Exportations par produit - Volume (CVS-CJO) - t_exports_vol

Données - INSEE

Auteur

François Geerolf

Last observation: Q2 2026 (N = 21)

First observation: Q1 1949 (N = 21)

Last data update: 03 sept. 2026, 05:31

Last compile: 24 sept. 2026, 01:47

Comptes trimestriels : exportations par produit, en volume.

Structure

Principales branches

Code 
`t_exports_vol` |>
  filter(variable %in% big) |>
  ggplot() + theme_minimal() + xlab("") + ylab("Exportations (volume)") +
  geom_line(aes(x = date, y = value, color = a17_label(variable))) +
  scale_x_date(date_breaks = "10 years", date_labels = "%Y") +
  theme(legend.title = element_blank(), legend.position = "bottom") +
  guides(color = guide_legend(nrow = 2))

Industrie manufacturière — glissement annuel

Code 
`t_exports_vol` |>
  filter(variable == "C") |>
  arrange(date) |> mutate(g = value / lag(value, 4) - 1) |>
  filter(date >= as.Date("1980-01-01")) |>
  ggplot() + theme_minimal() + xlab("") + ylab("Glissement annuel") +
  geom_hline(yintercept = 0, color = "grey60") +
  geom_line(aes(x = date, y = g)) +
  scale_x_date(date_breaks = "10 years", date_labels = "%Y") +
  scale_y_continuous(labels = percent_format(accuracy = 1))

Répartition par branche

Code 
`t_exports_vol` |>
  filter(grepl("^[A-Z][A-Z0-9]?$", variable), variable != "C") |>
  group_by(date) |> mutate(part = value / sum(value)) |> ungroup() |>
  arrange(desc(variable)) |> mutate(variable = factor(a17_label(variable), levels = unique(a17_label(variable)))) |>
  ggplot() + theme_minimal() + xlab("") + ylab("Part du total") +
  geom_area(aes(x = date, y = part, fill = variable)) +
  scale_x_date(date_breaks = "10 years", date_labels = "%Y") +
  scale_y_continuous(labels = percent_format(accuracy = 1)) +
  scale_fill_viridis_d() +
  theme(legend.title = element_blank(), legend.position = "bottom") +
  guides(fill = guide_legend(nrow = 3))

Derniers trimestres

Code 
`t_exports_vol` |>
  filter(grepl("^[A-Z][A-Z0-9]?$", variable), date >= last_d %m-% months(18)) |>
  mutate(value = round(value, 1)) |>
  tidyr::pivot_wider(names_from = variable, values_from = value) |>
  arrange(desc(date)) |>
  print_table_conditional()
date AZ DE C C1 C2 C3 C4 C5 FZ GZ HZ JZ KZ MN OQ RU
2026-04-01 4.0 4.7 133.0 12.9 1.9 26.3 37.2 55.0 0.1 2.1 13.8 7.1 8.6 29.0 0.4 1.1
2026-01-01 4.0 4.9 127.3 13.0 2.2 25.3 30.5 56.0 0.1 2.0 14.0 7.1 8.5 28.2 0.4 1.1
2025-10-01 4.0 5.0 134.4 12.8 2.3 25.0 37.7 56.5 0.2 2.0 13.5 7.1 8.7 28.0 0.4 1.2
2025-07-01 4.1 4.7 133.1 12.8 2.2 24.4 36.2 57.4 0.2 2.0 13.1 7.1 8.8 27.9 0.4 1.2
2025-04-01 4.1 4.5 127.3 13.1 2.1 24.0 32.0 55.9 0.2 2.1 13.4 7.0 8.8 28.0 0.4 1.2
2025-01-01 3.8 4.3 127.4 13.1 2.1 23.7 33.0 55.3 0.2 2.0 13.6 6.9 8.7 28.2 0.4 1.3
2024-10-01 3.7 4.5 129.5 13.2 2.1 23.6 33.9 56.6 0.2 2.0 13.6 7.0 8.5 27.9 0.4 1.3