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"id","address","description","species","diameter"
"819539","1307 HILLSIDE AVENUE","Remove dead 21 inch Live Oak in the ROW.","Oak",21
"757396","6201 GLEN MEADOW DRIVE","Remove Arizona Ash in Front Yard at 6201 Glen Meadow.","Arizona Ash",28
"785768","2614 DELWOOD PLACE","remove fallen post oak backyard","Oak",28
"733765","1109 FLANAGAN COVE","Remove 25"" Hackberry","Hackberry",25
"768887","1000 WISTERIA CIRCLE","Full of cavities and in decline, fall hazard","Arizona Ash",35
"773451","11776 JOLLYVILLE ROAD","Cedar elm in parking lot is hollow at the base creating a hazardous situation. The tree is also suffering from girdling roots, canopy decline, an unbalanced crown, borer damage, and mistletoe infection. Tree is recommended for removal due to void beneath tree and lower stem decay.","Cedar Elm",23
"746882","3801-1/2 EMMA BROWNING AVENUE","Remove dead tree / species unknown","Hackberry",12
"718921","2912 CHERRY LANE","URGENT! Remove protected sized cedar elm that is currently leaning and is a hazard.  Tree i

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EURIPI
HEARIE
IDEATA
AEDINE
DEAWIE
EOCENE
FINITO
VEGETE
PEREIA
ACULEI

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### Making half box/half point plot 

# somewhat hackish solution to:
# https://twitter.com/EamonCaddigan/status/646759751242620928
# based mostly on copy/pasting from ggplot2 geom_violin source:
# https://github.com/hadley/ggplot2/blob/master/R/geom-violin.r

library(ggplot2)
library(dplyr)

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library(tidyverse)
library(magrittr)
library(rvest)

webpage <- read_html("https://en.wikipedia.org/wiki/List_of_tournament_performances_by_Tiger_Woods")

l <- webpage %>% html_nodes("table.wikitable") %>% html_table()

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## Drawing consonants in a row

tiles <- c(rep("V", 44), rep("C", 56))  # 42 vowels + 2 blanks,  56 consonants
# combined vowels and blanks into "V" as don't care about difference for this


# loop 1 million times
res<-NULL
for(i in 1:1000000){
draw <- sample(tiles, 17, F)

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library(engsoccerdata)
library(tidyverse)

england %>% 
  filter(tier==1) %>%
  split(.$Season) %>%
  map(function(x) maketable_eng(x, Season = x$Season[1], tier=1, penalties=T) ) %>%
  map(~summarise(., diff = Pts[Pos==1] - Pts[Pos==2])) %>%
  bind_rows %>%
  ggplot(aes(x=diff))+geom_histogram(color='black', fill="gray62", binwidth = 1) + scale_x_continuous(breaks = seq(0,20,2)) +

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library(tidyverse)
library(engsoccerdata)

  england %>%
  filter(tier==1) %>%
  homeaway() %>%
  group_by(team) %>%
  arrange(Date) %>%
  filter(venue=="away") %>%
  mutate(gameno = row_number())%>%

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license: mit

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### Comparing Arsenal Points per N games over time

library(engsoccerdata)
library(tidyverse)

rollpts <- function(teamname=NULL, N=10){
rbind(england,england_current()) %>%
  homeaway() %>%
  filter(team==teamname) %>%
  mutate(pts = ifelse(gf>ga, 3, ifelse(gf<ga, 0, 1)),