Mortality rate, infant (per 1,000 live births) - SP.DYN.IMRT.IN

Data - WDI

~/data/wdi/

Nobs - Javascript

SP.DYN.IMRT.IN %>%
  left_join(iso2c, by = "iso2c") %>%
  group_by(iso2c, Iso2c) %>%
  rename(value = `SP.DYN.IMRT.IN`) %>%
  summarise(Nobs = n(),
            `Year 1` = first(year),
            `Pop 1` = first(value),
            `Year 2` = last(year),
            `Pop 2` = last(value)) %>%
  arrange(-Nobs) %>%
  mutate(Flag = gsub(" ", "-", str_to_lower(Iso2c)),
         Flag = paste0('<img src="../../bib/flags/vsmall/', Flag, '.png" alt="Flag">')) %>%
  select(Flag, everything()) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F, escape = F) else .}

China, E.U., U.S.

All

SP.DYN.IMRT.IN %>%
  right_join(iso2c, by = "iso2c") %>%
  year_to_date %>%
  rename(value = SP.DYN.IMRT.IN) %>%
  filter(iso2c %in% c("US", "CN", "EU")) %>%
  mutate(Iso2c = ifelse(iso2c == "EU", "Europe", Iso2c)) %>%
  left_join(colors, by = c("Iso2c" = "country")) %>%
  mutate(color = ifelse(iso2c == "US", color2, color)) %>%
  ggplot(.) + theme_minimal() + scale_color_identity() +
  geom_line(aes(x = date, y = value, color = color)) +
  add_3flags +
  scale_x_date(breaks = seq(1950, 2020, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%y")) +
  scale_y_continuous(breaks = 0.01*seq(0, 70, 2),
                     labels = scales::percent_format(accuracy = 1)) + 
  xlab("") + ylab("% de la population mondiale")