Code
produits |>
select(1:4) %>%
{if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}Chelem - chelem
Données - CEPII
Last data update: 01 août 2026, 21:30
Last compile: 05 sept. 2026, 01:35
Produits
Long
Court
Code
produits |>
select(1:3) %>%
{if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}Stades
Code
produits |>
select(2:4) |>
slice(95:100) %>%
{if (is_html_output()) print_table(.) else .}| Code | Libellé abrégé FR | Libellé long FR |
|---|---|---|
| ST1 | Primaires | HA+HB+HC+IA+IB+IC+JA+JB+JC |
| ST2 | Manufacturés de base | BA+BB+BC+CA+CC+GA+GC+IG |
| ST3 | Biens intermédiaires | CB+DA+EA+EC+FA+FB+FC+FL+FS+GB+GD+GG+GI |
| ST4 | Biens d'équipement | FD+FE+FF+FG+FH+FI+FN+FO+FQ+FR+FU+FV+FW |
| ST5 | Produits mixtes | DE+EB+ED+GH+IH+II+KB+KC+KF+KG |
| ST6 | Biens de consommation | DB+DC+DD+EE+FJ+FK+FM+FP+FT+GE+GF+KA+KD+KE+KH+KI |
Filières
Code
produits |>
select(2:4) |>
slice(84:94) %>%
{if (is_html_output()) print_table(.) else .}| Code | Libellé abrégé FR | Libellé long FR |
|---|---|---|
| R01 | Energétique | IA+IB+IC+IG+IH+II |
| R02 | Agroalimentaire | JA+JB+JC+KA+KB+KC+KD+KE+KF+KG+KH+KI |
| R03 | Textile | DA+DB+DC+DD+DE |
| R04 | Bois, papiers | EA+EB+EC+ED+EE |
| R05 | Chimique | GA+GB+GC+GD+GE+GF+GG+GH+GI+BA+BB+BC+HC |
| R06 | Sidérurgique | HA+CA+CB |
| R07 | Non ferreux | HB+CC |
| R08 | Mécanique | FA+FB+FC+FD+FE+FF+FG+FH+FV+FW |
| R09 | Véhicules | FS+FT+FU |
| R10 | Electrique | FP+FQ+FR |
| R11 | Electronique | FI+FJ+FK+FL+FM+FN+FO |
Sections
Code
produits |>
select(2:4) |>
slice(74:83) %>%
{if (is_html_output()) print_table(.) else .}| Code | Libellé abrégé FR | Libellé long FR |
|---|---|---|
| B | Matériaux de construction | BA + BB + BC |
| C | Sidérurgie, métallurgie | CA + CB + CC |
| D | Textiles, cuirs | DA + DB + DC + DD + DE |
| E | Bois, papiers | EA+EB+EC+ED+EE |
| F | Mécanique, électrique | FA+FB+FC+FD+FE+FF+FG+FH+FI+FJ+FK+FL+FM+FN+FO+FP+FQ+FR+FS+FT+FU+FV+FW |
| G | Chimie | GA+GB+GC+GD+GE+GF+GG+GH+GI |
| H | Minerais | HA+HB+HC |
| I | Energie | IA+IB+IC+IG+IH+II |
| J | Agriculture | JA+JB+JC |
| K | Produits alimentaires | KA+KB+KC+KD+KE+KF+KG+KH+KI |
Pays
Code
pays |>
select(1:3) %>%
{if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}France and Germany
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(),
country = i) |>
ggplot() + theme_minimal() + xlab("") + ylab("") +
geom_line(aes(x = date, y = v / 1000, 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
Imports
Code
chelem_DEU_M |>
year_to_date() |>
filter(partner == "WLD",
sector %in% c("ST6", "ST1", "ST2", "ST3", "ST4", "ST5")) |>
left_join(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, 10)) +
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(0.2, 0.75))
Imports - Table
Code
imports1 <- chelem_DEU_M |>
year_to_date() |>
filter(partner == "WLD",
date == as.Date("2016-01-01")) |>
left_join(sector, by = "sector") |>
select(sector, Sector, imports = value) |>
arrange(-imports)
imports1 |>
mutate(imports = round(imports/1000) |> paste0(" Mds€")) %>%
{if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}Exports
Code
chelem_DEU_X |>
year_to_date() |>
