hadley

library(httr)
library(digest)
library(XML)

s3_request <- function(verb, bucket, path = "/", query = NULL,
                       content = NULL, date = NULL) {
  list(
    verb = verb,
    bucket = bucket,
    path = path,

hadley

library("shiny")

x <- runApp(shinyApp(
  fluidPage(
    "Password:", 
    tags$input(id = "password", type = "password"),
    actionButton("done", "Done")
  ),
  function(input, output) {
    observe({

hadley

R_COMPLETION=FALSE
R_LIBS=~/R
TMPDIR=/tmp

_R_CHECK_FORCE_SUGGESTS_=false

GITHUB_PAT=[redacted]
DO_PAT=[redacted]

hadley

library(tidyverse)

simple_data <- tibble(
  group = factor(rep(c("A", "B"), each = 15)),
  subject = 1:30,
  score = c(rnorm(15, 40, 20), rnorm(15, 60, 10))
)

simple_data_se &lt;- simple_data %&gt;% 

hadley

library(tidyverse)
library(gapminder)

gapminder
gapminder <- gapminder %>% mutate(year1950 = year - 1950)

# Nested data -------------------------------------------------------------

by_country <- gapminder %>%
  group_by(continent, country) %>%

hadley

# need + validate -----------------------------------------------------------
validate(
  need(
    mzfinder::check_mzr_object(ms_object$mzr_connection),
    "Wasn't able to connect to MS file"
  )
)
validate(
  need(!is.null(input$ppm_input), "ppm_input must not be null"),
  need(input$ppm_input > 0L, "ppm_input must be > 0")

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(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

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

#' @include DBConnection.R
NULL

#' Generate SQL: CREATE TABLE
#' 
#' @param conn A subclass of \code{\linkS4class{DBIConnection}} describing
#'   an active database connection.
#' @param name A string giving the table name to create. Escaped with
#'   \code{\link{dbQuoteIdentifier}}
#' @param fields,types Character vectors of equal lengths giving the names