Code
tibble(LAST_DOWNLOAD = as.Date(file.info("~/Library/Mobile\ Documents/com~apple~CloudDocs/website/data/eurostat/mar_mg_am_pvh.RData")$mtime)) %>%
print_table_conditional()
LAST_DOWNLOAD |
---|
2024-10-08 |
Data - Eurostat
tibble(LAST_DOWNLOAD = as.Date(file.info("~/Library/Mobile\ Documents/com~apple~CloudDocs/website/data/eurostat/mar_mg_am_pvh.RData")$mtime)) %>%
print_table_conditional()
LAST_DOWNLOAD |
---|
2024-10-08 |
LAST_COMPILE |
---|
2024-11-05 |
%>%
mar_mg_am_pvh group_by(time) %>%
summarise(Nobs = n()) %>%
arrange(desc(time)) %>%
head(1) %>%
print_table_conditional()
time | Nobs |
---|---|
2022 | 116 |
%>%
mar_mg_am_pvh left_join(loadstat, by = "loadstat") %>%
group_by(loadstat, Loadstat) %>%
summarise(Nobs = n()) %>%
arrange(-Nobs) %>%
if (is_html_output()) print_table(.) else .} {
loadstat | Loadstat | Nobs |
---|---|---|
TOTAL | Total loaded and empty | 1089 |
EMPTY | Empty | 1085 |
%>%
mar_mg_am_pvh left_join(unit, by = "unit") %>%
group_by(unit, Unit) %>%
summarise(Nobs = n()) %>%
arrange(-Nobs) %>%
if (is_html_output()) print_table(.) else .} {
unit | Unit | Nobs |
---|---|---|
THS_TEU | Thousand twenty-foot equivalent unit (TEU) | 1124 |
RT_PRE | Growth rate on previous period (t/t-1) | 1050 |
%>%
mar_mg_am_pvh left_join(rep_mar, by = "rep_mar") %>%
group_by(rep_mar, Rep_mar) %>%
summarise(Nobs = n()) %>%
arrange(-Nobs) %>%
print_table_conditional()
%>%
mar_mg_am_pvh group_by(time) %>%
summarise(Nobs = n()) %>%
if (is_html_output()) datatable(., filter = 'top', rownames = F) else .} {
i_g("bib/industrie/top-20-ports.png")
%>%
mar_mg_am_pvh filter(unit == "THS_TEU",
== "2019",
time == "TOTAL") %>%
loadstat left_join(rep_mar, by = "rep_mar") %>%
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",
== "2020",
time == "TOTAL") %>%
loadstat left_join(rep_mar, by = "rep_mar") %>%
select(rep_mar, Rep_mar, values) %>%
arrange(-values) %>%
if (is_html_output()) datatable(., filter = 'top', rownames = F, escape = F) else .} {
%>%
mar_mg_am_pvh left_join(rep_mar, by = "rep_mar") %>%
filter(loadstat == "TOTAL",
== "THS_TEU",
unit %in% c("Rotterdam", "Antwerpen", "Hamburg", "Marseille")) %>%
Rep_mar %>%
year_to_date mutate(values = values / 10^3) %>%
+ geom_line(aes(x = date, y = values, color = Rep_mar)) +
ggplot 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 left_join(rep_mar, by = "rep_mar") %>%
filter(loadstat == "TOTAL",
== "THS_TEU",
unit %in% c("Rotterdam", "Antwerpen", "Hamburg")) %>%
Rep_mar %>%
year_to_date mutate(values = values / 10^3) %>%
+ geom_line(aes(x = date, y = values, color = Rep_mar)) +
ggplot 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 left_join(rep_mar, by = "rep_mar") %>%
filter(loadstat == "TOTAL",
== "THS_TEU",
unit %in% c("Peiraias", "Valencia", "Algeciras")) %>%
Rep_mar %>%
year_to_date mutate(values = values / 10^3) %>%
+ geom_line(aes(x = date, y = values, color = Rep_mar)) +
ggplot 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 left_join(rep_mar, by = "rep_mar") %>%
filter(loadstat == "TOTAL",
== "THS_TEU",
unit %in% c("Bremerhaven", "Felixstowe", "Barcelona")) %>%
Rep_mar %>%
year_to_date mutate(values = values / 10^3) %>%
+ geom_line(aes(x = date, y = values, color = Rep_mar)) +
ggplot 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 left_join(rep_mar, by = "rep_mar") %>%
filter(loadstat == "TOTAL",
== "THS_TEU",
unit %in% c("Ambarli", "Gioia Tauro", "Le Havre")) %>%
Rep_mar %>%
year_to_date mutate(values = values / 10^3) %>%
+ geom_line(aes(x = date, y = values, color = Rep_mar)) +
ggplot 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 left_join(rep_mar, by = "rep_mar") %>%
filter(loadstat == "TOTAL",
== "THS_TEU",
unit %in% c("Rotterdam", "Antwerpen", "Hamburg",
Rep_mar "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"))) %>%
+ geom_line(aes(x = date, y = values, color = Rep_mar)) +
ggplot 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 left_join(rep_mar, by = "rep_mar") %>%
filter(loadstat == "TOTAL",
== "THS_TEU",
unit %in% c("Rotterdam", "Antwerpen", "Hamburg",
Rep_mar "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"))) %>%
+ geom_line(aes(x = date, y = values, color = Rep_mar)) +
ggplot 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))