filter(partner == "WLD",
sector %in% c("ST6", "ST1", "ST2", "ST3", "ST4", "ST5")) |>
left_join(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, 10)) +
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(0.2, 0.75))
Exports - Table
Code
exports1 <- chelem_DEU_X |>
year_to_date() |>
filter(partner == "WLD",
date == as.Date("2016-01-01")) |>
left_join(sector, by = "sector") |>
select(sector, Sector, exports = value) |>
arrange(-exports)
exports1 |>
mutate(exports = round(exports/1000) |> paste0(" Mds€")) %>%
{if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}Net Exports - Table
Code
exports1 |>
left_join(imports1, by =c("sector", "Sector")) |>
mutate(net_exports = exports -imports) |>
arrange(-net_exports) |>
mutate(net_exports = round(net_exports/1000) |> paste0(" Mds€")) |>
select(-exports, -imports) %>%
{if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}Exports - Imports
Code
chelem_DEU_X |>
mutate(variable = "X") |>
bind_rows(chelem_DEU_M |>
mutate(variable = "M")) |>
spread(variable, value) |>
mutate(NX = X-M) |>
year_to_date() |>
filter(partner == "WLD",
sector %in% c("ST6", "ST1", "ST2", "ST3", "ST4", "ST5")) |>
left_join(sector, by = "sector") |>
ggplot() + theme_minimal() + xlab("") + ylab("") +
geom_line(aes(x = date, y = NX/1000, linetype = Sector, color = Sector)) +
scale_y_continuous(breaks = seq(-1000, 1500, 10)) +
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(0.2, 0.3))
GDP
Code
CHELEM_2018_PIB_VA_BvD_20180702 |>
filter(iso3c %in% c("DEU")) |>
select(date, GDP = value) %>%
{if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}FT, R09, FS
Code
chelem_DEU_X |>
mutate(variable = "X") |>
bind_rows(chelem_DEU_M |>
mutate(variable = "M")) |>
spread(variable, value) |>
year_to_date() |>
left_join(CHELEM_2018_PIB_VA_BvD_20180702 |>
filter(iso3c %in% c("DEU")) |>
select(date, GDP = value), by = "date") |>
mutate(NX = (X-M)/GDP) |>
filter(partner == "WLD",
sector %in% c("FT", "R09", "FS")) |>
left_join(sector, by = "sector") |>
ggplot() + theme_minimal() + xlab("") + ylab("") +
geom_line(aes(x = date, y = NX, linetype = Sector, color = Sector)) +
scale_y_continuous(breaks = 0.01*seq(-10, 10, 1),
labels = percent_format(accuracy = 1)) +
scale_x_date(breaks = as.Date(paste0(seq(1960, 2020, 5), "-01-01")),
labels = date_format("%Y")) +
scale_color_manual(values = viridis(4)[1:3]) +
theme(legend.title = element_blank(),
legend.position = c(0.2, 0.8))
Energie, Total
Code
chelem_DEU_X |>
mutate(variable = "X") |>
bind_rows(chelem_DEU_M |>
mutate(variable = "M")) |>
spread(variable, value) |>
year_to_date() |>
left_join(CHELEM_2018_PIB_VA_BvD_20180702 |>
filter(iso3c %in% c("DEU")) |>
select(date, GDP = value), by = "date") |>
mutate(NX = (X-M)/GDP) |>
filter(partner == "WLD",
sector %in% c("TT", "ST1", "R01")) |>
left_join(sector, by = "sector") |>
ggplot() + theme_minimal() + xlab("") + ylab("") +
geom_line(aes(x = date, y = NX, linetype = Sector, color = Sector)) +
scale_y_continuous(breaks = 0.01*seq(-10, 10, 1),
labels = percent_format(accuracy = 1)) +
scale_x_date(breaks = as.Date(paste0(seq(1960, 2020, 5), "-01-01")),
labels = date_format("%Y")) +
