| source | dataset | .html | .RData |
|---|---|---|---|
| insee | CNT-2014-CB | 2024-11-16 | 2024-11-17 |
Comptes des branches
Data - Insee
Info
Données sur la macroéconomie en France
| source | dataset | .html | .RData |
|---|---|---|---|
| bdf | CFT | 2024-11-17 | 2024-07-01 |
| insee | CNA-2014-CONSO-MEN | 2024-11-09 | 2024-11-09 |
| insee | CNA-2014-CONSO-SI | 2024-11-09 | 2024-11-09 |
| insee | CNA-2014-CSI | 2024-11-09 | 2024-11-09 |
| insee | CNA-2014-FBCF-BRANCHE | 2024-11-17 | 2024-11-17 |
| insee | CNA-2014-FBCF-SI | 2024-06-07 | 2024-11-17 |
| insee | CNA-2014-PIB | 2024-11-09 | 2024-11-09 |
| insee | CNA-2014-RDB | 2024-11-16 | 2024-11-16 |
| insee | CNT-2014-CB | 2024-11-16 | 2024-11-17 |
| insee | CNT-2014-CSI | 2024-11-17 | 2024-11-17 |
| insee | CNT-2014-OPERATIONS | 2024-11-15 | 2024-11-15 |
| insee | CNT-2014-PIB-EQB-RF | 2024-11-17 | 2024-11-17 |
| insee | CONSO-MENAGES-2014 | 2024-11-17 | 2024-11-17 |
| insee | conso-mensuelle | 2024-06-07 | 2023-07-04 |
| insee | ICA-2015-IND-CONS | 2024-11-17 | 2024-11-16 |
| insee | t_1101 | 2024-11-09 | 2022-01-02 |
| insee | t_1102 | 2024-11-09 | 2020-10-30 |
| insee | t_1105 | 2024-11-09 | 2020-10-30 |
LAST_UPDATE
Code
`CNT-2014-CB` %>%
group_by(LAST_UPDATE) %>%
summarise(Nobs = n()) %>%
arrange(desc(LAST_UPDATE)) %>%
print_table_conditional()| LAST_UPDATE | Nobs |
|---|---|
| 2024-04-30 | 178344 |
LAST_COMPILE
| LAST_COMPILE |
|---|
| 2024-11-17 |
Last
Code
`CNT-2014-CB` %>%
group_by(TIME_PERIOD) %>%
summarise(Nobs = n()) %>%
arrange(desc(TIME_PERIOD)) %>%
head(2) %>%
print_table_conditional()| TIME_PERIOD | Nobs |
|---|---|
| 2024-Q1 | 144 |
| 2023-Q4 | 594 |
Le compte de production décrit la relation entre la production et la consommation intermédiaire nécessaire à cette production. Il a pour solde la valeur ajoutée brute qui mesure la richesse créée lors du processus de production.
Le compte d’exploitation décrit comment la valeur ajoutée brute couvre la rémunération versée aux salariés et les impôts sur la production. Il a pour solde l’excédent brut d’exploitation et le revenu mixte brut qui mesurent le profit d’exploitation des branches.
TITLE_FR
Code
`CNT-2014-CB` %>%
group_by(IDBANK, TITLE_FR) %>%
summarise(Nobs = n()) %>%
arrange(-Nobs) %>%
{if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}INDICATEUR
Code
`CNT-2014-CB` %>%
left_join(INDICATEUR, by = "INDICATEUR") %>%
group_by(INDICATEUR, Indicateur) %>%
summarise(Nobs = n()) %>%
arrange(-Nobs) %>%
{if (is_html_output()) print_table(.) else .}| INDICATEUR | Indicateur | Nobs |
|---|---|---|
| CNT-COMPTE_EXPLOITATION_BRANCHES | Compte d'exploitation des branches | 63000 |
| CNT-COMPTE_PRODUCTION_BRANCHES | Compte de production des branches | 43344 |
| CNT-EMPLOI_INTERIEUR_BRANCHES | Emploi intérieur par branche | 43200 |
| CNT-DUREE_VOLUME_TRAVAIL_BRANCHE | Durée hebdomadaire et volume de travail par branche | 28800 |
VALORISATION
Code
`CNT-2014-CB` %>%
left_join(VALORISATION, by = "VALORISATION") %>%
group_by(VALORISATION, Valorisation) %>%
summarise(Nobs = n()) %>%
arrange(-Nobs) %>%
{if (is_html_output()) print_table(.) else .}| VALORISATION | Valorisation | Nobs |
|---|---|---|
| SO | Sans objet | 135000 |
| L | Volumes aux prix de l'année précédente chaînés | 21672 |
| V | Valeurs aux prix courants | 21672 |
OPERATION
Code
