Balance des paiements - 6ème manuel
Données - BDF
Info
Structure
| source | dataset | Title | .html | .rData |
|---|---|---|---|---|
| bdf | BPM6 | Balance des paiements - 6ème manuel | 2026-07-24 | 2026-07-24 |
| eurostat | bop_iip6_q | NA | NA | NA |
Balance des Paiements de la France
Novembre 2024
Octobre 2024
Solde des transactions courantes
Code
ig_b("bdf", "FR_Stat_Info_Balance_des_paiements_de_la_France_202410", "balance-courante")
Solde des opérations financières
Code
ig_b("bdf", "FR_Stat_Info_Balance_des_paiements_de_la_France_202410", "solde-des-operations-financieres")
Janvier 2024
Compte Courant
Table
Code
ig_b("bdf", "BDP_FRA_2284_fr__BDP_Stat_Info_janvier_2024_FR", "table1")
Figure
Code
ig_b("bdf", "BDP_FRA_2284_fr__BDP_Stat_Info_janvier_2024_FR", "figure1")
Compte Financier
Table
Code
ig_b("bdf", "BDP_FRA_2284_fr__BDP_Stat_Info_janvier_2024_FR", "table2")
Figure
Code
ig_b("bdf", "BDP_FRA_2284_fr__BDP_Stat_Info_janvier_2024_FR", "figure2")
Novembre 2021
Code
ig_b("bdf", "bdp_fra_2241_fr_bdp_stat_info_septembre_2021_fr", "comptes")
Mai 2020
Code
ig_b("bdf", "BPM6-2021-07")
Novembre 2020
Code
ig_b("bdf", "BPM6-2020-11-compte")
Compte financier vs compte courant, Différence
Compte financier et compte courant
Code
BPM6 %>%
filter(variable == "BPM6.M.N.FR.W1.S1.S1.T.N.FA._T.F._Z.EUR._T.V.N.ALL" |
variable == "BPM6.M.S.FR.W1.S1.S1.T.B.CA._Z._Z._Z.EUR._T._X.N.ALL") %>%
group_by(Accounting_entry) %>%
arrange(date) %>%
mutate(value = zoo::rollsum(x = value, 12, align = "right", fill = NA)) %>%
na.omit %>%
mutate(Int_acc_item = ifelse(Int_acc_item == "Transactions courantes", "Compte de transactions courantes", Int_acc_item)) %>%
ggplot + geom_line(aes(x = date, y = value/1000, color = Int_acc_item)) +
scale_x_date(breaks = "1 year",
labels = date_format("%Y")) +
scale_y_continuous(labels = dollar_format(pre = "", su = " Md€"),
breaks = seq(-300000, 300000, 10000)/1000) +
theme_minimal() + xlab("") + ylab("Cumul sur 12 mois") +
theme(legend.position = c(0.2, 0.3),
legend.title = element_blank(),
legend.direction = "vertical") +
geom_label(data = . %>% filter(date == max(date)),
aes(x = date, y = value/1000, label = paste0(round(value/1000, 1)), color = Int_acc_item)) +
geom_hline(yintercept = 0, linetype = "dashed")
Différence
Code
BPM6 %>%
filter(variable == "BPM6.M.N.FR.W1.S1.S1.T.N.FA._T.F._Z.EUR._T.V.N.ALL" |
variable == "BPM6.M.S.FR.W1.S1.S1.T.B.CA._Z._Z._Z.EUR._T._X.N.ALL") %>%
group_by(Accounting_entry) %>%
arrange(date) %>%
mutate(value = zoo::rollsum(x = value, 12, align = "right", fill = NA)) %>%
ungroup %>%
select(date, value, Int_acc_item) %>%
na.omit %>%
spread(Int_acc_item, value) %>%
mutate(`Différence` = `Compte financier` - `Transactions courantes`) %>%
gather(Int_acc_item, value, -date) %>%
ggplot + geom_line(aes(x = date, y = value/1000, color = Int_acc_item)) +
scale_x_date(breaks = "1 year",
labels = date_format("%Y")) +
scale_y_continuous(labels = dollar_format(pre = ""),
breaks = seq(-300000, 300000, 10000)/1000) +
theme_minimal() + xlab("") + ylab("") +
theme(legend.position = c(0.2, 0.3),
legend.title = element_blank(),
legend.direction = "vertical") +
geom_label(data = . %>% filter(date == max(date)),
aes(x = date, y = value/1000, label = round(value/1000, 1), color = Int_acc_item))
Investissement direct étranger
Flux
All
Monthly
Code
BPM6 %>%
filter(variable == "BPM6.M.N.FR.W1.S1.S1.T.A.FA.D.F._Z.EUR._T.V.N.ALL" |
variable == "BPM6.M.N.FR.W1.S1.S1.T.L.FA.D.F._Z.EUR._T.V.N.ALL" |
variable == "BPM6.M.N.FR.W1.S1.S1.T.N.FA.D.F._Z.EUR._T.V.N.ALL") %>%
group_by(Accounting_entry) %>%
arrange(date) %>%
mutate(value = zoo::rollsum(x = value, 36, align = "right", fill = NA)/3) %>%
na.omit %>%
ggplot + geom_line(aes(x = date, y = value, color = Accounting_entry)) +
scale_x_date(breaks = "1 year",
labels = date_format("%Y")) +
scale_y_continuous(labels = dollar_format(pre = ""),
breaks = seq(-10000, 300000, 5000)) +
theme_minimal() + xlab("") + ylab("") +
theme(legend.position = c(0.2, 0.8),
legend.title = element_blank(),
legend.direction = "vertical")
Quarterly
Code
BPM6 %>%
filter(variable == "BPM6.Q.N.FR.W1.S1.S1.T.A.FA.D.F._Z.EUR._T.V.N.ALL" |
variable == "BPM6.Q.N.FR.W1.S1.S1.T.L.FA.D.F._Z.EUR._T.V.N.ALL" |
variable == "BPM6.Q.N.FR.W1.S1.S1.T.N.FA.D.F._Z.EUR._T.V.N.ALL") %>%
group_by(Accounting_entry) %>%
arrange(date) %>%
mutate(value = zoo::rollsum(x = value, 12, align = "right", fill = NA)/3) %>%
na.omit %>%
ggplot + geom_line(aes(x = date, y = value, color = Accounting_entry)) +
scale_x_date(breaks = "1 year",
labels = date_format("%Y")) +
scale_y_continuous(labels = dollar_format(pre = ""),
breaks = seq(-10000, 300000, 5000)) +
theme_minimal() + xlab("") + ylab("") +
theme(legend.position = c(0.2, 0.8),
