hadley

Stuff and things

head of mtcars

head(mtcars)

hadley

library(shiny)
library(httr)

# OAuth setup --------------------------------------------------------

# Most OAuth applications require that you redirect to a fixed and known
# set of URLs. Many only allow you to redirect to a single URL: if this
# is the case for, you'll need to create an app for testing with a localhost
# url, and an app for your deployed app.

hadley

library(tidyverse)
library(gapminder)

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

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

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

hadley

path <- "~/Documents/ingest/readxl/inst/extdata/datasets.xlsx"

zip_file <- function(path) {
  stopifnot(file.exists(path))
  
  path <- normalizePath(path)
  
  contents <- utils::unzip(path, list = TRUE) 
  names(contents) <- c("path", "size", "date")
  contents <- contents[contents$size > 0, , drop = FALSE]

hadley

only_if <- function(if_false, cond, if_true) {
  if (cond) {
    if_true
  } else {
    if_false
  }
}

hadley

library(data.table)
dt <- data.table(x = 1:10)

bad_fun <- function(x) {
  if (x > 5)
    stop("Uhoh")
  x * 10L
}
dt[, x := bad_fun(x), by = x]
dt

hadley

#include <Rcpp.h>
using namespace Rcpp;

inline SEXP subset_element(SEXP x, int i) {
  size_t n = Rf_length(x);

  if (i < 0 || i >= n || i == NA_INTEGER)
    stop("Invalid subscript");

  return VECTOR_ELT(x, i);

hadley

library(purrr)
library(github) # install_github("cscheid/rgithub")
library(dplyr)
library(stringr)
library(magrittr)

# Download issues ---------------------------------------------------------

ctx <- interactive.login("56b637a5baffac62cad9", "8e107541ae1791259e9987d544ca568633da2ebf")
issues1 <- get.repository.issues("hadley", "dplyr", per_page = 100)

hadley

msg <- function(..., prob = 0.25) {
  if (runif(1) > prob) {
    return(invisible())
  }
  
  messages <- c(...)
  message(sample(messages, 1))
}

encourage <- function() {

hadley

diamonds <- ggplot2::diamonds
pryr::object_size(diamonds)
#> 3.46 MB

diamonds2 <- transform(diamonds, price_per_carat = price / carat)
pryr::object_size(diamonds2)
#> 3.89 MB

# Size of both data frames combined