`CNT-2014-CB` %>%
left_join(OPERATION, by = "OPERATION") %>%
group_by(OPERATION, Operation) %>%
summarise(Nobs = n()) %>%
arrange(-Nobs) %>%
{if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}UNIT_MEASURE
Code
`CNT-2014-CB` %>%
group_by(UNIT_MEASURE) %>%
summarise(Nobs = n()) %>%
{if (is_html_output()) print_table(.) else .}| UNIT_MEASURE | Nobs |
|---|---|
| ETP | 21600 |
| EUROS | 106344 |
| HEURES | 28800 |
| INDIVIDUS | 21600 |
CNA_PRODUIT
Code
`CNT-2014-CB` %>%
left_join(CNA_PRODUIT, by = "CNA_PRODUIT") %>%
group_by(CNA_PRODUIT, Cna_produit) %>%
summarise(Nobs = n()) %>%
arrange(-Nobs) %>%
{if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}TIME_PERIOD
Code
`CNT-2014-CB` %>%
group_by(TIME_PERIOD) %>%
summarise(Nobs = n()) %>%
arrange(desc(TIME_PERIOD)) %>%
{if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}Excédent Brut / PIB par branche
All
Code
`CNT-2014-CB` %>%
filter(TIME_PERIOD %in% c("2022-Q4", "2019-Q4", "2006-Q4")) %>%
filter(OPERATION %in% c("B2"),
#INDICATEUR == "CNT-COMPTE_EXPLOITATION_BRANCHES",
VALORISATION %in% c("V", "SO")) %>%
quarter_to_date() %>%
select(date, OPERATION, CNA_PRODUIT, OBS_VALUE) %>%
left_join(gdp_quarterly, by = "date") %>%
mutate(B2_gdp = round(100*OBS_VALUE/gdp, 1)) %>%
left_join(CNA_PRODUIT, by = "CNA_PRODUIT") %>%
select(CNA_PRODUIT, Cna_produit, date, B2_gdp) %>%
spread(date, B2_gdp) %>%
mutate(change = `2022-10-01`-`2006-10-01`) %>%
arrange(-change) %>%
print_table_conditional()| CNA_PRODUIT | Cna_produit | 2006-10-01 | 2019-10-01 | 2022-10-01 | change |
|---|---|---|---|---|---|
| A17-HZ | A17-HZ - Transports et entreposage | 1.0 | 1.3 | 1.8 | 0.8 |
| A17-AZ | A17-AZ - Agriculture, sylviculture et pêche | 1.5 | 1.3 | 1.9 | 0.4 |
| A17-C2 | A17-C2 - Cokéfaction et raffinage | 0.0 | 0.0 | 0.3 | 0.3 |
| A17-GZ | A17-GZ - Commerce ; réparation d'automobiles et de motocycles | 3.2 | 3.3 | 3.5 | 0.3 |
| A17-C1 | A17-C1 - Fabrication de denrées alimentaires, de boissons et de produits à base de tabac | 0.9 | 0.8 | 0.9 | 0.0 |
| A17-OQ | A17-OQ - Administration publique, enseignement, santé humaine et action sociale | 4.3 | 4.5 | 4.3 | 0.0 |
| DSN-CNT | Tertiaire principalement non marchand (OQ) | 4.3 | 4.5 | 4.3 | 0.0 |
| A17-LZ | A17-LZ - Activités immobilières | 9.7 | 9.6 | 9.6 | -0.1 |
| A17-DE | A17-DE - Industries extractives, énergie, eau, gestion des déchets et dépollution | 1.5 | 1.4 | 1.4 | -0.1 |
| A17-FZ | A17-FZ - Construction | 1.8 | 1.9 | 1.7 | -0.1 |
| A17-C3 | A17-C3 - Fabrication d'équipements électriques, électroniques, informatiques ; fabrication de machines | 0.6 | 0.5 | 0.4 | -0.2 |
| A17-C4 | A17-C4 - Fabrication de matériels de transport | 0.6 | 0.7 | 0.4 | -0.2 |
| DI-CNT | Industrie (DE, C1, C2, C3, C4, C5) | 5.6 | 5.2 | 5.3 | -0.3 |
| A17-C5 | A17-C5 - Fabrication d'autres produits industriels | 2.1 | 1.8 | 1.8 | -0.3 |
| DIM-CNT | Industrie manufacturière (C1, C2, C3, C4, C5) | 4.2 | 3.7 | 3.9 | -0.3 |
| A17-RU | A17-RU - Autres activités de services | 0.8 | 0.7 | 0.4 | -0.4 |
| A17-IZ | A17-IZ - Hébergement et restauration | 0.9 | 0.8 | 0.4 | -0.5 |
| A17-JZ | A17-JZ - Information et communication | 2.2 | 1.9 | 1.6 | -0.6 |
| A17-KZ | A17-KZ - Activités financières et d'assurance | 0.9 | 0.8 | 0.3 | -0.6 |
| A17-MN | A17-MN - Activités scientifiques et techniques ; services administratifs et de soutien | 4.0 | 3.7 | 3.3 | -0.7 |