scale_color_manual(values = viridis(4)[1:3]) +
theme(legend.title = element_blank(),
legend.position = c(0.2, 0.9))
FT, R09, FS - Exports
Code
chelem_DEU_X |>
mutate(variable = "X") |>
bind_rows(chelem_DEU_M |>
mutate(variable = "M")) |>
spread(variable, value) |>
year_to_date() |>
left_join(CHELEM_2018_PIB_VA_BvD_20180702 |>
filter(iso3c %in% c("DEU")) |>
select(date, GDP = value), by = "date") |>
filter(partner == "WLD",
sector %in% c("FT", "R09", "FS")) |>
left_join(sector, by = "sector") |>
ggplot() + theme_minimal() + xlab("") + ylab("") +
geom_line(aes(x = date, y = X/GDP, linetype = Sector, color = Sector)) +
scale_y_continuous(breaks = 0.01*seq(-10, 50, 1),
labels = percent_format(accuracy = 1)) +
scale_x_date(breaks = as.Date(paste0(seq(1960, 2020, 5), "-01-01")),
labels = date_format("%Y")) +
scale_color_manual(values = viridis(4)[1:3]) +
theme(legend.title = element_blank(),
legend.position = c(0.2, 0.8))
ST1, ST2, ST3, ST4, ST5, ST6
Code
chelem_DEU_X |>
mutate(variable = "X") |>
bind_rows(chelem_DEU_M |>
mutate(variable = "M")) |>
spread(variable, value) |>
year_to_date() |>
left_join(CHELEM_2018_PIB_VA_BvD_20180702 |>
filter(iso3c %in% c("DEU")) |>
select(date, GDP = value), by = "date") |>
mutate(NX = (X-M)/GDP) |>
filter(partner == "WLD",
sector %in% c("ST6", "ST1", "ST2", "ST3", "ST4", "ST5")) |>
left_join(sector, by = "sector") |>
ggplot() + theme_minimal() + xlab("") + ylab("") +
geom_line(aes(x = date, y = NX, linetype = Sector, color = Sector)) +
scale_y_continuous(breaks = 0.01*seq(-10, 10, 1),
labels = percent_format()) +
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(0.2, 0.3))
M, ST1, ST2
Code
chelem_DEU_X |>
mutate(variable = "X") |>
bind_rows(chelem_DEU_M |>
mutate(variable = "M")) |>
spread(variable, value) |>
year_to_date() |>
left_join(CHELEM_2018_PIB_VA_BvD_20180702 |>
filter(iso3c %in% c("DEU")) |>
select(date, GDP = value), by = "date") |>
mutate(NX = (X-M)/GDP) |>
filter(partner == "WLD",
sector %in% c("ST2", "M", "ST1")) |>
left_join(sector, by = "sector") |>
ggplot() + theme_minimal() + xlab("") + ylab("") +
geom_line(aes(x = date, y = NX, linetype = Sector, color = Sector)) +
scale_y_continuous(breaks = 0.01*seq(-1000, 1500, 1),
labels = percent_format()) +
scale_x_date(breaks = as.Date(paste0(seq(1960, 2020, 5), "-01-01")),
labels = date_format("%Y")) +
scale_color_manual(values = viridis(4)[1:3]) +
theme(legend.title = element_blank(),
legend.position = c(0.2, 0.3))
Partners
Code
chelem_DEU_X |>
mutate(variable = "X") |>
bind_rows(chelem_DEU_M |>
mutate(variable = "M")) |>
spread(variable, value) |>
year_to_date() |>
left_join(CHELEM_2018_PIB_VA_BvD_20180702 |>
filter(iso3c %in% c("DEU")) |>
select(date, GDP = value), by = "date") |>
filter(partner == c("WLD", "FRA", "USA", "CHN"),
sector %in% c("TT")) |>
left_join(partner, by = "partner") |>
ggplot() + theme_minimal() + xlab("") + ylab("") +
geom_line(aes(x = date, y = (X-M)/GDP, linetype = Partner, color = Partner)) +
scale_y_continuous(breaks = 0.01*seq(-1000, 1500, 1),
labels = percent_format(accuracy = 1)) +
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(0.2, 0.3))