legend.title = element_blank(),
legend.direction = "vertical")
Annual
Code
BPM6 %>%
filter(variable == "BPM6.A.N.FR.W1.S1.S1.T.A.FA.D.F._Z.EUR._T.V.N.ALL" |
variable == "BPM6.A.N.FR.W1.S1.S1.T.L.FA.D.F._Z.EUR._T.V.N.ALL" |
variable == "BPM6.A.N.FR.W1.S1.S1.T.N.FA.D.F._Z.EUR._T.V.N.ALL") %>%
group_by(Accounting_entry) %>%
arrange(date) %>%
mutate(value = zoo::rollsum(x = value, 4, align = "right", fill = NA)/4) %>%
na.omit %>%
ggplot + geom_line(aes(x = date, y = value, color = Accounting_entry)) +
scale_x_date(breaks = "1 year",
labels = date_format("%Y")) +
scale_y_continuous(labels = dollar_format(pre = ""),
breaks = seq(-10000, 300000, 5000)) +
theme_minimal() + xlab("") + ylab("") +
theme(legend.position = c(0.2, 0.8),
legend.title = element_blank(),
legend.direction = "vertical")
2017
Code
BPM6 %>%
filter(variable == "BPM6.M.N.FR.W1.S1.S1.T.A.FA.D.F._Z.EUR._T.V.N.ALL" |
variable == "BPM6.M.N.FR.W1.S1.S1.T.L.FA.D.F._Z.EUR._T.V.N.ALL" |
variable == "BPM6.M.N.FR.W1.S1.S1.T.N.FA.D.F._Z.EUR._T.V.N.ALL",
date >= as.Date("2017-01-01")) %>%
arrange(desc(date)) %>%
ggplot + geom_line(aes(x = date, y = value, color = Accounting_entry)) +
scale_x_date(breaks = "1 year",
labels = date_format("%Y")) +
theme_minimal() + xlab("") + ylab("") +
theme(legend.position = c(0.2, 0.2),
legend.title = element_blank(),
legend.direction = "vertical")
Compte de transactions courantes
Biens, Services, Biens & Services
Annual
Code
BPM6 %>%
filter(variable == "BPM6.A.N.FR.W1.S1.S1.T.B.G._Z._Z._Z.EUR._T._X.N.ALL" |
variable == "BPM6.A.N.FR.W1.S1.S1.T.B.GS._Z._Z._Z.EUR._T._X.N.ALL" |
variable == "BPM6.A.N.FR.W1.S1.S1.T.B.S._Z._Z._Z.EUR._T._X.N.ALL" |
variable == "BPM6.A.N.FR.W1.S1.S1.T.B.CA._Z._Z._Z.EUR._T._X.N.ALL") %>%
left_join(gdp, by = "date") %>%
ggplot + geom_line(aes(x = date, y = value /gdp / 1000, color = Int_acc_item)) +
theme_minimal() +
scale_x_date(breaks = "2 years",
labels = date_format("%Y")) +
theme(legend.position = c(0.2, 0.2),
legend.title = element_blank(),
legend.direction = "vertical") +
xlab("") + ylab("Biens, Services, Biens et Services (Net)") +
scale_y_continuous(breaks = 0.01*seq(-200, 200, 1),
labels = percent_format(accuracy = 1))
Quarterly
Code
BPM6 %>%
filter(variable %in%c("BPM6.Q.N.FR.W1.S1.S1.T.B.GS._Z._Z._Z.EUR._T._X.N.ALL",
"BPM6.Q.N.FR.W1.S1.S1.T.B.G._Z._Z._Z.EUR._T._X.N.ALL",
"BPM6.Q.N.FR.W1.S1.S1.T.B.S._Z._Z._Z.EUR._T._X.N.ALL",
"BPM6.Q.N.FR.W1.S1.S1.T.B.CA._Z._Z._Z.EUR._T._X.N.ALL")) %>%
left_join(gdp_quarterly, by = "date") %>%
ggplot + geom_line(aes(x = date, y = value/gdp, color = Int_acc_item)) +
theme_minimal() +
scale_x_date(breaks = "2 years",
labels = date_format("%Y")) +
theme(legend.position = c(0.2,0.2),
legend.title = element_blank(),
legend.direction = "vertical") +
xlab("") + ylab("Balance") +
scale_y_continuous(breaks = 0.01*seq(-200, 200, 1),
labels = percent_format(accuracy = 1))
Monthly
Par mois
Code
BPM6 %>%
filter(variable == "BPM6.M.S.FR.W1.S1.S1.T.B.GS._Z._Z._Z.EUR._T._X.N.ALL" |
variable == "BPM6.M.S.FR.W1.S1.S1.T.B.G._Z._Z._Z.EUR._T._X.N.ALL" |
variable == "BPM6.M.S.FR.W1.S1.S1.T.B.S._Z._Z._Z.EUR._T._X.N.ALL" |
variable == "BPM6.M.S.FR.W1.S1.S1.T.B.CA._Z._Z._Z.EUR._T._X.N.ALL") %>%
ggplot + geom_line(aes(x = date, y = value / 1000, color = Int_acc_item)) +
theme_minimal() +
scale_x_date(breaks = "1 year",
labels = date_format("%Y")) +
theme(legend.position = c(0.2,0.9),
legend.title = element_blank(),
legend.direction = "vertical") +
xlab("") + ylab("Par mois") +
scale_y_continuous(breaks = seq(-200, 200, 2),
labels = dollar_format(suffix = " Md€", accuracy = 1, prefix = ""))
Cumul sur 12 mois
Code
BPM6 %>%
filter(variable == "BPM6.M.S.FR.W1.S1.S1.T.B.GS._Z._Z._Z.EUR._T._X.N.ALL" |
variable == "BPM6.M.S.FR.W1.S1.S1.T.B.G._Z._Z._Z.EUR._T._X.N.ALL" |
variable == "BPM6.M.S.FR.W1.S1.S1.T.B.S._Z._Z._Z.EUR._T._X.N.ALL" |
variable == "BPM6.M.S.FR.W1.S1.S1.T.B.CA._Z._Z._Z.EUR._T._X.N.ALL") %>%
group_by(Int_acc_item) %>%
arrange(desc(date)) %>%
mutate(value = zoo::rollsum(value, 12, align = "left", fill = NA)) %>%
na.omit %>%
ggplot + geom_line(aes(x = date, y = value / 1000, color = Int_acc_item)) +
theme_minimal() +
scale_x_date(breaks = "1 year",
labels = date_format("%Y")) +
theme(legend.position = c(0.3, 0.2),
legend.title = element_blank(),
legend.direction = "vertical") +
xlab("") + ylab("Cumul sur 12 mois") +
scale_y_continuous(breaks = seq(-200, 200, 10),
labels = dollar_format(suffix = " Md€", accuracy = 1, prefix = "")) +
geom_hline(yintercept = 0, linetype = "dashed") +
geom_label_repel(data = . %>% filter(date == max(date)),
aes(x = date, y = value/1000, color = Int_acc_item, label = round(value/1000, digits = 1)))
Balance des services