| D-CNT | Ensemble des biens et services | 35.8 | 35.1 | 34.1 | -1.7 |
| DS-CNT | Ensemble des services | 28.7 | 28.5 | 27.0 | -1.7 |
| DSM-CNT | Tertiaire principalement marchand (GZ, HZ, IZ, JZ, KZ, LZ, MN, RU) | 22.7 | 22.1 | 21.0 | -1.7 |
| SMNA-CNT | Ensemble principalement marchand non agricole | 30.1 | 29.2 | 28.0 | -2.1 |
Transports, Energie, Alimentation
All
Code
`CNT-2014-CB` %>%
filter(OPERATION %in% c("B2"),
#INDICATEUR == "CNT-COMPTE_EXPLOITATION_BRANCHES",
CNA_PRODUIT %in% c("A17-DE", "A17-HZ", "A17-C1", "A17-C2"),
VALORISATION %in% c("V", "SO")) %>%
select(OPERATION, CNA_PRODUIT, TIME_PERIOD, OBS_VALUE) %>%
quarter_to_date %>%
spread(OPERATION, OBS_VALUE) %>%
left_join(CNA_PRODUIT, by = "CNA_PRODUIT") %>%
left_join(gdp_quarterly, by = "date") %>%
ggplot + geom_line(aes(x = date, y = B2/gdp, color = Cna_produit)) +
theme_minimal() +
xlab("") + ylab("Excédent brut d'exploitation (% du PIB)") +
theme(legend.position = c(0.5, 0.9),
legend.title = element_blank()) +
scale_y_continuous(breaks = 0.01*seq(-100, 500, 1),
labels = percent_format(accuracy = 1)) +
scale_x_date(breaks = seq(1920, 2100, 10) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%Y"))
2000-
Code
`CNT-2014-CB` %>%
filter(OPERATION %in% c("B2"),
#INDICATEUR == "CNT-COMPTE_EXPLOITATION_BRANCHES",
CNA_PRODUIT %in% c("A17-DE", "A17-HZ", "A17-C1", "A17-C2"),
VALORISATION %in% c("V", "SO")) %>%
select(OPERATION, CNA_PRODUIT, TIME_PERIOD, OBS_VALUE) %>%
quarter_to_date %>%
filter(date >= as.Date("2000-01-01")) %>%
spread(OPERATION, OBS_VALUE) %>%
left_join(CNA_PRODUIT, by = "CNA_PRODUIT") %>%
left_join(gdp_quarterly, by = "date") %>%
ggplot + geom_line(aes(x = date, y = B2/gdp, color = Cna_produit)) +
theme_minimal() +
xlab("") + ylab("Excédent brut d'exploitation (% du PIB)") +
theme(legend.position = c(0.5, 0.9),
legend.title = element_blank()) +
scale_y_continuous(breaks = 0.01*seq(-100, 500, 1),
labels = percent_format(accuracy = 1)) +
scale_x_date(breaks = seq(1920, 2100, 2) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%Y"))
Industrie
All
Code
`CNT-2014-CB` %>%
filter(OPERATION %in% c("B2"),
#INDICATEUR == "CNT-COMPTE_EXPLOITATION_BRANCHES",
CNA_PRODUIT %in% c("A17-C1", "A17-C2", "A17-C3", "A17-C4", "A17-C5"),
VALORISATION %in% c("V", "SO")) %>%
select(OPERATION, CNA_PRODUIT, TIME_PERIOD, OBS_VALUE) %>%
quarter_to_date %>%
spread(OPERATION, OBS_VALUE) %>%
left_join(CNA_PRODUIT, by = "CNA_PRODUIT") %>%
left_join(gdp_quarterly, by = "date") %>%
ggplot + geom_line(aes(x = date, y = B2/gdp, color = Cna_produit)) +
theme_minimal() +
xlab("") + ylab("Excédent brut d'exploitation (% du PIB)") +
theme(legend.position = c(0.5, 0.7),
legend.title = element_blank()) +
scale_y_continuous(breaks = 0.01*seq(-100, 500, 2),
labels = percent_format(accuracy = 1)) +
scale_x_date(breaks = seq(1920, 2100, 10) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%Y"))
2000-
Code
`CNT-2014-CB` %>%
filter(OPERATION %in% c("B2"),
#INDICATEUR == "CNT-COMPTE_EXPLOITATION_BRANCHES",
CNA_PRODUIT %in% c("A17-C1", "A17-C2", "A17-C3", "A17-C4", "A17-C5"),
VALORISATION %in% c("V", "SO")) %>%
select(OPERATION, CNA_PRODUIT, TIME_PERIOD, OBS_VALUE) %>%
quarter_to_date %>%
filter(date >= as.Date("2000-01-01")) %>%
spread(OPERATION, OBS_VALUE) %>%
