Mortality (by week) - HEALTH_MORTALITY

Data - OECD

Author

François Geerolf

WEEK

Code 
HEALTH_MORTALITY %>%
  left_join(HEALTH_MORTALITY_var$WEEK, by = "WEEK") %>%
  group_by(WEEK, Week) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  print_table_conditional

VARIABLE

Code 
HEALTH_MORTALITY %>%
  left_join(HEALTH_MORTALITY_var$VARIABLE, by = "VARIABLE") %>%
  group_by(VARIABLE, Variable) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  print_table_conditional
VARIABLE Variable Nobs
ALLCAUNB All-cause deaths (number) 138954
EXCESSNB Excess deaths (number) 47826
EXCESSPC Excess deaths (% change from average) 47811
COVIDNB COVID-19 deaths (number) 6659
COVIDPC COVID-19 deaths (% of All-cause deaths) 4730

COUNTRY

Code 
HEALTH_MORTALITY %>%
  left_join(HEALTH_MORTALITY_var$COUNTRY, by = "COUNTRY") %>%
  group_by(COUNTRY, Country) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  mutate(Flag = gsub(" ", "-", str_to_lower(gsub(" ", "-", Country))),
         Flag = paste0('<img src="../../icon/flag/vsmall/', Flag, '.png" alt="Flag">')) %>%
  select(Flag, everything()) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F, escape = F) else .}

obsTime

Code 
HEALTH_MORTALITY %>%
  group_by(obsTime) %>%
  summarise(Nobs = n()) %>%
  arrange(desc(obsTime)) %>%
  print_table_conditional()
obsTime Nobs
2022 42049
2021 56327
2020 57893
2019 18025
2018 17992
2017 17995
2016 17992
2015 17707