1.105 – Produit intérieur brut - les trois approches à prix courants (En milliards d’euros) - t_1105

Data - INSEE

Author

2019

Code

t_1105 %>%
  filter(date == as.Date("2019-12-31")) %>%
  select(-date) %>%
  mutate(value = round(value) %>% paste0(" Mds€")) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}

Investissement, Exportations, Importations

Code

t_1105 %>%
  filter(line %in% c(7, 8, 9)) %>%
  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(1945, 2020, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%y")) +
  scale_y_continuous(breaks = 0.01*seq(0, 500, 2),
                labels = percent_format(accuracy = 1)) +
  scale_color_manual(values = viridis(4)[1:3]) +
  theme(legend.position = c(0.75, 0.15),
        legend.title = element_blank())

Consommation, Rémunération des salariés

Plus de détail sur la consommation finale. html

Code

t_1105 %>%
  filter(line %in% c(6, 11)) %>%
  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(1945, 2020, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%y")) +
  scale_y_continuous(breaks = 0.01*seq(0, 500, 5),
                labels = percent_format(accuracy = 1)) +
  scale_color_manual(values = viridis(3)[1:2]) +
  theme(legend.position = c(0.75, 0.15),
        legend.title = element_blank())

Exportations, Importations

1949-2020

Code

t_1105 %>%
  filter(line %in% c(8, 9)) %>%
  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(1945, 2020, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%y")) +
  scale_y_continuous(breaks = 0.01*seq(0, 500, 2),
                labels = percent_format(accuracy = 1)) +
  scale_color_manual(values = viridis(3)[1:2]) +
  theme(legend.position = c(0.75, 0.15),
        legend.title = element_blank())

1990-2020

Code

t_1105 %>%
  filter(line %in% c(8, 9)) %>%
  filter(date >= as.Date("1990-01-01")) %>%
  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(1945, 2020, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%y")) +
  scale_y_continuous(breaks = 0.01*seq(0, 500, 2),
                labels = percent_format(accuracy = 1)) +
  scale_color_manual(values = viridis(3)[1:2]) +
  theme(legend.position = c(0.75, 0.15),
        legend.title = element_blank())