left_join(CNA_PRODUIT, by = "CNA_PRODUIT") %>%
left_join(gdp_quarterly, by = "date") %>%
ggplot + geom_line(aes(x = date, y = B2/gdp, color = Cna_produit)) +
theme_minimal() +
xlab("") + ylab("Excédent brut d'exploitation (% du PIB)") +
theme(legend.position = c(0.5, 0.5),
legend.title = element_blank()) +
scale_y_continuous(breaks = 0.01*seq(-100, 500, 0.5),
labels = percent_format(accuracy = .1)) +
scale_x_date(breaks = seq(1920, 2100, 2) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%Y"))
Grands ensembles
All
Code
`CNT-2014-CB` %>%
filter(OPERATION %in% c("B2"),
#INDICATEUR == "CNT-COMPTE_EXPLOITATION_BRANCHES",
CNA_PRODUIT %in% c("DI-CNT", "DIM-CNT", "DS-CNT", "DSM-CNT"),
VALORISATION %in% c("V", "SO")) %>%
select(OPERATION, CNA_PRODUIT, TIME_PERIOD, OBS_VALUE) %>%
quarter_to_date %>%
spread(OPERATION, OBS_VALUE) %>%
left_join(CNA_PRODUIT, by = "CNA_PRODUIT") %>%
left_join(gdp_quarterly, by = "date") %>%
ggplot + geom_line(aes(x = date, y = B2/gdp, color = Cna_produit)) +
theme_minimal() +
xlab("") + ylab("Excédent brut d'exploitation (% du PIB)") +
theme(legend.position = c(0.5, 0.9),
legend.title = element_blank()) +
scale_y_continuous(breaks = 0.01*seq(-100, 500, 2),
labels = percent_format(accuracy = 1)) +
scale_x_date(breaks = seq(1920, 2100, 10) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%Y"))
2000-
Code
`CNT-2014-CB` %>%
filter(OPERATION %in% c("B2"),
#INDICATEUR == "CNT-COMPTE_EXPLOITATION_BRANCHES",
CNA_PRODUIT %in% c("DI-CNT", "DIM-CNT", "DS-CNT", "DSM-CNT"),
VALORISATION %in% c("V", "SO")) %>%
select(OPERATION, CNA_PRODUIT, TIME_PERIOD, OBS_VALUE) %>%
quarter_to_date %>%
filter(date >= as.Date("2000-01-01")) %>%
spread(OPERATION, OBS_VALUE) %>%
left_join(CNA_PRODUIT, by = "CNA_PRODUIT") %>%
left_join(gdp_quarterly, by = "date") %>%
ggplot + geom_line(aes(x = date, y = B2/gdp, color = Cna_produit)) +
theme_minimal() +
xlab("") + ylab("Excédent brut d'exploitation (% du PIB)") +
theme(legend.position = c(0.5, 0.5),
legend.title = element_blank()) +
scale_y_continuous(breaks = 0.01*seq(-100, 500, 2),
labels = percent_format(accuracy = 1)) +
scale_x_date(breaks = seq(1920, 2100, 2) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%Y"))
Excédent Brut / VA par branche
All
Code
`CNT-2014-CB` %>%
filter(TIME_PERIOD %in% c("2023-Q1", "2022-Q1")) %>%
filter(OPERATION %in% c("B2", "B1"),
#INDICATEUR == "CNT-COMPTE_EXPLOITATION_BRANCHES",
VALORISATION %in% c("V", "SO")) %>%
select(OPERATION, TIME_PERIOD, CNA_PRODUIT, OBS_VALUE) %>%
spread(OPERATION, OBS_VALUE) %>%
mutate(B2_B1 = round(100*B2/B1, 1)) %>%
left_join(CNA_PRODUIT, by = "CNA_PRODUIT") %>%
select(Cna_produit, TIME_PERIOD, B2_B1) %>%
spread(TIME_PERIOD, B2_B1) %>%
mutate(change = `2023-Q1` - `2022-Q1`) %>%
arrange(change) %>%
print_table_conditional()| Cna_produit | 2022-Q1 | 2023-Q1 | change |
|---|---|---|---|
| A17-IZ - Hébergement et restauration | 27.2 | 15.2 | -12.0 |
| A17-KZ - Activités financières et d'assurance | 17.3 | 9.7 | -7.6 |
| A17-HZ - Transports et entreposage | 43.4 | 36.6 | -6.8 |
| A17-RU - Autres activités de services | 23.5 | 17.1 | -6.4 |
| A17-OQ - Administration publique, enseignement, santé humaine et action sociale | 23.4 | 21.2 | -2.2 |
| Tertiaire principalement non marchand (OQ) | 23.4 | 21.2 | -2.2 |
| A17-JZ - Information et communication | 34.1 | 32.5 | -1.6 |