BPM6.M.S.FR.W1.S1.S1.T.B.S._Z._Z._Z.EUR._T._X.N.ALL (Services) BPM6.M.S.FR.W1.S1.S1.T.B.SXD._Z._Z._Z.EUR._T._X.N.ALL (Services hors voyages) BPM6.M.S.FR.W1.S1.S1.T.B.SC._Z._Z._Z.EUR._T._X.N.ALL (Services - Transport) BPM6.M.N.FR.W1.S1.S1.T.D.SD._Z._Z._Z.EUR._T._X.N.ALL (Services, Voyages)
Cumul sur 12 mois
Code
BPM6 %>%
# Services
filter(variable == "BPM6.M.S.FR.W1.S1.S1.T.B.S._Z._Z._Z.EUR._T._X.N.ALL" |
# Services hors voyages
variable == "BPM6.M.S.FR.W1.S1.S1.T.B.SXD._Z._Z._Z.EUR._T._X.N.ALL" |
# Services - Transport
variable == "BPM6.M.S.FR.W1.S1.S1.T.B.SC._Z._Z._Z.EUR._T._X.N.ALL" |
# Services, Voyages
variable == "BPM6.M.N.FR.W1.S1.S1.T.D.SD._Z._Z._Z.EUR._T._X.N.ALL") %>%
group_by(Int_acc_item) %>%
arrange(desc(date)) %>%
mutate(value = zoo::rollsum(value, 12, align = "left", fill = NA)) %>%
na.omit %>%
ggplot + geom_line(aes(x = date, y = value / 1000, color = Int_acc_item)) +
theme_minimal() +
scale_x_date(breaks = "1 year",
labels = date_format("%Y")) +
theme(legend.position = c(0.3, 0.8),
legend.title = element_blank(),
legend.direction = "vertical") +
xlab("") + ylab("Cumul sur 12 mois") +
scale_y_continuous(breaks = seq(-200, 200, 10),
labels = dollar_format(suffix = " Md€", accuracy = 1, prefix = "")) +
geom_hline(yintercept = 0, linetype = "dashed") +
geom_label_repel(data = . %>% filter(date == max(date)),
aes(x = date, y = value/1000, color = Int_acc_item, label = round(value/1000, digits = 1)))
Cumul sur 12 mois
Code
BPM6 %>%
# Services
filter(variable == "BPM6.M.S.FR.W1.S1.S1.T.B.S._Z._Z._Z.EUR._T._X.N.ALL" |
# Services hors voyages
variable == "BPM6.M.S.FR.W1.S1.S1.T.B.SXD._Z._Z._Z.EUR._T._X.N.ALL" |
# Services, Voyages
variable == "BPM6.M.N.FR.W1.S1.S1.T.B.SD._Z._Z._Z.EUR._T._X.N.ALL") %>%
group_by(Int_acc_item) %>%
arrange(desc(date)) %>%
mutate(value = zoo::rollsum(value, 12, align = "left", fill = NA)) %>%
na.omit %>%
ggplot + geom_line(aes(x = date, y = value / 1000, color = Int_acc_item)) +
theme_minimal() +
scale_x_date(breaks = "1 year",
labels = date_format("%Y")) +
theme(legend.position = c(0.3, 0.8),
legend.title = element_blank(),
legend.direction = "vertical") +
xlab("") + ylab("Cumul sur 12 mois") +
scale_y_continuous(breaks = seq(-200, 200, 10),
labels = dollar_format(suffix = " Md€", accuracy = 1, prefix = "")) +
geom_hline(yintercept = 0, linetype = "dashed") +
geom_label_repel(data = . %>% filter(date == max(date)),
aes(x = date, y = value/1000, color = Int_acc_item, label = round(value/1000, digits = 1)))
Balance des biens (Douanes vs. BPM6)
Cumul sur 12 mois
Code
BPM6 %>%
filter(variable == "BPM6.M.S.FR.W1.S1.S1.T.B.G1X._Z._Z._Z.EUR._T._X.N.ALL" |
variable == "BPM6.M.S.FR.W1.S1.S1.T.B.G._Z._Z._Z.EUR._T._X.N.ALL" |
variable == "BPM6.M.S.FR.W1.S1.S1.T.B.GX._Z._Z._Z.EUR._T._X.N.ALL") %>%
group_by(Int_acc_item) %>%
arrange(desc(date)) %>%
mutate(value = zoo::rollsum(value, 12, align = "left", fill = NA)) %>%
na.omit %>%
ggplot + geom_line(aes(x = date, y = value / 1000, color = Int_acc_item)) +
theme_minimal() +
scale_x_date(breaks = "1 year",
labels = date_format("%Y")) +
theme(legend.position = c(0.3, 0.2),
legend.title = element_blank(),
legend.direction = "vertical") +
xlab("") + ylab("Cumul sur 12 mois") +
scale_y_continuous(breaks = seq(-200, 200, 10),
labels = dollar_format(suffix = " Md€", accuracy = 1, prefix = "")) +
geom_hline(yintercept = 0, linetype = "dashed") +
geom_label_repel(data = . %>% filter(date == max(date)),
aes(x = date, y = value/1000, color = Int_acc_item, label = round(value/1000, digits = 1)))
Solde - Services, Transport, Voyage
Annual
Code
BPM6 %>%
filter(variable %in% c("BPM6.A.N.FR.W1.S1.S1.T.B.S._Z._Z._Z.EUR._T._X.N.ALL",
"BPM6.A.N.FR.W1.S1.S1.T.B.SD._Z._Z._Z.EUR._T._X.N.ALL",
"BPM6.A.N.FR.W1.S1.S1.T.B.SC._Z._Z._Z.EUR._T._X.N.ALL",
"BPM6.A.N.FR.W1.S1.S1.T.B.SXCD._Z._Z._Z.EUR._T._X.N.ALL")) %>%
left_join(gdp, by = "date") %>%
ggplot + geom_line(aes(x = date, y = value/gdp / 1000, color = Int_acc_item)) +
theme_minimal() +
scale_x_date(breaks = "1 year",
labels = date_format("%Y")) +
theme(legend.position = c(0.3, 0.85),
legend.title = element_blank(),
legend.direction = "vertical",
axis.text.x = element_text(angle = 45, vjust = 1, hjust = 1)) +
xlab("") + ylab("Balance des Services (% du PIB)") +
scale_y_continuous(breaks = 0.01*seq(-200, 200, .2),
labels = percent_format(accuracy = .1),
limits = 0.01*c(-0.6, 2.2)) +
geom_hline(yintercept = 0, linetype = "dashed")
Quarterly
Code
BPM6 %>%
filter(variable %in% c("BPM6.Q.N.FR.W1.S1.S1.T.B.S._Z._Z._Z.EUR._T._X.N.ALL",
"BPM6.Q.N.FR.W1.S1.S1.T.B.SD._Z._Z._Z.EUR._T._X.N.ALL",
"BPM6.Q.N.FR.W1.S1.S1.T.B.SC._Z._Z._Z.EUR._T._X.N.ALL",
"BPM6.Q.N.FR.W1.S1.S1.T.B.SXCD._Z._Z._Z.EUR._T._X.N.ALL")) %>%
left_join(gdp_quarterly, by = "date") %>%
