data-raw/mobility_major_cities-R.R

In etc5523-2020/r-package-assessment-samuellyu-2021: Covid19: The Battle For Independence Package

#' UK and IRL Mobility data that was used for analysis 
library(tidycovid19)
library(here)
library(tidyverse)
library(tibble)
library(lubridate)
library(covdata)
library(glue)

major_cities <- tibble(lat = c("55.953251", "51.481312", "54.597286", "52.486244","55.861147", "53.797419", "53.405472", "53.479147","53.349307", "51.897928", "53.274412", "52.661258", "51.507276"), 
                       lng = c("-3.188267","-3.180500", "-5.930120", "-1.890401", "-4.249989", "-1.543794", "-2.980539","-2.244745", "-6.261175", "-8.470581", "-9.049063", "-8.630208", "-0.12766"), 
                       region = c("Edinburgh","Cardiff","Belfast","Birmingham","Glasgow","Leeds","Liverpool","Manchester","Dublin","Cork", "Galway","Limerick", "London"),
                       country = c("GBR", "GBR", "GBR", "GBR", "GBR", "GBR", "GBR", "GBR", "IRL", "IRL", "IRL", "IRL", "GBR"),
                       population = c("482005", "335145", "280211", "1086000", "598830", "474632", "552267", "510746", "1388000", "124391", "79934", "194899", "8982000"))



mobility_major_cities <- apple_mobility_covdata %>%
  left_join(major_cities, by = "region") %>%
  select(-country.y) %>%
  rename(country = country.x) %>%
  mutate(lat = as.numeric(lat),
         population = as.numeric(population),
         lng = as.numeric(lng),
         Details = case_when(
           country == "United Kingdom" ~ glue::glue("<br><b>City: {region}
                          <b>Country: {sub_region}, {country}"),
           country == "Ireland" ~ glue::glue("<br><b>City: {region}
                          <b>Country:{country}"))) %>%
  filter(region %in% c("Edinburgh","Cardiff","Belfast","Birmingham","Glasgow","Leeds",
                       "Liverpool","Manchester","Dublin","Cork", "Galway","Limerick", "London"))

usethis::use_data(mobility_major_cities, overwrite = TRUE)