| Ensemble des services | 36.4 | 35.3 | -1.1 |
| Tertiaire principalement marchand (GZ, HZ, IZ, JZ, KZ, LZ, MN, RU) | 42.1 | 41.0 | -1.1 |
| A17-AZ - Agriculture, sylviculture et pêche | 92.7 | 92.5 | -0.2 |
| A17-MN - Activités scientifiques et techniques ; services administratifs et de soutien | 26.2 | 26.0 | -0.2 |
| A17-GZ - Commerce ; réparation d'automobiles et de motocycles | 35.5 | 35.5 | 0.0 |
| Ensemble des biens et services | 38.0 | 38.3 | 0.3 |
| Ensemble principalement marchand non agricole | 40.9 | 41.6 | 0.7 |
| A17-C2 - Cokéfaction et raffinage | 88.3 | 89.2 | 0.9 |
| A17-C5 - Fabrication d'autres produits industriels | 34.1 | 35.1 | 1.0 |
| A17-LZ - Activités immobilières | 83.0 | 84.3 | 1.3 |
| A17-FZ - Construction | 31.4 | 33.9 | 2.5 |
| Industrie manufacturière (C1, C2, C3, C4, C5) | 33.5 | 39.8 | 6.3 |
| A17-DE - Industries extractives, énergie, eau, gestion des déchets et dépollution | 62.7 | 69.7 | 7.0 |
| A17-C3 - Fabrication d'équipements électriques, électroniques, informatiques ; fabrication de machines | 30.1 | 37.2 | 7.1 |
| Industrie (DE, C1, C2, C3, C4, C5) | 40.0 | 47.2 | 7.2 |
| A17-C4 - Fabrication de matériels de transport | 21.1 | 33.6 | 12.5 |
| A17-C1 - Fabrication de denrées alimentaires, de boissons et de produits à base de tabac | 29.1 | 47.9 | 18.8 |
Total VS Energie
Tous
Code
`CNT-2014-CB` %>%
filter(OPERATION %in% c("B2", "B1"),
#INDICATEUR == "CNT-COMPTE_EXPLOITATION_BRANCHES",
CNA_PRODUIT %in% c("A17-DE", "D-CNT"),
VALORISATION %in% c("V", "SO")) %>%
select(OPERATION, CNA_PRODUIT, TIME_PERIOD, OBS_VALUE) %>%
quarter_to_date %>%
spread(OPERATION, OBS_VALUE) %>%
mutate(profit_share = B2/B1) %>%
left_join(CNA_PRODUIT, by = "CNA_PRODUIT") %>%
#filter(date >= as.Date("1990-01-01")) %>%
ggplot + geom_line(aes(x = date, y = B2/B1, color = Cna_produit)) +
scale_color_manual(values = c("brown", "black")) +
theme_minimal() +
xlab("") + ylab("Taux de marge (% de la VA)") +
theme(legend.position = c(0.4, 0.3),
legend.title = element_blank()) +
scale_y_continuous(breaks = 0.01*seq(-100, 500, 5),
labels = percent_format(accuracy = 1)) +
scale_x_date(breaks = seq(1920, 2100, 5) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%Y")) +
labs(title = "Taux de marge (en % de la Valeur Ajoutée)",
caption = "Source: INSEE, Comptes Trimestriels")
1990-
Code
`CNT-2014-CB` %>%
filter(OPERATION %in% c("B2", "B1"),
#INDICATEUR == "CNT-COMPTE_EXPLOITATION_BRANCHES",
CNA_PRODUIT %in% c("A17-DE", "D-CNT"),
VALORISATION %in% c("V", "SO")) %>%
select(OPERATION, CNA_PRODUIT, TIME_PERIOD, OBS_VALUE) %>%
quarter_to_date %>%
spread(OPERATION, OBS_VALUE) %>%
mutate(profit_share = B2/B1) %>%
left_join(CNA_PRODUIT, by = "CNA_PRODUIT") %>%
filter(date >= as.Date("1990-01-01")) %>%
ggplot + geom_line(aes(x = date, y = B2/B1, color = Cna_produit)) +
scale_color_manual(values = c("brown", "black")) +
theme_minimal() +
xlab("") + ylab("Taux de marge (% de la VA)") +
theme(legend.position = c(0.4, 0.3),
legend.title = element_blank()) +
scale_y_continuous(breaks = 0.01*seq(-100, 500, 5),
labels = percent_format(accuracy = 1)) +
scale_x_date(breaks = seq(1920, 2100, 5) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%Y")) +
labs(title = "Taux de marge (en % de la Valeur Ajoutée)",
caption = "Source: INSEE, Comptes Trimestriels")
