^(x+1)) ``` ``` ## [1] 1 8 81 1024 15625 ``` purrr lets us write anonymous functions using one sided formulas where the first arguments ```r map_dbl(1:5, ~ .^(.+1)) ``` ``` ## [1] 1 8 81 1024 15625 ``` ```r map_dbl(1:5, ~ .x^(.x+1)) ``` ``` ## [1] 1 8 81 1024 15625 ``` ```r map2_dbl(1:5, 1:5, ~ .x^(.y+1)) ``` ``` ## [1] 1 8 81 1024 15625 ``` --- ## Purrr shortcut - Lookups Very often we want to extract only certain (named) values from a list, `purrr` provides a shortcut for this operation when you provide either a character or numeric value instead of a function to apply. ```r x = list(list(a=1L,b=2L,c=list(d=3L,e=4L)), list(a=5L,b=6L,c=list(d=7L,e=8L,f=9L))) ``` -- .pull-left[ ```r map_int(x, "a") ``` ``` ## [1] 1 5 ``` ```r map_dbl(x, c("c","e")) ``` ``` ## [1] 4 8 ``` ```r map_chr(x, list(3,"d")) ``` ``` ## [1] "3" "7" ``` ] -- .pull-right[ ```r map_df(x, 3) ``` ``` ## # A tibble: 2 x 3 ## d e f ## <int> <int> <int> ## 1 3 4 NA ## 2 7 8 9 ``` ```r map_dfc(x, 3) ``` ``` ## # A tibble: 1 x 5 ## d e d1 e1 f ## <int> <int> <int> <int> <int> ## 1 3 4 7 8 9 ``` ] --- ```r x = list(list(a=1L,b=2L,c=list(d=3L,e=4L)), list(a=5L,b=6L,c=list(d=7L,e=8L,f=9L))) ``` ```r map(x, list(3,"f")) ``` ``` ## [[1]] ## NULL ## ## [[2]] ## [1] 9 ``` ```r map_int(x, list(3,"f")) ``` ``` ## Error: Result 1 is not a length 1 atomic vector ``` ```r map_int(x, list(3,"f"), .default=NA) ``` ``` ## [1] NA 9 ``` --- ## Example 3 Using the `sw_people` data set in the `repurrrsive` package, generate a tidy data frame (tibble) containing as many details as possible. ```r library(repurrrsive) ``` .pull-left[ ```r str(sw_people,max.level = 1) ``` ``` ## List of 87 ## $ :List of 16 ## $ :List of 14 ## $ :List of 14 ## $ :List of 15 ## $ :List of 15 ## $ :List of 14 ## $ :List of 14 ## $ :List of 14 ## $ :List of 15 ## $ :List of 16 ## $ :List of 16 ## $ :List of 14 ## $ :List of 16 ## $ :List of 15 ## $ :List of 14 ## $ :List of 14 ## $ :List of 16 ## $ :List of 15 ## $ :List of 14 ## $ :List of 14 ## $ :List of 15 ## $ :List of 14 ## $ :List of 14 ## $ :List of 15 ## $ :List of 14 ## $ :List of 14 ## $ :List of 14 ## $ :List of 15 ## $ :List of 14 ## $ :List of 15 ## $ :List of 15 ## $ :List of 14 ## $ :List of 14 ## $ :List of 14 ## $ :List of 14 ## $ :List of 14 ## $ :List of 14 ## $ :List of 14 ## $ :List of 14 ## $ :List of 13 ## $ :List of 14 ## $ :List of 16 ## $ :List of 14 ## $ :List of 14 ## $ :List of 14 ## $ :List of 14 ## $ :List of 14 ## $ :List of 14 ## $ :List of 14 ## $ :List of 14 ## $ :List of 14 ## $ :List of 14 ## $ :List of 14 ## $ :List of 14 ## $ :List of 15 ## $ :List of 14 ## $ :List of 15 ## $ :List of 14 ## $ :List of 14 ## $ :List of 14 ## $ :List of 14 ## $ :List of 14 ## $ :List of 14 ## $ :List of 15 ## $ :List of 14 ## $ :List of 14 ## $ :List of 15 ## $ :List of 14 ## $ :List of 14 ## $ :List of 14 ## $ :List of 14 ## $ :List of 14 ## $ :List of 13 ## $ :List of 14 ## $ :List of 14 ## $ :List of 14 ## $ :List of 16 ## $ :List of 14 ## $ :List of 14 ## $ :List of 13 ## $ :List of 14 ## $ :List of 14 ## $ :List of 14 ## $ :List of 15 ## $ :List of 14 ## $ :List of 13 ## $ :List of 15 ``` ] .pull-right[ ```r str(sw_people,max.level = 2) ``` ``` ## List of 87 ## $ :List of 16 ## ..