Partners 2
Code
chelem_DEU_X |>
mutate(variable = "X") |>
bind_rows(chelem_DEU_M |>
mutate(variable = "M")) |>
spread(variable, value) |>
year_to_date() |>
left_join(CHELEM_2018_PIB_VA_BvD_20180702 |>
filter(iso3c %in% c("DEU")) |>
select(date, GDP = value), by = "date") |>
filter(partner == c("EUR", "UE", "USA", "CHN"),
sector %in% c("TT")) |>
left_join(partner, by = "partner") |>
ggplot() + theme_minimal() + xlab("") + ylab("") +
geom_line(aes(x = date, y = (X-M)/GDP, linetype = Partner, color = Partner)) +
scale_y_continuous(breaks = 0.01*seq(-1000, 1500, 1),
labels = percent_format(accuracy = 1)) +
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(0.2, 0.3))
Table
Code
chelem_DEU_X |>
mutate(variable = "X") |>
bind_rows(chelem_DEU_M |>
mutate(variable = "M")) |>
spread(variable, value) |>
year_to_date() |>
left_join(CHELEM_2018_PIB_VA_BvD_20180702 |>
filter(iso3c %in% c("DEU")) |>
select(date, GDP = value), by = "date") |>
filter(sector %in% c("TT"),
date == as.Date("2017-01-01")) |>
left_join(partner, by = "partner") |>
mutate(`NX (% of GDP)` = round(100 * (X - M)/GDP, 1)) |>
select(partner, Partner, `NX (% of GDP)`) |>
arrange(-`NX (% of GDP)`) %>%
{if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}ST3, ST4, ST5
Code
chelem_DEU_X |>
mutate(variable = "X") |>
bind_rows(chelem_DEU_M |>
mutate(variable = "M")) |>
spread(variable, value) |>
year_to_date() |>
left_join(CHELEM_2018_PIB_VA_BvD_20180702 |>
filter(iso3c %in% c("DEU")) |>
select(date, GDP = value), by = "date") |>
mutate(NX = (X-M)/GDP) |>
filter(partner == "WLD",
sector %in% c("ST3", "ST4", "ST5")) |>
left_join(sector, by = "sector") |>
ggplot() + theme_minimal() + xlab("") + ylab("") +
geom_line(aes(x = date, y = NX, linetype = Sector, color = Sector)) +
scale_y_continuous(breaks = 0.01*seq(-1000, 1500, 0.5),
labels = percent_format()) +
scale_x_date(breaks = as.Date(paste0(seq(1960, 2020, 5), "-01-01")),
labels = date_format("%Y")) +
scale_color_manual(values = viridis(4)[1:3]) +
theme(legend.title = element_blank(),
legend.position = c(0.2, 0.3))
France
Imports
Code
chelem_FRA_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, 10)) +
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(0.2, 0.75))
Exports
Code
chelem_FRA_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, 10)) +
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(0.2, 0.75))
Exports - Imports
Code
chelem_FRA_X |>
mutate(variable = "X") |>
bind_rows(chelem_FRA_M |>
mutate(variable = "M")) |>
spread(variable, value) |>
mutate(NX = X-M) |>
year_to_date() |>
filter(partner == "WLD",
sector %in% c("ST6", "ST1", "ST2", "ST3", "ST4", "ST5")) |>
left_join(sector, by = "sector") |>
ggplot() + theme_minimal() + xlab("") + ylab("") +
geom_line(aes(x = date, y = NX/1000, linetype = Sector, color = Sector)) +
scale_y_continuous(breaks = seq(-1000, 1500, 10)) +
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(0.2, 0.3))
GDP
Code
CHELEM_2018_PIB_VA_BvD_20180702 |>
filter(iso3c %in% c("FRA")) |>
select(date, GDP = value) %>%
{if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}ST1, ST2, ST3, ST4, ST5, ST6
Code
chelem_FRA_X |>