ggplot + geom_line(aes(x = date, y = value/gdp / 1000, color = Int_acc_item)) +
theme_minimal() +
scale_x_date(breaks = "1 year",
labels = date_format("%Y")) +
theme(legend.position = c(0.2,0.9),
legend.title = element_blank(),
legend.direction = "vertical",
axis.text.x = element_text(angle = 45, vjust = 1, hjust = 1)) +
xlab("") + ylab("Services (Balance)") +
scale_y_continuous(breaks = 0.01*seq(-200, 200, .2),
labels = percent_format(accuracy = .1)) +
geom_hline(yintercept = 0, linetype = "dashed")
Biens
Code
BPM6 %>%
filter(variable == "BPM6.A.N.FR.W1.S1.S1.T.C.G._Z._Z._Z.EUR._T._X.N.ALL" |
variable == "BPM6.A.N.FR.W1.S1.S1.T.D.G._Z._Z._Z.EUR._T._X.N.ALL" |
variable == "BPM6.A.N.FR.W1.S1.S1.T.B.G._Z._Z._Z.EUR._T._X.N.ALL") %>%
left_join(gdp, by = "date") %>%
ggplot + geom_line(aes(x = date, y = value / gdp / 1000, color = Accounting_entry)) +
theme_minimal() +
scale_x_date(breaks = "1 year",
labels = date_format("%Y")) +
theme(legend.position = c(0.2,0.9),
legend.title = element_blank(),
legend.direction = "vertical",
axis.text.x = element_text(angle = 45, vjust = 1, hjust = 1)) +
xlab("") + ylab("Biens") +
scale_y_continuous(breaks = 0.01*seq(-200, 200, 2),
labels = percent_format(accuracy = 1))
Services
Annual
Code
BPM6 %>%
filter(variable == "BPM6.A.N.FR.W1.S1.S1.T.C.S._Z._Z._Z.EUR._T._X.N.ALL" |
variable == "BPM6.A.N.FR.W1.S1.S1.T.D.S._Z._Z._Z.EUR._T._X.N.ALL" |
variable == "BPM6.A.N.FR.W1.S1.S1.T.B.S._Z._Z._Z.EUR._T._X.N.ALL") %>%
ggplot + geom_line(aes(x = date, y = value / 1000, color = Accounting_entry)) +
theme_minimal() +
scale_x_date(breaks = "1 year",
labels = date_format("%Y")) +
theme(legend.position = c(0.2,0.9),
legend.title = element_blank(),
legend.direction = "vertical",
axis.text.x = element_text(angle = 45, vjust = 1, hjust = 1)) +
xlab("") + ylab("Services de Voyage") +
scale_y_continuous(breaks = seq(-200, 2000, 20),
labels = dollar_format(suffix = " Mds €", accuracy = 1, prefix = ""))
Quarterly
Code
BPM6 %>%
filter(variable == "BPM6.Q.N.FR.W1.S1.S1.T.C.SD._Z._Z._Z.EUR._T._X.N.ALL" |
variable == "BPM6.Q.N.FR.W1.S1.S1.T.D.SD._Z._Z._Z.EUR._T._X.N.ALL" |
variable == "BPM6.Q.N.FR.W1.S1.S1.T.B.SD._Z._Z._Z.EUR._T._X.N.ALL") %>%
ggplot + geom_line(aes(x = date, y = value / 1000, color = Accounting_entry)) +
theme_minimal() +
scale_x_date(breaks = "1 year",
labels = date_format("%Y")) +
theme(legend.position = c(0.2,0.9),
legend.title = element_blank(),
legend.direction = "vertical",
axis.text.x = element_text(angle = 45, vjust = 1, hjust = 1)) +
xlab("") + ylab("") +
scale_y_continuous(breaks = seq(-200, 200, 2),
labels = dollar_format(suffix = " Tn €", accuracy = 1, prefix = ""))
Monthly
Code
BPM6 %>%
filter(variable == "BPM6.M.S.FR.W1.S1.S1.T.B.SD._Z._Z._Z.EUR._T._X.N.ALL" |
variable == "BPM6.M.S.FR.W1.S1.S1.T.C.SD._Z._Z._Z.EUR._T._X.N.ALL" |
variable == "BPM6.M.S.FR.W1.S1.S1.T.D.SD._Z._Z._Z.EUR._T._X.N.ALL") %>%
ggplot + geom_line(aes(x = date, y = value / 1000, color = Accounting_entry)) +
theme_minimal() +
scale_x_date(breaks = "1 year",
labels = date_format("%Y")) +
theme(legend.position = c(0.2,0.9),
legend.title = element_blank(),
legend.direction = "vertical") +
xlab("") + ylab("") +
scale_y_continuous(breaks = seq(-200, 200, 2),
labels = dollar_format(suffix = " Tn €", accuracy = 1, prefix = ""))
Services de Transport
Annual
Code
BPM6 %>%
filter(variable == "BPM6.A.N.FR.W1.S1.S1.T.C.SC._Z._Z._Z.EUR._T._X.N.ALL" |
variable == "BPM6.A.N.FR.W1.S1.S1.T.D.SC._Z._Z._Z.EUR._T._X.N.ALL" |
variable == "BPM6.A.N.FR.W1.S1.S1.T.B.SC._Z._Z._Z.EUR._T._X.N.ALL") %>%
ggplot + geom_line(aes(x = date, y = value / 1000, color = Accounting_entry)) +
theme_minimal() +
scale_x_date(breaks = "1 year",
labels = date_format("%Y")) +
theme(legend.position = c(0.2,0.9),
legend.title = element_blank(),
legend.direction = "vertical",
axis.text.x = element_text(angle = 45, vjust = 1, hjust = 1)) +
xlab("") + ylab("Services de Voyage") +
scale_y_continuous(breaks = seq(-200, 200, 5),
labels = dollar_format(suffix = " Mds €", accuracy = 1, prefix = ""))
Quarterly
Code
BPM6 %>%
filter(variable == "BPM6.Q.N.FR.W1.S1.S1.T.C.SD._Z._Z._Z.EUR._T._X.N.ALL" |
variable == "BPM6.Q.N.FR.W1.S1.S1.T.D.SD._Z._Z._Z.EUR._T._X.N.ALL" |
variable == "BPM6.Q.N.FR.W1.S1.S1.T.B.SD._Z._Z._Z.EUR._T._X.N.ALL") %>%
ggplot + geom_line(aes(x = date, y = value / 1000, color = Accounting_entry)) +
theme_minimal() +
scale_x_date(breaks = "1 year",
labels = date_format("%Y")) +
theme(legend.position = c(0.2,0.9),
legend.title = element_blank(),
legend.direction = "vertical",
axis.text.x = element_text(angle = 45, vjust = 1, hjust = 1)) +
xlab("") + ylab("") +
scale_y_continuous(breaks = seq(-200, 200, 2),
labels = dollar_format(suffix = " Tn €", accuracy = 1, prefix = ""))