$ name : chr "Luke Skywalker" ## ..$ height : chr "172" ## ..$ mass : chr "77" ## ..$ hair_color: chr "blond" ## ..$ skin_color: chr "fair" ## ..$ eye_color : chr "blue" ## ..$ birth_year: chr "19BBY" ## ..$ gender : chr "male" ## ..$ homeworld : chr "http://swapi.co/api/planets/1/" ## ..$ films : chr [1:5] "http://swapi.co/api/films/6/" "http://swapi.co/api/films/3/" "http://swapi.co/api/films/2/" "http://swapi.co/api/films/1/" ... ## ..$ species : chr "http://swapi.co/api/species/1/" ## ..$ vehicles : chr [1:2] "http://swapi.co/api/vehicles/14/" "http://swapi.co/api/vehicles/30/" ## ..$ starships : chr [1:2] "http://swapi.co/api/starships/12/" "http://swapi.co/api/starships/22/" ## ..$ created : chr "2014-12-09T13:50:51.644000Z" ## ..$ edited : chr "2014-12-20T21:17:56.891000Z" ## ..$ url : chr "http://swapi.co/api/people/1/" ## $ :List of 14 ## ..$ name : chr "C-3PO" ## ..$ height : chr "167" ## ..$ mass : chr "75" ## ..$ hair_color: chr "n/a" ## ..$ skin_color: chr "gold" ## ..$ eye_color : chr "yellow" ## ..$ birth_year: chr "112BBY" ## ..$ gender : chr "n/a" ## ..$ homeworld : chr "http://swapi.co/api/planets/1/" ## ..$ films : chr [1:6] "http://swapi.co/api/films/5/" "http://swapi.co/api/films/4/" "http://swapi.co/api/films/6/" "http://swapi.co/api/films/3/" ... ## ..$ species : chr "http://swapi.co/api/species/2/" ## ..$ created : chr "2014-12-10T15:10:51.357000Z" ## ..$ edited : chr "2014-12-20T21:17:50.309000Z" ## ..$ url : chr "http://swapi.co/api/people/2/" ## $ :List of 14 ## ..$ name : chr "R2-D2" ## ..$ height : chr "96" ## ..$ mass : chr "32" ## ..$ hair_color: chr "n/a" ## ..$ skin_color: chr "white, blue" ## ..$ eye_color : chr "red" ## ..$ birth_year: chr "33BBY" ## ..$ gender : chr "n/a" ## ..$ homeworld : chr "http://swapi.co/api/planets/8/" ## ..$ films : chr [1:7] "http://swapi.co/api/films/5/" "http://swapi.co/api/films/4/" "http://swapi.co/api/films/6/" "http://swapi.co/api/films/3/" ... ## ..$ species : chr "http://swapi.co/api/species/2/" ## ..$ created : chr "2014-12-10T15:11:50.376000Z" ## ..$ edited : chr "2014-12-20T21:17:50.311000Z" ## ..$ url : chr "http://swapi.co/api/people/3/" ## $ :List of 15 ## ..$ name : chr "Darth Vader" ## ..$ height : chr "202" ## ..$ mass : chr "136" ## ..$ hair_color: chr "none" ## ..$ skin_color: chr "white" ## ..$ eye_color : chr "yellow" ## ..$ birth_year: chr "41.9BBY" ## ..$ gender : chr "male" ## ..$ homeworld : chr "http://swapi.co/api/planets/1/" ## ..$ films : chr [1:4] "http://swapi.co/api/films/6/" "http://swapi.co/api/films/3/" "http://swapi.co/api/films/2/" "http://swapi.co/api/films/1/" ## ..