Last observation: 2024 (N = 120)
First observation: 2005 (N = 64)
Last data update: 14 aoû 2026, 21:12. Last compile: 18 aoû 2026, 02:04
Data - Eurostat
Last observation: 2024 (N = 120)
First observation: 2005 (N = 64)
Last data update: 14 aoû 2026, 21:12. Last compile: 18 aoû 2026, 02:04
i_g("bib/industrie/top-20-ports.png")
mar_mg_am_pvh |>
filter(unit == "THS_TEU",
time == "2019",
loadstat == "TOTAL") |>
select(rep_mar, Rep_mar, values) |>
arrange(-values) %>%
{if (is_html_output()) datatable(., filter = 'top', rownames = F, escape = F) else .}mar_mg_am_pvh |>
filter(unit == "THS_TEU",
time == "2020",
loadstat == "TOTAL") |>
select(rep_mar, Rep_mar, values) |>
arrange(-values) %>%
{if (is_html_output()) datatable(., filter = 'top', rownames = F, escape = F) else .}mar_mg_am_pvh |>
filter(loadstat == "TOTAL",
unit == "THS_TEU",
Rep_mar %in% c("Rotterdam", "Antwerpen", "Hamburg", "Marseille")) |>
year_to_date() |>
mutate(values = values / 10^3) |>
ggplot() + geom_line(aes(x = date, y = values, color = Rep_mar)) +
theme_minimal() + xlab("") + ylab("Volumes des conteneurs (Millions EVP)") +
theme(legend.position = c(0.3, 0.85),
legend.title = element_blank()) +
scale_x_date(breaks = seq(1940, 2100, 2) |> paste0("-01-01") |> as.Date(),
labels = date_format("%Y")) +
scale_y_continuous(breaks = seq(0, 20, 1))
FR_2FRMRS
mar_mg_am_pvh |>
filter(loadstat == "TOTAL",
unit == "THS_TEU",
Rep_mar %in% c("Rotterdam", "Antwerpen", "Hamburg")) |>
year_to_date() |>
mutate(values = values / 10^3) |>
ggplot() + geom_line(aes(x = date, y = values, color = Rep_mar)) +
theme_minimal() + xlab("") + ylab("Volumes des conteneurs (Millions EVP)") +
theme(legend.position = c(0.3, 0.85),
legend.title = element_blank()) +
scale_x_date(breaks = seq(1940, 2100, 2) |> paste0("-01-01") |> as.Date(),
labels = date_format("%Y")) +
scale_y_continuous(breaks = seq(0, 20, 1))
mar_mg_am_pvh |>
filter(loadstat == "TOTAL",
unit == "THS_TEU",
Rep_mar %in% c("Peiraias", "Valencia", "Algeciras")) |>
year_to_date() |>
mutate(values = values / 10^3) |>
ggplot() + geom_line(aes(x = date, y = values, color = Rep_mar)) +
theme_minimal() + xlab("") + ylab("Volumes des conteneurs (Millions EVP)") +
theme(legend.position = c(0.3, 0.85),
legend.title = element_blank()) +
scale_x_date(breaks = seq(1940, 2100, 2) |> paste0("-01-01") |> as.Date(),
labels = date_format("%Y")) +
scale_y_continuous(breaks = seq(0, 20, 1))
mar_mg_am_pvh |>
filter(loadstat == "TOTAL",
unit == "THS_TEU",
Rep_mar %in% c("Bremerhaven", "Felixstowe", "Barcelona")) |>
year_to_date() |>
mutate(values = values / 10^3) |>
ggplot() + geom_line(aes(x = date, y = values, color = Rep_mar)) +
theme_minimal() + xlab("") + ylab("Volumes des conteneurs (Millions EVP)") +
theme(legend.position = c(0.1, 0.85),
legend.title = element_blank()) +
scale_x_date(breaks = seq(1940, 2100, 2) |> paste0("-01-01") |> as.Date(),
labels = date_format("%Y")) +
scale_y_continuous(breaks = seq(0, 20, 1))
mar_mg_am_pvh |>
filter(loadstat == "TOTAL",
unit == "THS_TEU",
Rep_mar %in% c("Ambarli", "Gioia Tauro", "Le Havre")) |>
year_to_date() |>
mutate(values = values / 10^3) |>
ggplot() + geom_line(aes(x = date, y = values, color = Rep_mar)) +
theme_minimal() + xlab("") + ylab("Volumes des conteneurs (Millions EVP)") +
theme(legend.position = c(0.1, 0.85),
legend.title = element_blank()) +
scale_x_date(breaks = seq(1940, 2100, 2) |> paste0("-01-01") |> as.Date(),
labels = date_format("%Y")) +
scale_y_continuous(breaks = seq(0, 20, .5))
mar_mg_am_pvh |>
filter(loadstat == "TOTAL",
unit == "THS_TEU",
Rep_mar %in% c("Rotterdam", "Antwerpen", "Hamburg",
"Peiraias", "Valencia", "Algeciras",
"Bremerhaven", "Felixstowe", "Barcelona",
"Ambarli", "Gioia Tauro", "Le Havre")) |>
year_to_date() |>
mutate(values = values / 10^3) |>
mutate(Rep_mar = factor(Rep_mar, c("Rotterdam", "Antwerpen", "Hamburg",
"Peiraias", "Valencia", "Algeciras",
"Bremerhaven", "Felixstowe", "Barcelona",
"Ambarli", "Gioia Tauro", "Le Havre"))) |>
ggplot() + geom_line(aes(x = date, y = values, color = Rep_mar)) +
theme_minimal() + xlab("") + ylab("Volumes des conteneurs (Millions EVP)") +
#scale_color_manual(values = viridis(13)[1:12]) +
theme(legend.title = element_blank()) +
scale_x_date(breaks = seq(1940, 2100, 2) |> paste0("-01-01") |> as.Date(),
labels = date_format("%Y")) +
scale_y_continuous(breaks = seq(0, 20, 1))
mar_mg_am_pvh |>
filter(loadstat == "TOTAL",
unit == "THS_TEU",
Rep_mar %in% c("Rotterdam", "Antwerpen", "Hamburg",
"Peiraias", "Valencia", "Algeciras",
"Bremerhaven", "Felixstowe", "Barcelona",
"Ambarli", "Gioia Tauro", "Le Havre")) |>
year_to_date() |>
mutate(values = values / 10^3) |>
mutate(Rep_mar = factor(Rep_mar, c("Rotterdam", "Antwerpen", "Hamburg",
"Peiraias", "Valencia", "Algeciras",
"Bremerhaven", "Felixstowe", "Barcelona",
"Ambarli", "Gioia Tauro", "Le Havre"))) |>
ggplot() + geom_line(aes(x = date, y = values, color = Rep_mar)) +
theme_minimal() + xlab("") + ylab("Volumes des conteneurs (Millions EVP)") +
#scale_color_manual(values = viridis(13)[1:12]) +
theme(legend.title = element_blank()) +
scale_x_date(breaks = seq(1940, 2100, 2) |> paste0("-01-01") |> as.Date(),
labels = date_format("%Y")) +
scale_y_log10(breaks = seq(0, 20, 1))