Monthly
Code
BPM6 %>%
filter(variable == "BPM6.M.S.FR.W1.S1.S1.T.B.SD._Z._Z._Z.EUR._T._X.N.ALL" |
variable == "BPM6.M.S.FR.W1.S1.S1.T.C.SD._Z._Z._Z.EUR._T._X.N.ALL" |
variable == "BPM6.M.S.FR.W1.S1.S1.T.D.SD._Z._Z._Z.EUR._T._X.N.ALL") %>%
ggplot + geom_line(aes(x = date, y = value / 1000, color = Accounting_entry)) +
theme_minimal() +
scale_x_date(breaks = "1 year",
labels = date_format("%Y")) +
theme(legend.position = c(0.2,0.9),
legend.title = element_blank(),
legend.direction = "vertical") +
xlab("") + ylab("") +
scale_y_continuous(breaks = seq(-200, 200, 2),
labels = dollar_format(suffix = " Tn €", accuracy = 1, prefix = ""))
Services de Voyage
Annual
Code
BPM6 %>%
filter(variable == "BPM6.A.N.FR.W1.S1.S1.T.C.SD._Z._Z._Z.EUR._T._X.N.ALL" |
variable == "BPM6.A.N.FR.W1.S1.S1.T.D.SD._Z._Z._Z.EUR._T._X.N.ALL" |
variable == "BPM6.A.N.FR.W1.S1.S1.T.B.SD._Z._Z._Z.EUR._T._X.N.ALL") %>%
ggplot + geom_line(aes(x = date, y = value / 1000, color = Accounting_entry)) +
theme_minimal() +
scale_x_date(breaks = "1 year",
labels = date_format("%Y")) +
theme(legend.position = c(0.2,0.9),
legend.title = element_blank(),
legend.direction = "vertical",
axis.text.x = element_text(angle = 45, vjust = 1, hjust = 1)) +
xlab("") + ylab("Services de Voyage") +
scale_y_continuous(breaks = seq(-200, 200, 5),
labels = dollar_format(suffix = " Mds €", accuracy = 1, prefix = ""))
Quarterly
Code
BPM6 %>%
filter(variable == "BPM6.Q.N.FR.W1.S1.S1.T.C.SD._Z._Z._Z.EUR._T._X.N.ALL" |
variable == "BPM6.Q.N.FR.W1.S1.S1.T.D.SD._Z._Z._Z.EUR._T._X.N.ALL" |
variable == "BPM6.Q.N.FR.W1.S1.S1.T.B.SD._Z._Z._Z.EUR._T._X.N.ALL") %>%
ggplot + geom_line(aes(x = date, y = value / 1000, color = Accounting_entry)) +
theme_minimal() +
scale_x_date(breaks = "1 year",
labels = date_format("%Y")) +
theme(legend.position = c(0.2,0.9),
legend.title = element_blank(),
legend.direction = "vertical",
axis.text.x = element_text(angle = 45, vjust = 1, hjust = 1)) +
xlab("") + ylab("") +
scale_y_continuous(breaks = seq(-200, 200, 2),
labels = dollar_format(suffix = " Tn €", accuracy = 1, prefix = ""))
Monthly
Code
BPM6 %>%
filter(variable == "BPM6.M.S.FR.W1.S1.S1.T.B.SD._Z._Z._Z.EUR._T._X.N.ALL" |
variable == "BPM6.M.S.FR.W1.S1.S1.T.C.SD._Z._Z._Z.EUR._T._X.N.ALL" |
variable == "BPM6.M.S.FR.W1.S1.S1.T.D.SD._Z._Z._Z.EUR._T._X.N.ALL") %>%
ggplot + geom_line(aes(x = date, y = value / 1000, color = Accounting_entry)) +
theme_minimal() +
scale_x_date(breaks = "1 year",
labels = date_format("%Y")) +
theme(legend.position = c(0.2,0.9),
legend.title = element_blank(),
legend.direction = "vertical") +
xlab("") + ylab("") +
scale_y_continuous(breaks = seq(-200, 200, 1),
labels = dollar_format(suffix = " Tn €", accuracy = 1, prefix = ""))
Investissements de portefeuille
Quarterly
Code
BPM6 %>%
filter(variable == "BPM6.Q.N.FR.W1.S1.S1.T.A.FA.P.F._Z.EUR._T.M.N.ALL" |
variable == "BPM6.Q.N.FR.W1.S1.S1.T.N.FA.P.F._Z.EUR._T.M.N.ALL") %>%
ggplot + geom_line(aes(x = date, y = value / 1000, color = Variable)) +
theme_minimal() +
scale_x_date(breaks = "1 year",
labels = date_format("%Y")) +
theme(legend.position = c(0.3,0.1),
legend.title = element_blank(),
legend.direction = "vertical",
axis.text.x = element_text(angle = 45, vjust = 1, hjust = 1)) +
xlab("") + ylab("") +
scale_y_continuous(breaks = seq(-200, 200, 20),
labels = dollar_format(suffix = " Tn €", accuracy = 1, prefix = ""))
Revenus Primaires
Tous
Code
BPM6 %>%
filter(variable == "BPM6.A.N.FR.W1.S1.S1.T.C.IN1._Z._Z._Z.EUR._T._X.N.ALL" |
variable == "BPM6.A.N.FR.W1.S1.S1.T.D.IN1._Z._Z._Z.EUR._T._X.N.ALL" |
variable == "BPM6.A.N.FR.W1.S1.S1.T.B.IN1._Z._Z._Z.EUR._T._X.N.ALL") %>%
ggplot + geom_line(aes(x = date, y = value / 1000, color = Accounting_entry)) +
theme_minimal() +
scale_x_date(breaks = "2 years",
labels = date_format("%Y")) +
theme(legend.position = c(0.2,0.9),
legend.title = element_blank(),
legend.direction = "vertical") +
xlab("") + ylab("Revenus Primaires") +
scale_y_continuous(breaks = seq(-200, 1000, 20),
labels = dollar_format(suffix = " Mds €", accuracy = 1, prefix = ""))
Portefeuille
Code
BPM6 %>%
filter(variable == "BPM6.A.N.FR.W1.S1.S1.T.C.D4P.P.F._Z.EUR._T._X.N.ALL" |
variable == "BPM6.A.N.FR.W1.S1.S1.T.B.D4P.P.F._Z.EUR._T._X.N.ALL" |
variable == "BPM6.A.N.FR.W1.S1.S1.T.D.D4P.P.F._Z.EUR._T._X.N.ALL") %>%
ggplot + geom_line(aes(x = date, y = value / 1000, color = Accounting_entry)) +
theme_minimal() +
scale_x_date(breaks = "1 year",
labels = date_format("%Y")) +
theme(legend.position = c(0.2,0.9),
legend.title = element_blank(),
legend.direction = "vertical",
axis.text.x = element_text(angle = 45, vjust = 1, hjust = 1)) +
xlab("") + ylab("Revenus de portefeuille") +
scale_y_continuous(breaks = seq(-200, 1000, 20),