$ species : chr "http://swapi.co/api/species/1/" ## ..$ starships : chr "http://swapi.co/api/starships/13/" ## ..$ created : chr "2014-12-10T15:18:20.704000Z" ## ..$ edited : chr "2014-12-20T21:17:50.313000Z" ## ..$ url : chr "http://swapi.co/api/people/4/" ## $ :List of 15 ## ..$ name : chr "Leia Organa" ## ..$ height : chr "150" ## ..$ mass : chr "49" ## ..$ hair_color: chr "brown" ## ..$ skin_color: chr "light" ## ..$ eye_color : chr "brown" ## ..$ birth_year: chr "19BBY" ## ..$ gender : chr "female" ## ..$ homeworld : chr "http://swapi.co/api/planets/2/" ## ..$ films : chr [1:5] "http://swapi.co/api/films/6/" "http://swapi.co/api/films/3/" "http://swapi.co/api/films/2/" "http://swapi.co/api/films/1/" ... ## ..$ species : chr "http://swapi.co/api/species/1/" ## ..$ vehicles : chr "http://swapi.co/api/vehicles/30/" ## ..$ created : chr "2014-12-10T15:20:09.791000Z" ## ..$ edited : chr "2014-12-20T21:17:50.315000Z" ## ..$ url : chr "http://swapi.co/api/people/5/" ## $ :List of 14 ## ..$ name : chr "Owen Lars" ## ..$ height : chr "178" ## ..$ mass : chr "120" ## ..$ hair_color: chr "brown, grey" ## ..$ skin_color: chr "light" ## ..$ eye_color : chr "blue" ## ..$ birth_year: chr "52BBY" ## ..$ gender : chr "male" ## ..$ homeworld : chr "http://swapi.co/api/planets/1/" ## ..$ films : chr [1:3] "http://swapi.co/api/films/5/" "http://swapi.co/api/films/6/" "http://swapi.co/api/films/1/" ## ..$ species : chr "http://swapi.co/api/species/1/" ## ..$ created : chr "2014-12-10T15:52:14.024000Z" ## ..$ edited : chr "2014-12-20T21:17:50.317000Z" ## ..$ url : chr "http://swapi.co/api/people/6/" ## $ :List of 14 ## ..$ name : chr "Beru Whitesun lars" ## ..$ height : chr "165" ## ..$ mass : chr "75" ## ..$ hair_color: chr "brown" ## ..$ skin_color: chr "light" ## ..$ eye_color : chr "blue" ## ..$ birth_year: chr "47BBY" ## ..$ gender : chr "female" ## ..$ homeworld : chr "http://swapi.co/api/planets/1/" ## ..$ films : chr [1:3] "http://swapi.co/api/films/5/" "http://swapi.co/api/films/6/" "http://swapi.co/api/films/1/" ## ..$ species : chr "http://swapi.co/api/species/1/" ## ..$ created : chr "2014-12-10T15:53:41.121000Z" ## ..$ edited : chr "2014-12-20T21:17:50.319000Z" ## ..$ url : chr "http://swapi.co/api/people/7/" ## $ :List of 14 ## ..$ name : chr "R5-D4" ## ..$ height : chr "97" ## ..$ mass : chr "32" ## ..$ hair_color: chr "n/a" ## ..$ skin_color: chr "white, red" ## ..$ eye_color : chr "red" ## ..$ birth_year: chr "unknown" ## ..$ gender : chr "n/a" ## ..$ homeworld : chr "http://swapi.co/api/planets/1/" ## ..$ films : chr "http://swapi.co/api/films/1/" ## ..$ species : chr "http://swapi.co/api/species/2/" ## ..$ created : chr "2014-12-10T15:57:50.959000Z" ## ..$ edited : chr "2014-12-20T21:17:50.321000Z" ## ..$ url : chr "http://swapi.co/api/people/8/" ## $ :List of 15 ## ..$ name : chr "Biggs Darklighter" ## ..$ height : chr "183" ## ..$ mass : chr "84" ## ..