mutate(variable = "X") |>
bind_rows(chelem_FRA_M |>
mutate(variable = "M")) |>
spread(variable, value) |>
year_to_date() |>
left_join(CHELEM_2018_PIB_VA_BvD_20180702 |>
filter(iso3c %in% c("FRA")) |>
select(date, GDP = value), by = "date") |>
mutate(NX = (X-M)/GDP) |>
filter(partner == "WLD",
sector %in% c("ST6", "ST1", "ST2", "ST3", "ST4", "ST5")) |>
left_join(sector, by = "sector") |>
ggplot() + theme_minimal() + xlab("") + ylab("") +
geom_line(aes(x = date, y = NX, linetype = Sector, color = Sector)) +
scale_y_continuous(breaks = 0.01*seq(-10, 10, 1),
labels = percent_format()) +
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(0.2, 0.3))
Energie, Total
Code
chelem_FRA_X |>
mutate(variable = "X") |>
bind_rows(chelem_FRA_M |>
mutate(variable = "M")) |>
spread(variable, value) |>
year_to_date() |>
left_join(CHELEM_2018_PIB_VA_BvD_20180702 |>
filter(iso3c %in% c("FRA")) |>
select(date, GDP = value), by = "date") |>
mutate(NX = (X-M)/GDP) |>
filter(partner == "WLD",
sector %in% c("TT", "ST1", "R01")) |>
left_join(sector, by = "sector") |>
ggplot() + theme_minimal() + xlab("") + ylab("") +
geom_line(aes(x = date, y = NX, linetype = Sector, color = Sector)) +
scale_y_continuous(breaks = 0.01*seq(-10, 10, 1),
labels = percent_format(accuracy = 1)) +
scale_x_date(breaks = as.Date(paste0(seq(1960, 2020, 5), "-01-01")),
labels = date_format("%Y")) +
scale_color_manual(values = viridis(4)[1:3]) +
theme(legend.title = element_blank(),
legend.position = c(0.2, 0.9))
M, ST1, ST2
Code
chelem_FRA_X |>
mutate(variable = "X") |>
bind_rows(chelem_FRA_M |>
mutate(variable = "M")) |>
spread(variable, value) |>
year_to_date() |>
left_join(CHELEM_2018_PIB_VA_BvD_20180702 |>
filter(iso3c %in% c("FRA")) |>
select(date, GDP = value), by = "date") |>
mutate(NX = (X-M)/GDP) |>
filter(partner == "WLD",
sector %in% c("ST2", "M", "ST1")) |>
left_join(sector, by = "sector") |>
ggplot() + theme_minimal() + xlab("") + ylab("") +
geom_line(aes(x = date, y = NX, linetype = Sector, color = Sector)) +
scale_y_continuous(breaks = 0.01*seq(-1000, 1500, 1),
labels = percent_format()) +
scale_x_date(breaks = as.Date(paste0(seq(1960, 2020, 5), "-01-01")),
labels = date_format("%Y")) +
scale_color_manual(values = viridis(4)[1:3]) +
theme(legend.title = element_blank(),
legend.position = c(0.2, 0.3))
ST3, ST4, ST5
Code
chelem_FRA_X |>
mutate(variable = "X") |>
bind_rows(chelem_FRA_M |>
mutate(variable = "M")) |>
spread(variable, value) |>
year_to_date() |>
left_join(CHELEM_2018_PIB_VA_BvD_20180702 |>
filter(iso3c %in% c("FRA")) |>
select(date, GDP = value), by = "date") |>
mutate(NX = (X-M)/GDP) |>
filter(partner == "WLD",
sector %in% c("ST3", "ST4", "ST5")) |>
left_join(sector, by = "sector") |>
ggplot() + theme_minimal() + xlab("") + ylab("") +
geom_line(aes(x = date, y = NX, linetype = Sector, color = Sector)) +
scale_y_continuous(breaks = 0.01*seq(-1000, 1500, 0.5),
labels = percent_format()) +
scale_x_date(breaks = as.Date(paste0(seq(1960, 2020, 5), "-01-01")),
labels = date_format("%Y")) +
scale_color_manual(values = viridis(4)[1:3]) +
theme(legend.title = element_blank(),
legend.position = c(0.2, 0.3))