hadley

library(dplyr, warn.conflicts = FALSE)
library(gapminder)
probs <- c(0.1, 0.5, 0.9)

gapminder %>% 
  group_by(continent) %>% 
  summarise(
    probs = probs,
    across(is.numeric & !year, ~ quantile(.x, probs))
  )

hadley

#!/bin/bash
#
# Installs the latest RStudio daily desktop build for OSX/macOS and Ubuntu(amd64)
#
# https://support.rstudio.com/hc/en-us/articles/203842428-Getting-the-newest-RStudio-builds
set -e
install_macos_daily() {
    REDIRECT_URL="https://www.rstudio.org/download/latest/daily/desktop/mac/RStudio-latest.dmg"
echo "Discovering daily build from: ${REDIRECT_URL}"
# Perform a HEAD request to find the redirect target. We use the name of the

hadley

# What's the most natural way to express this code in base R?
library(dplyr, warn.conflicts = FALSE)
mtcars %>%
  group_by(cyl) %>%
  summarise(mean = mean(disp), n = n())
#> # A tibble: 3 x 3
#>     cyl  mean     n
#>   <dbl> <dbl> <int>
#> 1     4  105.    11
#> 2     6  183.     7

hadley

library(tidyverse)
library(gh)
library(lubridate)
library(glue)

repo <- tibble(json = unclass(gh("/user/repos", .limit = Inf)))

repo <- repo %>% 
  hoist(json, 
    owner = c("owner", "login"),

hadley

# =======================================
# =     Enhancements to data tidying    =
# =          Hadley Wickham             =
# = https://rstd.io/tidyhancements-2019 =
# =======================================

# What is tidy data? ----------------------------------------------------------
# 1. Each column is a variable.
# 2. Each row is an observation.
# 3. Each cell is a value.

hadley

library(rlang)

enum_value <- function(x, values) {
  structure(
    x, 
    values = values,
  )
}

enum <- function(...) {

hadley

library(tidyverse)
library(rvest)

url <- "https://en.wikipedia.org/wiki/The_Great_British_Bake_Off_(series_3)"
page <- read_html(url)

table <- page %>% 
  html_nodes("table.wikitable") %>% 
  .[[2]]

hadley

# Constructor and basic methods  ---------------------------------------------

new_rational <- function(n, d) {
  stopifnot(is.integer(n), is.integer(d))
  stopifnot(length(n) == length(d))

  structure(list(d = d, n = n), class = "rational")
}

length.rational <- function(x) {

hadley

ruler <- function(width = getOption("width")) {
  x <- seq_len(width)
  y <- dplyr::case_when(
    x %% 10 == 0 ~ as.character((x %/% 10) %% 10),
    x %% 5 == 0  ~ "+",
    TRUE         ~ "-"
  )
  cat(y, "\n", sep = "")
  cat(x %% 10, "\n", sep = "")
}

hadley

library(class)
library(mass)
library(mva)

tst <- read.table("e:/uni/stats766/puktest.txt", header = TRUE)
tst.v <- tst[,1:7]
tst.g <- tst[,8]
trn <- read.table("e:/uni/stats766/puktrain.txt", header = TRUE)
trn.v <- trn[,1:7]
trn.g <- trn[,8]