labels = dollar_format(suffix = " Mds €", accuracy = 1, prefix = ""))
Revenus des autres investissements
Code
BPM6 %>%
filter(variable == "BPM6.A.N.FR.W1.S1.S1.T.C.D4P.O.F._Z.EUR._T._X.N.ALL" |
variable == "BPM6.A.N.FR.W1.S1.S1.T.D.D4P.O.F._Z.EUR._T._X.N.ALL" |
variable == "BPM6.A.N.FR.W1.S1.S1.T.B.D4P.O.F._Z.EUR._T._X.N.ALL") %>%
ggplot + geom_line(aes(x = date, y = value / 1000, color = Accounting_entry)) +
theme_minimal() +
scale_x_date(breaks = "1 year",
labels = date_format("%Y")) +
theme(legend.position = c(0.2,0.9),
legend.title = element_blank(),
legend.direction = "vertical",
axis.text.x = element_text(angle = 45, vjust = 1, hjust = 1)) +
xlab("") + ylab("Revenus de portefeuille") +
scale_y_continuous(breaks = seq(-200, 1000, 10),
labels = dollar_format(suffix = " Mds €", accuracy = 1, prefix = ""))
Revenus d’investissement
Code
BPM6 %>%
filter(variable == "BPM6.A.N.FR.W1.S1.S1.T.B.D4P._T.F._Z.EUR._T._X.N.ALL" |
variable == "BPM6.A.N.FR.W1.S1.S1.T.C.D4P._T.F._Z.EUR._T._X.N.ALL" |
variable == "BPM6.A.N.FR.W1.S1.S1.T.D.D4P._T.F._Z.EUR._T._X.N.ALL") %>%
ggplot + geom_line(aes(x = date, y = value / 1000, color = Accounting_entry)) +
theme_minimal() +
scale_x_date(breaks = "1 year",
labels = date_format("%Y")) +
theme(legend.position = c(0.2,0.9),
legend.title = element_blank(),
legend.direction = "vertical",
axis.text.x = element_text(angle = 45, vjust = 1, hjust = 1)) +
xlab("") + ylab("Revenus d'investissement") +
scale_y_continuous(breaks = seq(-200, 1000, 20),
labels = dollar_format(suffix = " Mds €", accuracy = 1, prefix = ""))
Revenus des investissements directs
Code
BPM6 %>%
filter(variable == "BPM6.A.N.FR.W1.S1.S1.T.B.D4P.D.F._Z.EUR._T._X.N.ALL" |
variable == "BPM6.A.N.FR.W1.S1.S1.T.C.D4P.D.F._Z.EUR._T._X.N.ALL" |
variable == "BPM6.A.N.FR.W1.S1.S1.T.D.D4P.D.F._Z.EUR._T._X.N.ALL") %>%
ggplot + geom_line(aes(x = date, y = value / 1000, color = Accounting_entry)) +
theme_minimal() +
scale_x_date(breaks = "1 year",
labels = date_format("%Y")) +
theme(legend.position = c(0.2,0.9),
legend.title = element_blank(),
legend.direction = "vertical",
axis.text.x = element_text(angle = 45, vjust = 1, hjust = 1)) +
xlab("") + ylab("Revenus des investissements directs") +
scale_y_continuous(breaks = seq(-200, 1000, 10),
labels = dollar_format(suffix = " Mds €", accuracy = 1, prefix = ""))
Balance
Code
BPM6 %>%
filter(variable == "BPM6.A.N.FR.W1.S1.S1.T.B.D4P.D.F._Z.EUR._T._X.N.ALL" |
variable == "BPM6.A.N.FR.W1.S1.S1.T.B.D4P._T.F._Z.EUR._T._X.N.ALL" |
variable == "BPM6.A.N.FR.W1.S1.S1.T.B.D4P.O.F._Z.EUR._T._X.N.ALL" |
variable == "BPM6.A.N.FR.W1.S1.S1.T.B.D4P.P.F._Z.EUR._T._X.N.ALL") %>%
ggplot + geom_line(aes(x = date, y = value / 1000, color = Functional_cat)) +
theme_minimal() + xlab("") + ylab("Revenus primaires") +
scale_x_date(breaks = "1 year",
labels = date_format("%Y")) +
theme(legend.position = c(0.25, 0.85),
legend.title = element_blank(),
legend.direction = "vertical",
axis.text.x = element_text(angle = 45, vjust = 1, hjust = 1)) +
scale_y_continuous(breaks = seq(-200, 1000, 10),
labels = dollar_format(suffix = " Mds €", accuracy = 1, prefix = ""))
Balance
Code
BPM6 %>%
filter(grepl("BPM6.A.N.FR.W1.S1.S1.T.B.D4P.", variable)) %>%
ggplot + geom_line(aes(x = date, y = value / 1000, color = Functional_cat)) +
theme_minimal() + xlab("") + ylab("Revenus primaires") +
scale_x_date(breaks = "1 year",
labels = date_format("%Y")) +
theme(legend.position = c(0.25, 0.85),
legend.title = element_blank(),
legend.direction = "vertical",
axis.text.x = element_text(angle = 45, vjust = 1, hjust = 1)) +
scale_y_continuous(breaks = seq(-200, 1000, 10),
labels = dollar_format(suffix = " Mds €", accuracy = 1, prefix = ""))
Revenus Secondaires
Tous
Code
BPM6 %>%
filter(grepl("BPM6.A.N.FR.W1.S1.S1.T.B.IN2.", variable) |
grepl("BPM6.A.N.FR.W1.S1.S1.T.C.IN2.", variable) |
grepl("BPM6.A.N.FR.W1.S1.S1.T.D.IN2.", variable)) %>%
ggplot + geom_line(aes(x = date, y = value / 1000, color = Accounting_entry)) +
theme_minimal() + xlab("") + ylab("Revenus secondaires") +
scale_x_date(breaks = "1 year",
labels = date_format("%Y")) +
theme(legend.position = c(0.25, 0.85),
legend.title = element_blank(),
legend.direction = "vertical",
axis.text.x = element_text(angle = 45, vjust = 1, hjust = 1)) +
scale_y_continuous(breaks = seq(-200, 1000, 10),
labels = dollar_format(suffix = " Mds €", accuracy = 1, prefix = ""))
Balance
Code
BPM6 %>%
filter(grepl("BPM6.A.N.FR.W1.S1.S1.T.B.IN2.", variable)) %>%
ggplot + geom_line(aes(x = date, y = value / 1000, color = Functional_cat)) +
theme_minimal() + xlab("") + ylab("Revenus secondaires") +
scale_x_date(breaks = "1 year",
labels = date_format("%Y")) +
theme(legend.position = c(0.25, 0.85),
legend.title = element_blank(),
