ozjimbob

# Simple tibble
d <- tibble(a1="foo",
           a2="bar")

# Want to make a new column called "new" and unite all the "a*" columns together
newcol <- "new"
startchar <- "a"

unite(d,col=newcol,starts_with(startchar)) # Yay

ozjimbob

# General data manipulation
library(tidyverse)

# Spatial data
library(sf)

# Thematic maps
library(tmap)

ozjimbob

# ignoring time=t, just modelling on dx for simplicity

frecent3 <- function(rank,dx){
  a = 6.1625
  cc = 1.6724
  b = 0.2882
  return(( a/(1e-04 * dx + cc)+b) * rank)
}

ozjimbob

library(tidyverse)
library(sf)
library(mapview)
library(furrr)
library(raster)
plan(multiprocess)



ex = extent(c(xmin=-112,xmax=155,ymin=-44,ymax=-10))

ozjimbob

# Demonstration - Downloading and animating ACCESS forecast data
# [email protected]

# General functions, including str_replace, map
library(tidyverse) 

# threddscrawler is a useful package for parsing THREDDS data servers
# Install it with:
# devtools::install_github("BigelowLab/threddscrawler")
library(threddscrawler)

ozjimbob

library("reticulate")
library(tidyverse)
library(purrr)

# We use the python "holidays" package for the basic holidays
# Installed it using pip first
holidays <- import("holidays")
tas_holidays <- holidays$Australia(prov="TAS")

# List of all dates from 2000 to 2018

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data = tibble(foo=c("Bah","Fuzz"))
my_column="foo"
data %>% filter(!!my_column := "Bah")

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## Load required packages
# you will need to install these, first do
# eg.   install.packages("tidyverse")
# etc. to install them one by one
library(tidyverse)
library(httr)
library(sf)
library(tmap)

ozjimbob

library(raster)
library(jpeg)

# Spherical environment mapping hillshade function
getv=function(i,a,s){
  ct = dim(i)[1:2]/2
  sx = values(s)/90 * ct[1]
  sy = values(s)/90 * ct[2]
  a = values(a) * 0.01745
  px = floor(ct[1] + sx * -sin(a))

ozjimbob

library(rjson)
library(httr)

turl="https://iowadems-caucussitecdn-prod2.azureedge.net/api/statecandidateresults"
a=GET(turl)
arr=c(content(a)$StateResults[[1]]$WinPercentage,content(a)$StateResults[[2]]$WinPercentage,content(a)$StateResults[[3]]$WinPercentage)
nam=c(content(a)$StateResults[[1]]$Candidate$DisplayName,content(a)$StateResults[[2]]$Candidate$DisplayName,content(a)$StateResults[[3]]$Candidate$DisplayName)
colr=c(content(a)$StateResults[[1]]$Candidate$Color,content(a)$StateResults[[2]]$Candidate$Color,content(a)$StateResults[[3]]$Candidate$Color)
rar=round(arr,3)*100
barplot(arr,names.arg=nam,col=colr)