$ hair_color: chr "black" ## ..$ skin_color: chr "light" ## ..$ eye_color : chr "brown" ## ..$ birth_year: chr "24BBY" ## ..$ gender : chr "male" ## ..$ homeworld : chr "http://swapi.co/api/planets/1/" ## ..$ films : chr "http://swapi.co/api/films/1/" ## ..$ species : chr "http://swapi.co/api/species/1/" ## ..$ starships : chr "http://swapi.co/api/starships/12/" ## ..$ created : chr "2014-12-10T15:59:50.509000Z" ## ..$ edited : chr "2014-12-20T21:17:50.323000Z" ## ..$ url : chr "http://swapi.co/api/people/9/" ## $ :List of 16 ## ..$ name : chr "Obi-Wan Kenobi" ## ..$ height : chr "182" ## ..$ mass : chr "77" ## ..$ hair_color: chr "auburn, white" ## ..$ skin_color: chr "fair" ## ..$ eye_color : chr "blue-gray" ## ..$ birth_year: chr "57BBY" ## ..$ gender : chr "male" ## ..$ homeworld : chr "http://swapi.co/api/planets/20/" ## ..$ films : chr [1:6] "http://swapi.co/api/films/5/" "http://swapi.co/api/films/4/" "http://swapi.co/api/films/6/" "http://swapi.co/api/films/3/" ... ## ..$ species : chr "http://swapi.co/api/species/1/" ## ..$ vehicles : chr "http://swapi.co/api/vehicles/38/" ## ..$ starships : chr [1:5] "http://swapi.co/api/starships/48/" "http://swapi.co/api/starships/59/" "http://swapi.co/api/starships/64/" "http://swapi.co/api/starships/65/" ... ## 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..$ mass : chr "unknown" ## ..$ hair_color: chr "white" ## ..$ skin_color: chr "fair" ## ..$ eye_color : chr "blue" ## ..$ birth_year: chr "unknown" ## ..$ gender : chr "female" ## ..$ homeworld : chr "http://swapi.co/api/planets/9/" ## ..$ films : chr "http://swapi.co/api/films/5/" ## ..$ species : chr "http://swapi.co/api/species/1/" ## ..$ created : chr "2014-12-20T17:32:51.996000Z" ## ..$ edited : chr "2014-12-20T21:17:50.476000Z" ## ..$ url : chr "http://swapi.co/api/people/74/" ## $ :List of 14 ## ..$ name : chr "Ratts Tyerell" ## ..$ height : chr "79" ## ..$ mass : chr "15" ## ..$ hair_color: chr "none" ## ..$ skin_color: chr "grey, blue" ## ..$ eye_color : chr "unknown" ## ..$ birth_year: chr "unknown" ## ..$ gender : chr "male" ## ..$ homeworld : chr "http://swapi.co/api/planets/38/" ## ..$ films : chr "http://swapi.co/api/films/4/" ## ..$ species : chr "http://swapi.co/api/species/16/" ## ..$ created : chr "2014-12-20T09:53:15.086000Z" ## ..$ edited : chr "2016-06-30T12:52:19.604868Z" ## ..$ url : chr "http://swapi.co/api/people/47/" ## $ :List of 13 ## ..$ name : chr "R4-P17" ## ..$ height : chr "96" ## ..$ mass : chr "unknown" ## ..$ hair_color: chr "none" ## ..$ skin_color: chr "silver, red" ## ..$ eye_color : chr "red, blue" ## ..$ birth_year: chr "unknown" ## ..$ gender : chr "female" ## ..$ homeworld : chr "http://swapi.co/api/planets/28/" ## ..$ films : chr [1:2] "http://swapi.co/api/films/5/" "http://swapi.co/api/films/6/" ## ..$ created : chr "2014-12-20T17:43:36.409000Z" ## ..$ edited : chr "2014-12-20T21:17:50.478000Z" ## ..$ url : chr "http://swapi.co/api/people/75/" ## $ :List of 14 ## ..