# Claimant rate during COVID-19 outbreak # Source: ONS # URL: https://www.nomisweb.co.uk/sources/cc # Licence: Open Government Licence v3.0 # load libraries --------------------------- library(tidyverse) ; library(zoo) ; library(forcats) # load Lab's ggplot2 theme --------------------------- source("https://github.com/traffordDataLab/assets/raw/master/theme/ggplot2/theme_lab.R") # load data --------------------------- raw <- read_csv("https://www.nomisweb.co.uk/api/v01/dataset/NM_162_1.data.csv?geography=1660945005...1660945019,1660945021,1660945020,1660945022...1660945025,1853882369,1811939363,2092957697&date=latestMINUS2-latest&gender=0&age=0&measure=2&measures=20100") # tidy data --------------------------- df <- raw %>% select(area_code = GEOGRAPHY_CODE, area_name = GEOGRAPHY_NAME, indicator = MEASURE_NAME, period = DATE_NAME, value = OBS_VALUE) %>% mutate(period = factor(as.yearmon(period, "%b %Y"), levels = c("Mar 2020","Apr 2020","May 2020")), area_name = fct_reorder(factor(area_name), ifelse(period == "May 2020", value, NA), na.rm = TRUE), area_name = fct_relevel(factor(area_name), "United Kingdom", "Greater Manchester","Trafford"), measure = "percent", unit = "persons") # plot data --------------------------- ggplot(df, aes(value,area_name)) + geom_line(color = "#f0f0f0", size=5) + geom_point(aes(color = period), size = 5) + scale_x_continuous(labels = function(x){ paste0(x, "%") }, limits = c(0, 15)) + scale_colour_manual(values = c( "#fd8d3c","#f03b20", "#bd0026")) + labs(x = "percentage of residents aged 16 or over", y = NULL, title = "Claimant Rate during COVID-19 outbreak", subtitle = "Trafford Wards, March 2020 to May 2020", caption = "Source: ONS | @traffordDataLab")+ theme_lab() + theme(panel.grid.major.y = element_blank(), axis.text.y = element_text(hjust = 1), legend.position = "bottom", legend.title = element_blank()) # write data --------------------------- write_csv(df, "data.csv") ggsave("plot.svg", dpi = 300, scale = 1) ggsave("plot.png", dpi = 300, scale = 1)