legend.direction = "vertical",
axis.text.x = element_text(angle = 45, vjust = 1, hjust = 1)) +
scale_y_continuous(breaks = seq(-200, 1000, 2),
labels = dollar_format(suffix = " Mds €", accuracy = 1, prefix = ""))
Transactions Courantes
All
Code
BPM6 %>%
filter(FREQ == "M",
INT_ACC_ITEM %in% c("G", "S", "G1X"),
ADJUSTMENT == "S",
REF_SECTOR == "S1",
COUNTERPART_SECTOR == "S1",
FLOW_STOCK_ENTRY == "T",
ACCOUNTING_ENTRY == "B") %>%
ggplot + geom_line(aes(x = date, y = value / 1000, color = Int_acc_item)) +
theme_minimal() +
scale_x_date(breaks = "1 year",
labels = date_format("%Y")) +
theme(legend.position = c(0.3,0.1),
legend.title = element_blank(),
legend.direction = "vertical") +
xlab("") + ylab("") +
scale_y_continuous(breaks = seq(-100, 10, 1),
labels = dollar_format(suffix = " Tn €", accuracy = 1, prefix = ""))
2018-
Code
BPM6 %>%
filter(date >= as.Date("2018-01-01"),
FREQ == "M",
ADJUSTMENT == "S",
COUNTERPART_AREA == "W1",
REF_SECTOR == "S1",
COUNTERPART_SECTOR == "S1",
FLOW_STOCK_ENTRY == "T",
ACCOUNTING_ENTRY == "B",
INT_ACC_ITEM %in% c("G", "S")) %>%
ggplot + geom_line(aes(x = date, y = value / 1000, color = Int_acc_item)) +
theme_minimal() + xlab("") + ylab("") +
scale_x_date(breaks = "3 months",
labels = date_format("%b-%y")) +
theme(legend.position = c(0.3,0.1),
legend.title = element_blank(),
legend.direction = "vertical",
axis.text.x = element_text(angle = 45, vjust = 1, hjust = 1)) +
scale_y_continuous(breaks = seq(-100, 10, 1),
labels = dollar_format(suffix = " Tn €", accuracy = 1, prefix = ""))
Table - Monthly
Code
BPM6 %>%
filter(date == as.Date("2018-01-01"),
FREQ == "M",
ADJUSTMENT == "S",
REF_SECTOR == "S1",
COUNTERPART_SECTOR == "S1",
FLOW_STOCK_ENTRY == "T",
ACCOUNTING_ENTRY == "B") %>%
select(Int_acc_item, Functional_cat, value) %>%
print_table_conditional| Int_acc_item | Functional_cat | value |
|---|---|---|
| NA | NA | NA |
| :------------: | :--------------: | :-----: |
France vis à vis de l’Allemagne
All
Code
BPM6 %>%
filter(FREQ == "A",
COUNTERPART_AREA == "DE",
ACCOUNTING_ENTRY == "B",
INT_ACC_ITEM %in% c("G", "S")) %>%
ggplot + geom_line(aes(x = date, y = value / 1000, color = Int_acc_item)) +
theme_minimal() + xlab("") + ylab("") +
scale_x_date(breaks = "1 year",
labels = date_format("%Y")) +
theme(legend.position = c(0.3,0.1),
legend.title = element_blank(),
legend.direction = "vertical") +
scale_y_continuous(breaks = seq(-40, 10, 1),
labels = dollar_format(suffix = " Bn €", accuracy = 1, prefix = ""))
Biens
Code
load_data("bdf/COUNTERPART_AREA.RData")
BPM6 %>%
filter(FREQ == "A",
COUNTERPART_AREA %in% c("DE", "CN"),
ACCOUNTING_ENTRY == "B",
INT_ACC_ITEM %in% c("G")) %>%
left_join(colors, by = c("Counterpart_area" = "country")) %>%
mutate(value = value / 1000) %>%
mutate(Ref_area = Counterpart_area) %>%
ggplot + geom_line(aes(x = date, y = value, color = color)) +
scale_color_identity() + add_2flags +
theme_minimal() + xlab("") + ylab("") +
scale_x_date(breaks = "1 year",
labels = date_format("%Y")) +
theme(legend.position = c(0.3,0.1),
legend.title = element_blank(),
legend.direction = "vertical") +
scale_y_continuous(breaks = seq(-100, 10, 5),
labels = dollar_format(suffix = "Mds€", accuracy = 1, prefix = ""))
Services
Code
load_data("bdf/COUNTERPART_AREA.RData")
BPM6 %>%
filter(FREQ == "A",
COUNTERPART_AREA %in% c("DE", "CN"),
ACCOUNTING_ENTRY == "B",
INT_ACC_ITEM %in% c("S")) %>%
left_join(colors, by = c("Counterpart_area" = "country")) %>%
mutate(value = value / 1000) %>%
mutate(Ref_area = Counterpart_area) %>%
ggplot + geom_line(aes(x = date, y = value, color = color)) +
scale_color_identity() + add_2flags +
theme_minimal() + xlab("") + ylab("") +
scale_x_date(breaks = "1 year",
labels = date_format("%Y")) +
theme(legend.position = c(0.3,0.1),
legend.title = element_blank(),
legend.direction = "vertical") +
scale_y_continuous(breaks = seq(-40, 10, 1),
labels = dollar_format(suffix = "Mds€", accuracy = 1, prefix = ""))
Biens et Services
Code
load_data("bdf/COUNTERPART_AREA.RData")
BPM6 %>%
filter(FREQ == "A",
COUNTERPART_AREA %in% c("DE", "CN"),
ACCOUNTING_ENTRY == "B",
INT_ACC_ITEM %in% c("S", "G")) %>%
select_if(~ n_distinct(.) > 1) %>%
group_by(date, COUNTERPART_AREA) %>%
summarise(value = sum(value)) %>%
left_join(COUNTERPART_AREA, by = "COUNTERPART_AREA") %>%
left_join(colors, by = c("Counterpart_area" = "country")) %>%
mutate(value = value / 1000) %>%
mutate(Ref_area = Counterpart_area) %>%
ggplot + geom_line(aes(x = date, y = value, color = color)) +
scale_color_identity() + add_2flags +
theme_minimal() + xlab("") + ylab("Déficit Bilatéral avec la France (Source: Banque de France)") +
scale_x_date(breaks = "1 year",
labels = date_format("%Y")) +
theme(legend.position = c(0.3,0.1),