$ name : chr "Wat Tambor" ## ..$ height : chr "193" ## ..$ mass : chr "48" ## ..$ hair_color: chr "none" ## ..$ skin_color: chr "green, grey" ## ..$ eye_color : chr "unknown" ## ..$ birth_year: chr "unknown" ## ..$ gender : chr "male" ## ..$ homeworld : chr "http://swapi.co/api/planets/56/" ## ..$ films : chr "http://swapi.co/api/films/5/" ## ..$ species : chr "http://swapi.co/api/species/33/" ## ..$ created : chr "2014-12-20T17:53:52.607000Z" ## ..$ edited : chr "2014-12-20T21:17:50.481000Z" ## ..$ url : chr "http://swapi.co/api/people/76/" ## $ :List of 14 ## ..$ name : chr "San Hill" ## ..$ height : chr "191" ## ..$ mass : chr "unknown" ## ..$ hair_color: chr "none" ## ..$ skin_color: chr "grey" ## ..$ eye_color : chr "gold" ## ..$ birth_year: chr "unknown" ## ..$ gender : chr "male" ## ..$ homeworld : chr "http://swapi.co/api/planets/57/" ## ..$ films : chr "http://swapi.co/api/films/5/" ## ..$ species : chr "http://swapi.co/api/species/34/" ## ..$ created : chr "2014-12-20T17:58:17.049000Z" ## ..$ edited : chr "2014-12-20T21:17:50.484000Z" ## ..$ url : chr "http://swapi.co/api/people/77/" ## $ :List of 14 ## ..$ name : chr "Shaak Ti" ## ..$ height : chr "178" ## ..$ mass : chr "57" ## ..$ hair_color: chr "none" ## ..$ skin_color: chr "red, blue, white" ## ..$ eye_color : chr "black" ## ..$ birth_year: chr "unknown" ## ..$ gender : chr "female" ## ..$ homeworld : chr "http://swapi.co/api/planets/58/" ## ..$ films : chr [1:2] "http://swapi.co/api/films/5/" "http://swapi.co/api/films/6/" ## ..$ species : chr "http://swapi.co/api/species/35/" ## ..$ created : chr "2014-12-20T18:44:01.103000Z" ## ..$ edited : chr "2014-12-20T21:17:50.486000Z" ## ..$ url : chr "http://swapi.co/api/people/78/" ## $ :List of 16 ## ..$ name : chr "Grievous" ## ..$ height : chr "216" ## ..$ mass : chr "159" ## ..$ hair_color: chr "none" ## ..$ skin_color: chr "brown, white" ## ..$ eye_color : chr "green, yellow" ## ..$ birth_year: chr "unknown" ## ..$ gender : chr "male" ## ..$ homeworld : chr "http://swapi.co/api/planets/59/" ## ..$ films : chr "http://swapi.co/api/films/6/" ## ..$ species : chr "http://swapi.co/api/species/36/" ## ..$ vehicles : chr "http://swapi.co/api/vehicles/60/" ## ..$ starships : chr "http://swapi.co/api/starships/74/" ## ..$ created : chr "2014-12-20T19:43:53.348000Z" ## ..$ edited : chr "2014-12-20T21:17:50.488000Z" ## ..$ url : chr "http://swapi.co/api/people/79/" ## $ :List of 14 ## 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..$ films : chr "http://swapi.co/api/films/7/" ## ..$ species : chr "http://swapi.co/api/species/1/" ## ..$ created : chr "2015-04-17T06:54:01.495077Z" ## ..$ edited : chr "2015-04-17T06:54:01.495128Z" ## ..$ url : chr "http://swapi.co/api/people/85/" ## $ :List of 15 ## ..$ name : chr "Poe Dameron" ## ..$ height : chr "unknown" ## ..$ mass : chr "unknown" ## ..$ hair_color: chr "brown" ## ..