source | dataset | .html | .RData |
---|---|---|---|
insee | CNA-2014-CPEB | 2024-11-05 | 2024-11-05 |
insee | CNA-2014-FBCF-BRANCHE | 2024-10-29 | 2024-11-05 |
insee | CNA-2014-PIB | 2024-10-29 | 2024-11-05 |
Formation brute de capital fixe (FBCF) par branche
Data - Insee
Info
Données sur la macroéconomie en France
source | dataset | .html | .RData |
---|---|---|---|
bdf | CFT | 2024-09-30 | 2024-07-01 |
insee | CNA-2014-CONSO-MEN | 2024-11-05 | 2024-11-05 |
insee | CNA-2014-CONSO-SI | 2024-11-05 | 2024-11-05 |
insee | CNA-2014-CSI | 2024-11-05 | 2024-11-05 |
insee | CNA-2014-FBCF-BRANCHE | 2024-10-29 | 2024-11-05 |
insee | CNA-2014-FBCF-SI | 2024-06-07 | 2024-11-05 |
insee | CNA-2014-PIB | 2024-10-29 | 2024-11-05 |
insee | CNA-2014-RDB | 2024-10-29 | 2024-11-05 |
insee | CNT-2014-CB | 2024-10-29 | 2024-11-05 |
insee | CNT-2014-CSI | 2024-10-29 | 2024-11-05 |
insee | CNT-2014-OPERATIONS | 2024-10-29 | 2024-11-05 |
insee | CNT-2014-PIB-EQB-RF | 2024-10-29 | 2024-11-05 |
insee | CONSO-MENAGES-2014 | 2024-10-29 | 2024-11-05 |
insee | conso-mensuelle | 2024-06-07 | 2023-07-04 |
insee | ICA-2015-IND-CONS | 2024-10-29 | 2024-11-05 |
insee | t_1101 | 2024-10-29 | 2022-01-02 |
insee | t_1102 | 2024-10-29 | 2020-10-30 |
insee | t_1105 | 2024-10-29 | 2020-10-30 |
LAST_UPDATE
Code
`CNA-2014-FBCF-BRANCHE` %>%
group_by(LAST_UPDATE) %>%
summarise(Nobs = n()) %>%
arrange(desc(LAST_UPDATE)) %>%
print_table_conditional()
LAST_UPDATE | Nobs |
---|---|
2023-05-12 | 5984 |
LAST_COMPILE
LAST_COMPILE |
---|
2024-11-05 |
Last
Code
`CNA-2014-FBCF-BRANCHE` %>%
group_by(TIME_PERIOD) %>%
summarise(Nobs = n()) %>%
arrange(desc(TIME_PERIOD)) %>%
head(1) %>%
print_table_conditional()
TIME_PERIOD | Nobs |
---|---|
2021 | 136 |
CNA_ACTIVITE
Code
`CNA-2014-FBCF-BRANCHE` %>%
left_join(CNA_ACTIVITE, by = "CNA_ACTIVITE") %>%
group_by(CNA_ACTIVITE, Cna_activite) %>%
summarise(Nobs = n()) %>%
arrange(-Nobs) %>%
print_table_conditional()
UNIT_MEASURE
Code
`CNA-2014-FBCF-BRANCHE` %>%
group_by(UNIT_MEASURE) %>%
summarise(Nobs = n()) %>%
arrange(-Nobs) %>%
print_table_conditional()
UNIT_MEASURE | Nobs |
---|---|
EUR2014 | 2992 |
EUROS_COURANTS | 2992 |
TIME_PERIOD
Code
`CNA-2014-FBCF-BRANCHE` %>%
group_by(TIME_PERIOD) %>%
summarise(Nobs = n()) %>%
arrange(desc(TIME_PERIOD)) %>%
print_table_conditional()
Decomposition
A5
Code
`CNA-2014-FBCF-BRANCHE` %>%
filter(grepl("A5", CNA_ACTIVITE),
== "EUROS_COURANTS") %>%
UNIT_MEASURE %>%
year_to_date left_join(CNA_ACTIVITE, by = "CNA_ACTIVITE") %>%
select(date, CNA_ACTIVITE, Cna_activite, OBS_VALUE) %>%
left_join(gdp, by = "date") %>%
+ geom_line(aes(x = date, y = OBS_VALUE/gdp, color = Cna_activite)) +
ggplot theme_minimal() + xlab("") + ylab("") +
theme(legend.title = element_blank(),
legend.position = c(0.4, 0.5)) +
scale_x_date(breaks = seq(1950, 2020, 5) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%Y")) +
scale_y_continuous(breaks = 0.01*seq(0, 100, 1),
labels = scales::percent_format(accuracy = 1))
A5 moins services marchands
Code
`CNA-2014-FBCF-BRANCHE` %>%
filter(CNA_ACTIVITE %in% c("A5-AZ", "A5-BE", "A5-FZ", "A5-OQ"),
== "EUROS_COURANTS") %>%
UNIT_MEASURE %>%
year_to_date left_join(CNA_ACTIVITE, by = "CNA_ACTIVITE") %>%
select(date, CNA_ACTIVITE, Cna_activite, OBS_VALUE) %>%
left_join(gdp, by = "date") %>%
+ geom_line(aes(x = date, y = OBS_VALUE/gdp, color = Cna_activite)) +
ggplot theme_minimal() + xlab("") + ylab("") +
theme(legend.title = element_blank(),
legend.position = c(0.4, 0.5)) +
scale_x_date(breaks = seq(1950, 2020, 5) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%Y")) +
scale_y_continuous(breaks = 0.01*seq(0, 100, .5),
labels = scales::percent_format(accuracy = .1))
GU, BE, JZ
Code
`CNA-2014-FBCF-BRANCHE` %>%
filter(CNA_ACTIVITE %in% c("A5-GU", "A10-BE", "A17-JZ"),
== "EUROS_COURANTS") %>%
UNIT_MEASURE %>%
year_to_date left_join(CNA_ACTIVITE, by = "CNA_ACTIVITE") %>%
select(date, CNA_ACTIVITE, Cna_activite, OBS_VALUE) %>%
left_join(gdp, by = "date") %>%
+ geom_line(aes(x = date, y = OBS_VALUE/gdp, color = Cna_activite)) +
ggplot theme_minimal() + xlab("") + ylab("") +
theme(legend.title = element_blank(),
legend.position = c(0.4, 0.5)) +
scale_x_date(breaks = seq(1950, 2020, 5) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%Y")) +
scale_y_continuous(breaks = 0.01*seq(0, 100, 1),
labels = scales::percent_format(accuracy = 1))