Mia datalove

Vagrant

vagrant init

	decode <- function(x, ...) {

	odds <- function(x) { unlist(x[1:length(x) %% 2 == 1][1:floor(length(x)/2)]) }
	even <- function(x) { unlist(x[1:length(x) %% 2 == 0]) }
	last <- function(x) { unlist(if(length(x) %% 2 == 1) tail(x,1)) }

	interpret_args <- function(x) { if(is.call(x)) {eval(x)} else if(is.name(x)) {as.character(x)} else {x} }

	args <- eval(substitute(alist(...)))
	args <- lapply(args, interpret_args)

	library(dplyr)

	# you can pull out a column from a tbl_df like this, but it's ugly and awkward to type
	mtcars %>% .[['mpg']]
	mtcars %>% .[[1]]

	# So let's make a nice function
	pull <- function(x,y) {x[,if(is.name(substitute(y))) deparse(substitute(y)) else y]}

	# works on tbl_df or dataframes equally well

	`%>>%` <- function(x,y) {
	cl <- match.call()
	lhs <- cl[[2]] ; rhs <- cl[[3]]
	if(length(rhs) == 1) {
	y(x)
	} else {
	rhsl <- as.list(rhs)
	rhsl <- c(rhsl[1], lhs, rhsl[2:length(rhsl)]) # swap in the lhs as the first arg in rhs
	eval(as.call(rhsl))
	}

	# Let's say we're doing some analysis on the mtcars data..

	# displacement/cylinder for high horsepower cars
	mtcars %>%
	filter(hp > 100) %>%
	mutate(disp_cyl = disp/cyl) %>% filter(disp_cyl > 25) %>%
	group_by(cyl,am) %>% summarise(mean_hp = mean(hp), mean_disp_cyl = mean(disp_cyl))

	# or displacement/cylinder for all cars
	mtcars %>%

	files <- list.files("C:/R/packages", pattern = "^MYPACKAGENAME.*\\.zip", full.names = TRUE)
	files <- gsub("-([0-9]{1})\\.","-0\\1\\.", files)
	files
	latest_file <- sort(files, decreasing = TRUE)[1]
	latest_file
	dest <- "\\\\intranet.mycompany.org/INTRANET/Shared/R/bin/windows/contrib/3.0"

	copy_success <- file.copy(latest_file, dest)
	copy_success

	identical <- function(x) UseMethod("identical")
	identical.my_class <- function(x) do_something(x)
	identical.default <- base::identical

	############################
	# Mapinfo TAB to __________
	############################
	# https://karlhennermann.wordpress.com/2013/03/15/converting-data-between-mapinfo-and-arcgis/

	ogr2ogr -f "ESRI Shapefile" output.shp National_heritage_public.TAB
	ogr2ogr -f "GeoJSON" output.json National_heritage_public.TAB

	### Title: Back to basics: High quality plots using base R graphics
	### An interactive tutorial for the Davis R Users Group meeting on April 24, 2015
	###
	### Date created: 20150418
	### Last updated: 20150423
	###
	### Author: Michael Koontz
	### Email: [email protected]
	### Twitter: @michaeljkoontz
	###