Centre d’études prospectives et d’informations internationales - CEPII

Data

Author

François Geerolf

Datasets

Code 
tibble(id = c("CHELEM_2018_PIB_VA_BvD_20180702",
              "CHELEM_2018_PIB_VO_BvD_20180702",
              "bilateral_ER",
              "TRADHIST_EXCHANGE_RATES",
              "chel202016718_TT",
              "chel202016718",
              "chelem"),
       label = c("PIB.",
                 "PIB Réel",
                 "bilateral_ER",
                 "TRADHIST_EXCHANGE_RATES",
                 "chel202016718_TT",
                 "chel202016718",
                 "chelem")) %>%
  {if (is_html_output()) mutate(., html = paste0("[html](",id, ".html)")) else .} %>%
  {if (is_html_output()) print_table(.) else .}
id label html
CHELEM_2018_PIB_VA_BvD_20180702 PIB. [html]
CHELEM_2018_PIB_VO_BvD_20180702 PIB Réel [html]
bilateral_ER bilateral_ER [html]
TRADHIST_EXCHANGE_RATES TRADHIST_EXCHANGE_RATES [html]
chel202016718_TT chel202016718_TT [html]
chel202016718 chel202016718 [html]
chelem chelem [html]

Produits

Code 
produits %>%
  select(1:4) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}

Produits - Court

Code 
produits %>%
  select(1:3) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}

Pays

Code 
pays %>%
  select(1:3) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}

Long time series

Long time series stretch back to 1967, in millions of current dollars.

Code 
chel201726716_FRA_DEU %>%
  filter(k == "TT") %>%
  mutate(date = paste0(t, "-01-01") %>% as.Date,
         value = v / 1000,
         country = i) %>%
  ggplot(.) + theme_minimal() + xlab("") + ylab("") +
  geom_line(aes(x = date, y = value, linetype = country, color = country)) +
  scale_y_continuous(breaks = seq(0, 150, 10)) +
  scale_x_date(breaks = as.Date(paste0(seq(1960, 2020, 5), "-01-01")),
               labels = date_format("%y")) + 
  scale_color_manual(values = viridis(5)[1:4]) +
  theme(legend.title = element_blank(),
        legend.position = c(0.15, 0.80))

Germany Exports

Plots

Code 
chelem_DEU_X %>%
  year_to_date() %>%
  filter(partner == "WLD",
         sector %in% c("ST6", "ST1", "ST2", "ST3", "ST4", "ST5")) %>%
  left_join(produits %>%
              select(2, 3) %>%
              setNames(c("sector", "Sector")), by = "sector") %>%
  ggplot(.) + theme_minimal() + xlab("") + ylab("") +
  geom_line(aes(x = date, y = value/1000, linetype = Sector, color = Sector)) +
  scale_y_continuous(breaks = seq(0, 1500, 100)) +
  scale_x_date(breaks = as.Date(paste0(seq(1960, 2020, 5), "-01-01")),
               labels = date_format("%y")) + 
  scale_color_manual(values = viridis(8)[1:7]) +
  theme(legend.title = element_blank(),
        legend.position = c(0.15, 0.80))

Table

Code 
chelem_DEU_X %>%
  year_to_date() %>%
  filter(partner == "WLD",
         date == as.Date("2016-01-01")) %>%
  left_join(produits %>%
              select(2, 3) %>%
              setNames(c("sector", "Sector")), by = "sector") %>%
  select(sector, Sector, value) %>%
  arrange(-value) %>%
  mutate(value = round(value/1000) %>% paste0(" Mds€")) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}

Germany Imports

Plots

Code 
chelem_DEU_M %>%
  year_to_date() %>%
  filter(partner == "WLD",
         sector %in% c("ST6", "ST1", "ST2", "ST3", "ST4", "ST5")) %>%
  left_join(produits %>%
              select(2, 3) %>%
              setNames(c("sector", "Sector")), by = "sector") %>%
  ggplot(.) + theme_minimal() + xlab("") + ylab("") +
  geom_line(aes(x = date, y = value/1000, linetype = Sector, color = Sector)) +
  scale_y_continuous(breaks = seq(0, 1500, 100)) +
  scale_x_date(breaks = as.Date(paste0(seq(1960, 2020, 5), "-01-01")),
               labels = date_format("%y")) + 
  scale_color_manual(values = viridis(8)[1:7]) +
  theme(legend.title = element_blank(),
        legend.position = c(0.15, 0.80))

Table

Code 
chelem_DEU_M %>%
  year_to_date() %>%
  filter(partner == "WLD",
         date == as.Date("2016-01-01")) %>%
  left_join(produits %>%
              select(2, 3) %>%
              setNames(c("sector", "Sector")), by = "sector") %>%
  select(sector, Sector, value) %>%
  arrange(-value) %>%
  mutate(value = round(value/1000) %>% paste0(" Mds€")) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}