Total VS Energie VS Total Hors Energie
Tous
Code
`CNT-2014-CB` %>%
filter(OPERATION %in% c("B2", "B1"),
#INDICATEUR == "CNT-COMPTE_EXPLOITATION_BRANCHES",
CNA_PRODUIT %in% c("A17-DE", "D-CNT"),
VALORISATION %in% c("V", "SO")) %>%
select(OPERATION, CNA_PRODUIT, TIME_PERIOD, OBS_VALUE) %>%
quarter_to_date %>%
spread(CNA_PRODUIT, OBS_VALUE) %>%
mutate(`D-CNT-A17-DE` = `D-CNT` - `A17-DE`) %>%
select(-`A17-DE`) %>%
gather(CNA_PRODUIT, OBS_VALUE, -date, -OPERATION) %>%
spread(OPERATION, OBS_VALUE) %>%
mutate(profit_share = B2/B1) %>%
left_join(CNA_PRODUIT, by = "CNA_PRODUIT") %>%
mutate(Cna_produit = ifelse(CNA_PRODUIT == "D-CNT-A17-DE", "Ensemble des biens et services, sans le secteur énergétique", Cna_produit)) %>%
#filter(date >= as.Date("1990-01-01")) %>%
ggplot + geom_line(aes(x = date, y = B2/B1, color = Cna_produit)) +
theme_minimal() +
xlab("") + ylab("Taux de marge (% de la VA)") +
theme(legend.position = c(0.6, 0.8),
legend.title = element_blank()) +
scale_y_continuous(breaks = 0.01*seq(-100, 500, 1),
labels = percent_format(accuracy = 1)) +
scale_x_date(breaks = seq(1920, 2100, 5) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%Y")) +
labs(title = "Taux de marge (en % de la Valeur Ajoutée)",
caption = "Source: INSEE, Comptes Trimestriels")
1970-
Code
`CNT-2014-CB` %>%
filter(OPERATION %in% c("B2", "B1"),
#INDICATEUR == "CNT-COMPTE_EXPLOITATION_BRANCHES",
CNA_PRODUIT %in% c("A17-DE", "D-CNT"),
VALORISATION %in% c("V", "SO")) %>%
select(OPERATION, CNA_PRODUIT, TIME_PERIOD, OBS_VALUE) %>%
quarter_to_date %>%
spread(CNA_PRODUIT, OBS_VALUE) %>%
mutate(`D-CNT-A17-DE` = `D-CNT` - `A17-DE`) %>%
select(-`A17-DE`) %>%
gather(CNA_PRODUIT, OBS_VALUE, -date, -OPERATION) %>%
spread(OPERATION, OBS_VALUE) %>%
mutate(profit_share = B2/B1) %>%
left_join(CNA_PRODUIT, by = "CNA_PRODUIT") %>%
mutate(Cna_produit = ifelse(CNA_PRODUIT == "D-CNT-A17-DE", "Ensemble des biens et services, sans le secteur énergétique", Cna_produit)) %>%
filter(date >= as.Date("1970-01-01")) %>%
ggplot + geom_line(aes(x = date, y = B2/B1, color = Cna_produit)) +
theme_minimal() +
xlab("") + ylab("Taux de marge (% de la VA)") +
theme(legend.position = c(0.65, 0.2),
legend.title = element_blank()) +
scale_y_continuous(breaks = 0.01*seq(-100, 500, 1),
labels = percent_format(accuracy = 1)) +
scale_x_date(breaks = seq(1920, 2100, 5) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%Y")) +
labs(title = "Taux de marge (en % de la Valeur Ajoutée)",
caption = "Source: INSEE, Comptes Trimestriels")
1990-
Code
`CNT-2014-CB` %>%
filter(OPERATION %in% c("B2", "B1"),
#INDICATEUR == "CNT-COMPTE_EXPLOITATION_BRANCHES",
CNA_PRODUIT %in% c("A17-DE", "D-CNT"),
VALORISATION %in% c("V", "SO")) %>%
select(OPERATION, CNA_PRODUIT, TIME_PERIOD, OBS_VALUE) %>%
quarter_to_date %>%
spread(CNA_PRODUIT, OBS_VALUE) %>%
mutate(`D-CNT-A17-DE` = `D-CNT` - `A17-DE`) %>%
select(-`A17-DE`) %>%
gather(CNA_PRODUIT, OBS_VALUE, -date, -OPERATION) %>%
spread(OPERATION, OBS_VALUE) %>%
mutate(profit_share = B2/B1) %>%
left_join(CNA_PRODUIT, by = "CNA_PRODUIT") %>%
mutate(Cna_produit = ifelse(CNA_PRODUIT == "D-CNT-A17-DE", "Ensemble des biens et services, sans le secteur énergétique", Cna_produit)) %>%
filter(date >= as.Date("1990-01-01")) %>%
ggplot + geom_line(aes(x = date, y = B2/B1, color = Cna_produit)) +
