class: center, middle, inverse, title-slide .title[ # Functions ] .author[ ### Lars Relund Nielsen ] --- layout: true <div class="my-footer"> <span> <a href="https://bss-osca.github.io/tfa/mod-r-functions" target="_blank">Notes</a> | <a href="10_r-functions-slides.html" target="_blank">Slides</a> | <a href="https://github.com/bss-osca/tfa/blob/master/slides/10_r-functions-slides.Rmd" target="_blank">Source</a> | <a href="https://rstudio.cloud/spaces/426101/content/6689204" target="_blank">Posit Cloud</a> </span> </div> --- class: middle > To understand computations in R, two slogans are helpful: > > Everything that exists is an object. > > Everything that happens is a function call. > > > .right[\- _John Chambers_] --- ## Functions - Functions are often used to encapsulate a sequence of expressions that need to be executed numerous times, perhaps under slightly different conditions. <!-- - In programming, functional programming is a programming paradigm, a style how code is written. Rather than repeating code, functions and control structures allow one to build code in blocks. --> - Functions are (often) verbs, followed by what they will be applied to in parentheses. - Functions can be defined using the `function()` directive: ```r library(tidyverse) loop_output <- function(dat, rows = 1:2, cols = 2:3, ...) { ite <- expand_grid(r = rows, c = cols) for (i in 1:nrow(ite)) { r <- ite$r[i] c <- ite$c[i] cat("Row ", r, " column ", c, " = ", dat[r,c], ".\n", ...) } return("Finished!") } ``` - Functions always return the last expression evaluated in the function body or when you use the `return` flow control statement (good coding practice). --- ## Functions - Arguments ```r loop_output(mtcars) # default values ``` ``` ## Row 1 column 2 = 6 . ## Row 1 column 3 = 160 . ## Row 2 column 2 = 6 . ## Row 2 column 3 = 160 . ``` ``` ## [1] "Finished!" ``` ```r loop_output(mtcars, rows = c(3,1), cols = 6) # specify values ``` ``` ## Row 3 column 6 = 2.32 . ## Row 1 column 6 = 2.62 . ``` ``` ## [1] "Finished!" ``` --- ## Functions - The `...` argument ```r loop_output(mtcars, rows = c(3,1), cols = 6) # specify values ``` ``` ## Row 3 column 6 = 2.32 . ## Row 1 column 6 = 2.62 . ``` ``` ## [1] "Finished!" ``` ```r loop_output(mtcars, rows = c(3,1), cols = 6, sep = "") # use the ... argument ``` ``` ## Row 3 column 6 = 2.32. ## Row 1 column 6 = 2.62. ``` ``` ## [1] "Finished!" ``` --- ## Functions - Document your functions Use **Code > Insert Roxygen skeleton** (Ctrl+Alt+Shift+R). ```r #' Loop through some values in a data frame #' #' @param dat A data frame. #' @param rows Rows to loop through. #' @param cols Columns to loop through. #' @param ... Arguments passed to `cat`. #' #' @return A string. loop_output <- function(dat, rows = 1:2, cols = 2:3, ...) { ite <- expand_grid(r = rows, c = cols) for (i in 1:nrow(ite)) { r <- ite$r[i] c <- ite$c[i] cat("Row ", r, " column ", c, " = ", dat[r,c], ".