Alison Presmanes Hill apreshill

## Alison plot
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)

## read-multiple-csv-files
# 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.R
# 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)
}

## names2snake
# 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

## h2olead.csv

          
            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

## cdc_addm_all.csv

          
            site
            total
            n_asd
            prevalence_1000
            data_source
            l95_1000
            u95_1000
            year_survey
            year_pub
            birth_cohort
            table
            for_line

            
              Alabama
              36566
              174
              4.8
              ho
              4.1
              5.5
              2008
              2012
              2000
              2
              1

            
              Arizona
              32601
              507
              15.6
              eh
              14.3
              17
              2008
              2012
              2000
              2
              1

            
              Arkansas
              4940
              52
              10.5
              eh
              8
              13.8
              2008
              2012
              2000
              2
              1

            
              Colorado
              7725
              91
              11.8
              eh
              9.6
              14.5
              2008
              2012
              2000
              2
              0

            
              Colorado
              29336
              188
              6.4
              ho
              5.6
              7.4
              2008
              2012
              2000
              2
              1

            
              Florida
              29366
              211
              7.2
              ho
              6.3
              8.2
              2008
              2012
              2000
              2
              1

            
              Georgia
              50427
              601
              11.9
              eh
              11
              12.9
              2008
              2012
              2000
              2
              1

            
              Maryland
              27022
              336
              12.4
              eh
              11.2
              13.8
              2008
              2012
              2000
              2
              1

            
              Missouri
              25668
              357
              13.9
              ho
              12.5
              15.4
              2008
              2012
              2000
              2
              1

## orly-owl-residuals
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)

## my-homebrew-bundle
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',

## 12-startup-alison.R
# 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

## dplyr-counts-and-proportions
library(tidyverse)

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

msleep

msleep %>%
  add_count(vore) %>% # n = vores
  count(vore, order, n) %>% # nn = unique orders per vore
	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
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
site	total	n_asd	prevalence_1000	data_source	l95_1000	u95_1000	year_survey	year_pub	birth_cohort	table	for_line
Alabama	36566	174	4.8	ho	4.1	5.5	2008	2012	2000	2	1
Arizona	32601	507	15.6	eh	14.3	17	2008	2012	2000	2	1
Arkansas	4940	52	10.5	eh	8	13.8	2008	2012	2000	2	1
Colorado	7725	91	11.8	eh	9.6	14.5	2008	2012	2000	2	0
Colorado	29336	188	6.4	ho	5.6	7.4	2008	2012	2000	2	1
Florida	29366	211	7.2	ho	6.3	8.2	2008	2012	2000	2	1
Georgia	50427	601	11.9	eh	11	12.9	2008	2012	2000	2	1
Maryland	27022	336	12.4	eh	11.2	13.8	2008	2012	2000	2	1
Missouri	25668	357	13.9	ho	12.5	15.4	2008	2012	2000	2	1
	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