theme_minimal() +
xlab("") + ylab("Taux de marge (% de la VA)") +
theme(legend.position = c(0.3, 0.2),
legend.title = element_blank()) +
scale_y_continuous(breaks = 0.01*seq(-100, 500, 1),
labels = percent_format(accuracy = 1)) +
scale_x_date(breaks = seq(1920, 2100, 2) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%Y")) +
labs(title = "Taux de marge (en % de la Valeur Ajoutée)",
caption = "Source: INSEE, Comptes Trimestriels")
2010-
Code
`CNT-2014-CB` %>%
filter(OPERATION %in% c("B2", "B1"),
#INDICATEUR == "CNT-COMPTE_EXPLOITATION_BRANCHES",
CNA_PRODUIT %in% c("A17-DE", "D-CNT"),
VALORISATION %in% c("V", "SO")) %>%
select(OPERATION, CNA_PRODUIT, TIME_PERIOD, OBS_VALUE) %>%
quarter_to_date %>%
spread(CNA_PRODUIT, OBS_VALUE) %>%
mutate(`D-CNT-A17-DE` = `D-CNT` - `A17-DE`) %>%
select(-`A17-DE`) %>%
gather(CNA_PRODUIT, OBS_VALUE, -date, -OPERATION) %>%
spread(OPERATION, OBS_VALUE) %>%
mutate(profit_share = B2/B1) %>%
left_join(CNA_PRODUIT, by = "CNA_PRODUIT") %>%
mutate(Cna_produit = ifelse(CNA_PRODUIT == "D-CNT-A17-DE", "Ensemble des biens et services, sans le secteur énergétique", Cna_produit)) %>%
filter(date >= as.Date("2010-01-01")) %>%
ggplot + geom_line(aes(x = date, y = B2/B1, color = Cna_produit)) +
theme_minimal() +
xlab("") + ylab("Taux de marge (% de la VA)") +
theme(legend.position = c(0.3, 0.8),
legend.title = element_blank()) +
scale_y_continuous(breaks = 0.01*seq(-100, 500, 1),
labels = percent_format(accuracy = 1)) +
scale_x_date(breaks = seq(1920, 2100, 1) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%Y")) +
labs(title = "Taux de marge (en % de la Valeur Ajoutée)",
caption = "Source: INSEE, Comptes Trimestriels")
Total VS Energie VS Agro-Alimentaire
Tous
% de la branche
Code
`CNT-2014-CB` %>%
filter(OPERATION %in% c("B2", "B1"),
#INDICATEUR == "CNT-COMPTE_EXPLOITATION_BRANCHES",
CNA_PRODUIT %in% c("A17-DE", "D-CNT", "A17-C1"),
VALORISATION %in% c("V", "SO")) %>%
select(OPERATION, CNA_PRODUIT, TIME_PERIOD, OBS_VALUE) %>%
quarter_to_date %>%
spread(OPERATION, OBS_VALUE) %>%
mutate(profit_share = B2/B1) %>%
left_join(CNA_PRODUIT, by = "CNA_PRODUIT") %>%
filter(date >= as.Date("1990-01-01")) %>%
ggplot + geom_line(aes(x = date, y = B2/B1, color = Cna_produit)) +
scale_color_manual(values = c("forestgreen", "brown", "black")) +
theme_minimal() +
xlab("") + ylab("Taux de marge (% de la VA)") +
theme(legend.position = c(0.5, 0.2),
legend.title = element_blank()) +
scale_y_continuous(breaks = 0.01*seq(-100, 500, 5),
labels = percent_format(accuracy = 1),
limits = c(0, 0.85)) +
scale_x_date(breaks = seq(1920, 2100, 5) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%Y")) +
labs(title = "Taux de marge (en % de la Valeur Ajoutée)",
caption = "Source: INSEE, Comptes Trimestriels")
% de la VA
Code
`CNT-2014-CB` %>%
filter(OPERATION %in% c("B1", "B2"),
#INDICATEUR == "CNT-COMPTE_EXPLOITATION_BRANCHES",
CNA_PRODUIT %in% c("A17-DE", "A17-C1"),
VALORISATION %in% c("V", "SO")) %>%
select(OPERATION, CNA_PRODUIT, TIME_PERIOD, OBS_VALUE) %>%
quarter_to_date %>%
spread(OPERATION, OBS_VALUE) %>%
mutate(profit_share = B2/B1) %>%
left_join(CNA_PRODUIT, by = "CNA_PRODUIT") %>%
left_join(gdp_quarterly, by = "date") %>%
ggplot + geom_line(aes(x = date, y = B2/gdp, color = Cna_produit)) +
theme_minimal() +
xlab("") + ylab("Excédent brut d'Exploitation (% du PIB)") +
