Alison Presmanes Hill apreshill

county	sample	state	name	exceedances
Mobile	20	al	Dauphin Island Water & Sewer	1
Monroe	23	al	Excel Water System	1
Washington	95	al	Tate & Lyle Sucralose, Inc. Water System	1
Coosa	18.3	al	Lake Mitchell Water, Incorporated	1
Juneau City and Borough	15.5	ak	Thunder Mountain Mobile Park	1
Juneau City and Borough	31	ak	Hecla Greens Creek Hawk Inlet	1
Ketchikan Gateway Borough	27.7	ak	Boyer Towing	1
Ketchikan Gateway Borough	32.9	ak	Thorne Bay, City Of	1
Ketchikan Gateway Borough	16.2	ak	Clover Pass Christian School	2

	Thanks to Hilary Parker for the easy breezy template!

	https://gist.github.com/hilaryparker/046f55f5222b12692d74

	#load packages
	library(babynames)
	library(dplyr)
	library(ggplot2)
	library(grid)
	library(wesanderson)

	# stack overflow answer from Joran Ellis:
	# http://stackoverflow.com/questions/5319839/read-multiple-csv-files-into-separate-data-frames

	# If the path is different than your working directory
	# you'll need to set full.names = TRUE to get the full
	# paths.
	my_files <- list.files("path/to/files")

	# Further arguments to read.csv can be passed in ...
	all_csv <- lapply(my_files,read.csv,...)

	# ipak function: install and load multiple R packages.
	# check to see if packages are installed. Install them if they are not, then load them into the R session.

	ipak <- function(pkg){
	new.pkg <- pkg[!(pkg %in% installed.packages()[, "Package"])]
	if (length(new.pkg))
	install.packages(new.pkg, dependencies = TRUE)
	sapply(pkg, require, character.only = TRUE)
	}

	# convert all column names to snake case
	# make all column names lower case
	# replace all . with _
	names2snake <- function(data){
	require(stringr)
	require(dplyr)
	names(data) = names(data) %>%
	tolower() %>%
	str_replace_all(., "[.]", "_")
	data

	library(broom)
	library(ggplot2)

	# read in the data
	# others available here: http://www4.stat.ncsu.edu/~stefanski/NSF_Supported/Hidden_Images/stat_res_plots.html
	owl <- read.table("http://www4.stat.ncsu.edu/~stefanski/NSF_Supported/Hidden_Images/orly_owl_files/orly_owl_Lin_4p_5_flat.txt",
	header = FALSE)

	# fit the linear model
	fit <- lm(V1 ~ . - 1, data = owl)

	tap 'homebrew/cask'
	tap 'homebrew/cask-fonts'
	tap 'homebrew/cask-versions'
	tap 'homebrew/cask-drivers'

	cask_args appdir: '/Applications'

	# Version Control
	brew 'git', args: ['with-persistent-https',
	'with-curl',

	# Create a GitHub PAT
	# Hint: use the usethis package
	# see: http://happygitwithr.com/github-pat.html#step-by-step
	library(usethis)
	browse_github_pat() # takes you to browser

	# Add it to .Renviron
	# Hint: use the usethis package
	edit_r_environ() # makes the file if not yet made- needs blank line at end!
	# now copy/paste long PAT with = sign

	library(tidyverse)

	msleep <- msleep %>%
	select(name:order)

	msleep

	msleep %>%
	add_count(vore) %>% # n = vores
	count(vore, order, n) %>% # nn = unique orders per vore