3.301 – Dépenses des administrations publiques (S13) ventilées par fonction (En milliards d’euros) - t_3301

Data - INSEE

2019

Ordre Ligne

t_3301 %>%
  left_join(gdp, by = "date") %>%
  filter(date == as.Date("2018-01-01")) %>%
  select(-date) %>%
  mutate(`% du PIB` = (100*value/(gdp)) %>% round(., digits = 2),
         value = round(value) %>% paste0(" M€")) %>%
  select(-gdp) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}

Ordre décroissant

t_3301 %>%
  left_join(gdp, by = "date") %>%
  filter(date == as.Date("2018-01-01")) %>%
  select(-date) %>%
  mutate(`% du PIB` = (100*value/(gdp)) %>% round(., digits = 2),
         value = round(value)) %>%
  select(-gdp) %>%
  arrange(-value) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}

Santé, Services ambulatoires, hospitaliers

t_3301 %>%
  filter(line %in% c(49, 51, 52)) %>%
  left_join(gdp, by = "date") %>%
  ggplot + geom_line(aes(x = date, y = value / gdp, color = Line, linetype = Line)) +
  theme_minimal() + xlab("") + ylab("% du PIB") +
  scale_x_date(breaks = seq(1960, 2020, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%y")) +
  scale_y_continuous(breaks = 0.01*seq(0, 500, 1),
                labels = percent_format(accuracy = 1),
                limits = c(0, 0.09)) +
  scale_color_manual(values = viridis(4)[1:3]) +
  theme(legend.position = c(0.75, 0.15),
        legend.title = element_blank())