\n", ...) } return("Finished!") } ``` --- ## Your Turn .your-turn[ - Create a function that given some dice numbers and some cards from a 52-card deck (e.g. 1-spade), write out all the possible combinations as strings in the form `Dice = [value] and card = [value]`. Hint: Use `cat`. - Moreover, if the dice numbers contains the number 2, function must return true; otherwise, false. Hint use `return`. - Document your function ```r get_combinations <- function(dice, card) { ite <- expand_grid(___) found <- FALSE for (i in 1:nrow(ite)) { ___ } return(found) } get_combinations(dice = c(2,3), card = c("2-spade", "ace-dimond")) get_combinations(dice = c(3,1), card = c("10-heart", "king-dimond")) ``` ] <div class="countdown" id="timer_0a4faf87" data-update-every="1" tabindex="0" style="top:0;right:0;"> <div class="countdown-controls"><button class="countdown-bump-down">−</button><button class="countdown-bump-up">+</button></div> <code class="countdown-time"><span class="countdown-digits minutes">05</span><span class="countdown-digits colon">:</span><span class="countdown-digits seconds">00</span></code> </div> ??? ```r get_combinations <- function(dice, card) { ite <- expand_grid(d = dice, c = card) found <- FALSE for (i in 1:nrow(ite)) { d <- ite$d[i] c <- ite$c[i] cat("Dice ", d, " and card = ", c, ".\n", sep = "") if (d == 2) found = TRUE } return(found) } get_combinations(dice = c(2,3), card = c("2-spade", "ace-dimond")) ``` ``` ## Dice 2 and card = 2-spade. ## Dice 2 and card = ace-dimond. ## Dice 3 and card = 2-spade. ## Dice 3 and card = ace-dimond. ``` ``` ## [1] TRUE ``` ```r get_combinations(dice = c(3,1), card = c("10-heart", "king-dimond")) ``` ``` ## Dice 3 and card = 10-heart. ## Dice 3 and card = king-dimond. ## Dice 1 and card = 10-heart. ## Dice 1 and card = king-dimond. ``` ``` ## [1] FALSE ``` --- ## Your Turn .your-turn[ - Create a function that calculates the present value (PV) of a future value. The equation is: `$$PV = FV/(1+r)^n$$` where `\(FV\)` is future value, `\(r\)` is the interest rate, and `\(n\)` is the number of periods. - Input arguments must be `\(FV\)`, `\(r\)`, `\(n\)` and a boolean `rond` equal true if the output should be rounded to two decimals. - The default interest rate is 0.1 (10%) and rounding is false by default. ] <div class="countdown" id="timer_023f6778" data-update-every="1" tabindex="0" style="right:0;bottom:0;"> <div class="countdown-controls"><button class="countdown-bump-down">−</button><button class="countdown-bump-up">+</button></div> <code class="countdown-time"><span class="countdown-digits minutes">05</span><span class="countdown-digits colon">:</span><span class="countdown-digits seconds">00</span></code> </div> ??? ```r get_PV <- function(FV, r = 0.1, n, rond = FALSE) { PV <- FV/(1+r)^n if (rond) return(round(PV, 2)) return(PV) } get_PV(100, n = 7) ``` ``` ## [1] 51.31581 ``` ```r get_PV(100, n = 7, rond = TRUE) ``` ``` ## [1] 51.32 ``` ```r get_PV(100, n = 7, r = 0.5) ``` ``` ## [1] 5.852766 ``` [BSS]: https://bss.au.dk/en/ [course-help]: https://github.com/bss-osca/tfa/issues [cran]: https://cloud.r-project.org [cheatsheet-readr]: https://rawgit.com/rstudio/cheatsheets/master/data-import.pdf [course-welcome-to-the-tidyverse]: https://github.com/rstudio-education/welcome-to-the-tidyverse [DataCamp]: https://www.datacamp.com/ [datacamp-signup]: https://www.datacamp.com/groups/shared_links/7a7a4ede68772eefe3a53ce01aead09b538efdf6770fd59911afc29ae396b88e [datacamp-r-intro]: https://learn.datacamp.com/courses/free-introduction-to-r [datacamp-r-rmarkdown]: https://campus.datacamp.com/courses/reporting-with-rmarkdown [datacamp-r-communicating]: https://learn.datacamp.com/courses/communicating-with-data-in-the-tidyverse [datacamp-r-communicating-chap3]: https://campus.datacamp.com/courses/communicating-with-data-in-the-tidyverse/introduction-to-rmarkdown [datacamp-r-communicating-chap4]: 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