$ skin_color: chr "light" ## ..$ eye_color : chr "brown" ## ..$ birth_year: chr "unknown" ## ..$ gender : chr "male" ## ..$ homeworld : chr "http://swapi.co/api/planets/28/" ## ..$ films : chr "http://swapi.co/api/films/7/" ## ..$ species : chr "http://swapi.co/api/species/1/" ## ..$ starships : chr "http://swapi.co/api/starships/77/" ## ..$ created : chr "2015-04-17T06:55:21.622786Z" ## ..$ edited : chr "2015-04-17T06:55:21.622835Z" ## ..$ url : chr "http://swapi.co/api/people/86/" ## $ :List of 14 ## ..$ name : chr "BB8" ## ..$ height : chr "unknown" ## ..$ mass : chr "unknown" ## ..$ hair_color: chr "none" ## ..$ skin_color: chr "none" ## ..$ eye_color : chr "black" ## ..$ birth_year: chr "unknown" ## ..$ gender : chr "none" ## ..$ homeworld : chr "http://swapi.co/api/planets/28/" ## ..$ films : chr "http://swapi.co/api/films/7/" ## ..$ species : chr "http://swapi.co/api/species/2/" ## ..$ created : chr "2015-04-17T06:57:38.061346Z" ## ..$ edited : chr "2015-04-17T06:57:38.061453Z" ## ..$ url : chr "http://swapi.co/api/people/87/" ## $ :List of 13 ## ..$ name : chr "Captain Phasma" ## ..$ height : chr "unknown" ## ..$ mass : chr "unknown" ## ..$ hair_color: chr "unknown" ## ..$ skin_color: chr "unknown" ## ..$ eye_color : chr "unknown" ## ..$ birth_year: chr "unknown" ## ..$ gender : chr "female" ## ..$ homeworld : chr "http://swapi.co/api/planets/28/" ## ..$ films : chr "http://swapi.co/api/films/7/" ## ..$ created : chr "2015-10-13T10:35:39.229823Z" ## ..$ edited : chr "2015-10-13T10:35:39.229894Z" ## ..$ url : chr "http://swapi.co/api/people/88/" ## $ :List of 15 ## ..$ name : chr "Padmé Amidala" ## ..$ height : chr "165" ## ..$ mass : chr "45" ## ..$ hair_color: chr "brown" ## ..$ skin_color: chr "light" ## ..$ eye_color : chr "brown" ## ..$ birth_year: chr "46BBY" ## ..$ gender : chr "female" ## ..$ homeworld : chr "http://swapi.co/api/planets/8/" ## ..$ films : chr [1:3] "http://swapi.co/api/films/5/" "http://swapi.co/api/films/4/" "http://swapi.co/api/films/6/" ## ..$ species : chr "http://swapi.co/api/species/1/" ## ..$ starships : chr [1:3] "http://swapi.co/api/starships/49/" "http://swapi.co/api/starships/64/" "http://swapi.co/api/starships/39/" ## ..$ created : chr "2014-12-19T17:28:26.926000Z" ## ..$ edited : chr "2016-04-20T17:06:31.502555Z" ## ..$ url : chr "http://swapi.co/api/people/35/" ``` ] --- class: middle count: false # Acknowledgments --- ## Acknowledgments Above materials are derived in part from the following sources: * Hadley Wickham - [Adv-R Functionals](http://adv-r.had.co.nz/Functionals.html) * Hadley Wickham - [R for Data Science](http://r4ds.had.co.nz/) * Neil Saunders - [A brief introduction to "apply" in R](http://nsaunders.wordpress.com/2010/08/20/a-brief-introduction-to-apply-in-r/) * Jenny Bryan - [Purrr Tutorial](https://jennybc.github.io/purrr-tutorial/) * [R Language Definition](http://stat.ethz.ch/R-manual/R-devel/doc/manual/R-lang.html)