5  Workflow: code style

Prerequisites

library(tidyverse)
#> ── Attaching core tidyverse packages ───────────────────── tidyverse 2.0.0 ──
#> ✔ dplyr     1.1.2     ✔ readr     2.1.4
#> ✔ forcats   1.0.0     ✔ stringr   1.5.0
#> ✔ ggplot2   3.4.2     ✔ tibble    3.2.1
#> ✔ lubridate 1.9.2     ✔ tidyr     1.3.0
#> ✔ purrr     1.0.1     
#> ── Conflicts ─────────────────────────────────────── tidyverse_conflicts() ──
#> ✖ dplyr::filter() masks stats::filter()
#> ✖ dplyr::lag()    masks stats::lag()
#> ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors
library(nycflights13)

5.1 Exercises 5.6

1. Restyled pipelines are given below.

   flights |>
     filter(dest == "IAH") |>
     group_by(year, month, day) |>
     summarize(
       n = n(),
       delay = mean(arr_delay, na.rm = TRUE)
     ) |>
     filter(n > 10)
   #> `summarise()` has grouped output by 'year', 'month'. You can override using
   #> the `.groups` argument.
   #> # A tibble: 365 × 5
   #> # Groups:   year, month [12]
   #>    year month   day     n delay
   #>   <int> <int> <int> <int> <dbl>
   #> 1  2013     1     1    20 17.8 
   #> 2  2013     1     2    20  7   
   #> 3  2013     1     3    19 18.3 
   #> 4  2013     1     4    20 -3.2 
   #> 5  2013     1     5    13 20.2 
   #> 6  2013     1     6    18  9.28
   #> # ℹ 359 more rows

   flights |>
     filter(
       carrier == "UA", 
       dest %in% c("IAH", "HOU"), 
       sched_dep_time > 0900, 
       sched_arr_time < 2000
     ) |>
     group_by(flight) |>
     summarize(
       delay = mean(arr_delay, na.rm = TRUE), 
       cancelled = sum(is.na(arr_delay)), n = n()
     ) |>
     filter(n > 10)
   #> # A tibble: 74 × 4
   #>   flight delay cancelled     n
   #>    <int> <dbl>     <int> <int>
   #> 1     53 12.5          2    18
   #> 2    112 14.1          0    14
   #> 3    205 -1.71         0    14
   #> 4    235 -5.36         0    14
   #> 5    255 -9.47         0    15
   #> 6    268 38.6          1    15
   #> # ℹ 68 more rows