legend.title = element_blank(),
legend.direction = "vertical") +
scale_y_continuous(breaks = seq(-40, 10, 2),
labels = dollar_format(suffix = "Mds€", accuracy = 1, prefix = ""))
France vis à vis de la Chine
All
Quarterly
Code
BPM6 %>%
filter(FREQ == "A",
COUNTERPART_AREA == "CN",
ACCOUNTING_ENTRY == "B",
INT_ACC_ITEM %in% c("G", "S")) %>%
ggplot + geom_line(aes(x = date, y = value / 1000, color = Int_acc_item)) +
theme_minimal() +
scale_x_date(breaks = "1 year",
labels = date_format("%Y")) +
theme(legend.position = c(0.3,0.1),
legend.title = element_blank(),
legend.direction = "vertical") +
xlab("") + ylab("") +
scale_y_continuous(breaks = seq(-100, 10, 5),
labels = dollar_format(suffix = " Mds€", accuracy = 1, prefix = ""))
Quarterly
Code
BPM6 %>%
filter(FREQ == "A",
INT_ACC_ITEM %in% c("G", "S", "G1X"),
COUNTERPART_AREA == "CN",
REF_SECTOR == "S1",
COUNTERPART_SECTOR == "S1",
FLOW_STOCK_ENTRY == "T",
ACCOUNTING_ENTRY == "B",
INT_ACC_ITEM %in% c("G", "S")) %>%
ggplot + geom_line(aes(x = date, y = value / 1000, color = Int_acc_item)) +
theme_minimal() +
scale_x_date(breaks = "1 year",
labels = date_format("%Y")) +
theme(legend.position = c(0.3, 0.1),
legend.title = element_blank(),
legend.direction = "vertical") +
xlab("") + ylab("") +
scale_y_continuous(breaks = seq(-50, 10, 5),
labels = dollar_format(suffix = " Mds€", accuracy = 1, prefix = ""))
Table
Code
BPM6 %>%
filter(date == as.Date("2020-03-31"),
FREQ == "Q",
INT_ACC_ITEM %in% c("G"),
REF_SECTOR == "S1",
COUNTERPART_SECTOR == "S1",
FLOW_STOCK_ENTRY == "T",
ACCOUNTING_ENTRY == "B") %>%
select(COUNTERPART_AREA, Variable, value) %>%
print_table_conditional| COUNTERPART_AREA | Variable | value |
|---|---|---|
| B6 | Transactions courantes - Biens - Ensemble de l'économie - Solde - France vis-à-vis de l'Union européenne (27 membres) - Trimestriel - Brut | -7510 |
| CH | Transactions courantes - Biens - Ensemble de l'économie - Solde - France vis-à-vis Suisse - Brut | 798 |
| J9 | Transactions courantes - Biens - Ensemble de l'économie - Solde - France vis-à-vis hors Zone Euro - Brut | -6778 |
| JP | Transactions courantes - Biens - Ensemble de l'économie - Solde - France vis-à-vis Japon - Brut | -938 |
| W1 | Transactions courantes - Biens - Ensemble de l'économie - Solde - France vis-à-vis Reste du monde - Brut | -13919 |
| I9 | Transactions courantes - Biens - Ensemble de l'économie - Solde - France vis-à-vis Zone Euro - Brut | -7142 |
| CN | Transactions courantes - Biens - Ensemble de l'économie - Solde - France vis-à-vis Chine - Brut | -8069 |
| Q6 | Transactions courantes - Biens - Ensemble de l'économie - Solde -France vis-à-vis de l'Union européenne à 28, hors zone euro à 18, à l?exclusion du Royaume-Uni, du Danemark et de la Suède - Brut | -416 |
| US | Transactions courantes - Biens - Ensemble de l'économie - Solde - France vis-à-vis États Unis - Brut | 651 |
Goods
Code
BPM6 %>%
filter(date >= as.Date("2016-12-31"),
FREQ == "Q",
INT_ACC_ITEM %in% c("G"),
REF_SECTOR == "S1",
COUNTERPART_AREA %in% c("W1", "I8", "J8"),
COUNTERPART_SECTOR == "S1",
FLOW_STOCK_ENTRY == "T",
ACCOUNTING_ENTRY == "B") %>%
ggplot + geom_line(aes(x = date, y = value / 1000, color = Counterpart_area)) +
theme_minimal() + xlab("") + ylab("") +
scale_x_date(breaks = "1 year",
labels = date_format("%Y")) +
theme(legend.position = c(0.6, 0.1),
legend.title = element_blank(),
legend.direction = "vertical") +
scale_y_continuous(breaks = seq(-30, 30, 2),
labels = dollar_format(suffix = " Tn €", accuracy = 1, prefix = ""))
2010
Code
BPM6 %>%
filter(date >= as.Date("2010-12-31"),
FREQ == "Q",
INT_ACC_ITEM %in% c("G"),
REF_SECTOR == "S1",
COUNTERPART_AREA %in% c("W1", "I8", "J8"),
COUNTERPART_SECTOR == "S1",
FLOW_STOCK_ENTRY == "T",
ACCOUNTING_ENTRY == "B") %>%
ggplot + geom_line(aes(x = date, y = value / 1000, color = Counterpart_area)) +
theme_minimal() + xlab("") + ylab("") +
scale_x_date(breaks = "1 year",
labels = date_format("%Y")) +
theme(legend.position = c(0.6, 0.1),
legend.title = element_blank(),
legend.direction = "vertical") +
scale_y_continuous(breaks = seq(-30, 30, 2),
labels = dollar_format(suffix = " Tn €", accuracy = 1, prefix = ""))
Dette Exterieure Nette
Code
BPM6 %>%
filter(variable %in% c("BPM6.A.N.FR.W1.S1.S1.LE.N.FA._T.FNED._Z.PCPIB._T._X.N.ALL",
"BPM6.A.N.FR.W1.S1.S1.LE.N.FA._T.F._Z.PCPIB._T._X.N.ALL")) %>%
ggplot + geom_line(aes(x = date, y = value/100, color = Variable)) +
xlab("") + ylab("") + theme_minimal() +
scale_x_date(breaks = "2 years",
labels = date_format("%Y")) +
scale_y_continuous(breaks = 0.01*seq(-200, 140, 10),
labels = percent_format(accuracy = 1)) +
theme(legend.position = c(0.3, 0.9),
legend.title = element_blank(),
legend.direction = "vertical")