johnburnmurdoch’s gists

johnburnmurdoch / voter_id_rerun.R

Created May 11, 2021 13:05

	install.packages("needs")
	library(needs)
	needs(sjlabelled, tidyverse, haven, magrittr, ggrepel, sf)

	# Load in data from all waves
	USoc_indresp_1 <- read_dta("/path to wave 1/", encoding = "latin1")
	USoc_indresp_2 <- read_dta("/path to wave 2/", encoding = "latin1")
	etc

	# Join all waves together, keeping the most recent driving licence record for each respondent, and their vote in the last election

johnburnmurdoch / covid_cases_UK_LAs.csv

Created July 27, 2020 17:22

johnburnmurdoch / google_covid_mobility_scraper.R

Created April 15, 2020 08:04

	# Install and load required packages
	install.packages("needs")
	library(needs)
	needs(tidyverse, magrittr, animation, pdftools, png, scales)

	# Function that extracts data from Google Mobility PDFs
	process_google_mobility <- function(country_code, start_date, end_date){

	# Convert first page of PDF into high-res PNG
	pdf_convert(paste0("https://www.gstatic.com/covid19/mobility/",end_date,"_",country_code,"_Mobility_Report_en.pdf"), format = "png", pages = 1, dpi = 300, filenames = "IMG1.png")

johnburnmurdoch / coronavirus_cases_trajectories.R

Created March 11, 2020 15:17

	read_csv("https://raw.githubusercontent.com/CSSEGISandData/COVID-19/master/csse_covid_19_data/csse_covid_19_time_series/time_series_19-covid-Confirmed.csv") %>%
	gather(date, cases, 5:ncol(.)) %>%
	mutate(date = as.Date(date, "%m/%d/%y")) %>%
	group_by(country = `Country/Region`, date) %>%
	summarise(cases = sum(cases)) %>%
	filter(country != "Others" & country != "Mainland China") %>%
	bind_rows(
	tibble(country = "Republic of Korea", date = as.Date("2020-03-11"), cases = 7755)
	) %>%
	group_by(country) %>%

johnburnmurdoch / ireland_consituency_results_map.R

Created February 13, 2020 17:35

	install.packages("needs")
	library(needs)
	needs(tidyverse, magrittr, rvest, sf, raster, rgdal)

	ireland_constits <- c("https://en.wikipedia.org/wiki/Carlow%E2%80%93Kilkenny_(D%C3%A1il_constituency)") %>%
	read_html() %>%
	html_nodes('div[aria-labelledby="Current_Dáil_constituencies"] tr:nth-child(2) ul li a') %>%
	html_attr("href") %>%
	tail(-1) %>%
	c("/wiki/Carlow%E2%80%93Kilkenny_(D%C3%A1il_constituency)", .)

johnburnmurdoch / covid_cases_script.R

Created February 13, 2020 17:27

	install.packages("needs")
	library(needs)
	needs(tidyverse, magrittr, rvest, zoo, scales)

	WHO_sars_links <- read_html("https://www.who.int/csr/sars/country/en/") %>%
	html_nodes("ul.auto_archive") %>%
	magrittr::extract(1) %>%
	html_nodes("li a") %>%
	map_dfr(~{
	link <- .x %>% html_attr("href") %>% paste0("https://www.who.int",.)

johnburnmurdoch / city_populations_projections.csv

Last active December 7, 2019 14:48

johnburnmurdoch / extract_values_from_bar_charts.R

Created November 3, 2019 18:12

	needs(tidyverse, magrittr, png)

	# Create a folder for storing the charts
	dir.create("BFB_images")

	# Loop though constituency codes in England and Wales, downloading the chart for each on from BfB
	for(pcon in c(B4B_MRP$westminster_constituency[B4B_MRP$region != "Scotland"])){
	tryCatch(download.file(paste0("https://www.getvoting.org/charts/",pcon,"_1.png"), destfile = paste0("BFB_images/", pcon, ".png")), error = function(e){message("No chart")})
	}

johnburnmurdoch / USoc_driving_licence.R

Created October 13, 2019 14:32

	needs(sjlabelled, tidyverse, haven, magrittr)

	# Load wave 8
	USoc_indresp_8 <- read_dta("~/Downloads/UKDA-6614-stata/stata11_se/ukhls_w8/h_indresp.dta", encoding = "latin1")

	# Load all other waves
	USoc_indresp_1 <- read_dta("~/Downloads/UKDA-6614-stata/stata11_se/ukhls_w1/a_indresp.dta", encoding = "latin1")
	USoc_indresp_2 <- read_dta("~/Downloads/UKDA-6614-stata/stata11_se/ukhls_w2/b_indresp.dta", encoding = "latin1")
	USoc_indresp_3 <- read_dta("~/Downloads/UKDA-6614-stata/stata11_se/ukhls_w3/c_indresp.dta", encoding = "latin1")
	USoc_indresp_4 <- read_dta("~/Downloads/UKDA-6614-stata/stata11_se/ukhls_w4/d_indresp.dta", encoding = "latin1")

johnburnmurdoch / custom_unit_histograms_in_R.R

Last active September 30, 2019 17:04

	install.packages("needs")
	library(needs)
	needs(tidyverse, magrittr)

	# I’m using an example dataset of net national income per capita, from the World Bank (https://data.worldbank.org/indicator/NY.ADJ.NNTY.PC.CD?most_recent_value_desc=true)
	head(dataset)

	# Here’s a basic histogram using the ggplot defaults to show the distribution of NNI per capita across the world:
	ggplot(dataset, aes(value)) +
	geom_histogram()