lashlee

library(tidyverse)
library(ggmap)

#Test number must be of the form of a number (ndx) followed by a single letter (version).
is_valid_test_nbr <- function(test_nbr) grepl("^[0-9]+[A-Za-z]?{1}$",test_nbr)

##Test
identical(is_valid_test_nbr(c("A","123","123A","123AB","_123A","_123","_A")),
          c(FALSE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE))

lashlee

// Will be parameters
var PARAM_EVENT_NAME = "My Event Name"
var PARAM_LOCATION = "Mountain View, CA"
var PARAM_DESCRIPTION = "My Description"
var PARAM_START_DATE = "12/08/2019"
var PARAM_START_TIME = "7:00 PM"
var PARAM_END_DATE = "12/08/2019"
var PARAM_END_TIME = "9:00 PM"

// Xpaths

lashlee

library(ggplot2)
library(ggthemes)
dat <- data.frame(
  party = c('con', 'lab', 'snp', 'lib', 'dup', 'sf', 'pc', 'green', 'ukip_brexit'),
  party_label = c('Conservative', 'Labour', 'Scottish National', 'Liberal Democrats', 
                  'Democratic Unionist', 'Sinn Fein', 'Plaid Cymru', 'Green', 'Brexit & UKIP'),
  vote_2017 = c(13636684, 12877918, 977568,  2371861, 292316, 238915, 164466, 525665, 594068),
  vote_2019 = c(13941200, 10292054, 1242372, 3675342, 244128, 181853, 153265, 864743, 665120),
  seats_2017 = c(317, 262, 35, 12, 10, 7, 4, 1, 0),
  seats_2019 = c(364, 203, 48, 11, 8,  7, 4, 1, 0),

lashlee

# Setup -------------------------------------------------------------------

library(htmltab)
library(dplyr)
library(tidyr)
library(ggplot2)
url <- 'https://www.politico.com/2020-election/results/super-tuesday/'

# Parse -------------------------------------------------------------------

lashlee

# Setup -------------------------------------------------------------------

library(htmltab)
library(dplyr)
library(ggplot2)
library(knitr)
library(scales)
url <- 'https://docquery.fec.gov/cgi-bin/forms/C00739110/1391696//sa/ALL'

# Parse -------------------------------------------------------------------

lashlee

library(ggplot2)
url <- 'https://raw.githubusercontent.com/nytimes/covid-19-data/master/us-counties.csv'
dat <- read.csv(url, header = TRUE, stringsAsFactors = FALSE)
scc <- dat[dat$county == 'Santa Clara' & dat$state == 'California', ]
scc$date <- as.Date(scc$date)
scc <- scc[order(scc$date), ]
# County advises that the five most recent days may change.
# So remove those days from analysis.
scc <- scc[!(scc$date %in% seq.Date(from = Sys.Date() - 4, to = Sys.Date(), by = 1)), ]
scc$incremental_cases <- scc$cases - c(NA_integer_, scc$cases[-nrow(scc)])

lashlee

suppressPackageStartupMessages(library(data.table))
suppressPackageStartupMessages(library(janitor))
suppressPackageStartupMessages(library(lubridate))
suppressPackageStartupMessages(library(tidyr))
suppressPackageStartupMessages(library(dplyr))

# load and transform ------------------------------------------------------

vts <- 
  fread('data/Vote Archive - Public-Grid view.csv', encoding = 'UTF-8') |>