theme(legend.position = c(0.5, 0.9),
legend.title = element_blank()) +
scale_y_continuous(breaks = 0.01*seq(-100, 500, 0.5),
labels = percent_format(accuracy = .1)) +
scale_x_date(breaks = seq(1920, 2100, 10) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%Y"))
% de la VA
Code
`CNT-2014-CB` %>%
filter(OPERATION %in% c("B1", "B2"),
#INDICATEUR == "CNT-COMPTE_EXPLOITATION_BRANCHES",
CNA_PRODUIT %in% c("A17-DE"),
VALORISATION %in% c("V", "SO")) %>%
select(OPERATION, CNA_PRODUIT, TIME_PERIOD, OBS_VALUE) %>%
quarter_to_date %>%
spread(OPERATION, OBS_VALUE) %>%
left_join(CNA_PRODUIT, by = "CNA_PRODUIT") %>%
left_join(gdp_quarterly, by = "date") %>%
ggplot + geom_line(aes(x = date, y = B2/gdp)) +
theme_minimal() +
xlab("") + ylab("Excédent brut d'Exploitation (% du PIB)") +
theme(legend.position = c(0.5, 0.9),
legend.title = element_blank()) +
scale_y_continuous(breaks = 0.01*seq(-100, 500, 0.5),
labels = percent_format(accuracy = .1)) +
scale_x_date(breaks = seq(1920, 2100, 10) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%Y"))
2010-
% of B1 de la branche
avec 0
Code
`CNT-2014-CB` %>%
filter(OPERATION %in% c("B2", "B1"),
#INDICATEUR == "CNT-COMPTE_EXPLOITATION_BRANCHES",
CNA_PRODUIT %in% c("A17-DE", "D-CNT", "A17-C1"),
VALORISATION %in% c("V", "SO")) %>%
select(OPERATION, CNA_PRODUIT, TIME_PERIOD, OBS_VALUE) %>%
quarter_to_date %>%
spread(OPERATION, OBS_VALUE) %>%
mutate(profit_share = B2/B1) %>%
left_join(CNA_PRODUIT, by = "CNA_PRODUIT") %>%
filter(date >= as.Date("2010-01-01")) %>%
ggplot + geom_line(aes(x = date, y = B2/B1, color = Cna_produit)) +
scale_color_manual(values = c("forestgreen", "brown", "black")) +
theme_minimal() +
xlab("") + ylab("Taux de marge (% de la VA)") +
theme(legend.position = c(0.5, 0.2),
legend.title = element_blank()) +
scale_y_continuous(breaks = 0.01*seq(-100, 500, 5),
labels = percent_format(accuracy = 1),
limits = c(0, 0.75)) +
scale_x_date(breaks = seq(1920, 2100, 1) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%Y")) +
labs(title = "Taux de marge (en % de la Valeur Ajoutée)",
caption = "Source: INSEE, Comptes Trimestriels")
sans 0
Code
`CNT-2014-CB` %>%
filter(OPERATION %in% c("B2", "B1"),
#INDICATEUR == "CNT-COMPTE_EXPLOITATION_BRANCHES",
CNA_PRODUIT %in% c("A17-DE", "D-CNT", "A17-C1"),
VALORISATION %in% c("V", "SO")) %>%
select(OPERATION, CNA_PRODUIT, TIME_PERIOD, OBS_VALUE) %>%
quarter_to_date %>%
spread(OPERATION, OBS_VALUE) %>%
mutate(profit_share = B2/B1) %>%
left_join(CNA_PRODUIT, by = "CNA_PRODUIT") %>%
filter(date >= as.Date("2010-01-01")) %>%
arrange(desc(date)) %>%
ggplot + geom_line(aes(x = date, y = B2/B1, color = Cna_produit)) +
scale_color_manual(values = c("forestgreen", "brown", "black")) +
theme_minimal() +
xlab("") + ylab("Taux de marge (% de la VA)") +
theme(legend.position = c(0.5, 0.8),
legend.title = element_blank()) +
scale_y_continuous(breaks = 0.01*seq(-100, 500, 5),
labels = percent_format(accuracy = 1)) +
scale_x_date(breaks = seq(1920, 2100, 1) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%Y")) +
labs(title = "Taux de marge (en % de la Valeur Ajoutée)",
caption = "Source: INSEE, Comptes Trimestriels") +
geom_text(data = . %>%
filter(date == as.Date("2023-10-01")), aes(x = date, y = B2/B1, label = percent(B2/B1)))
% de la production (définition finance entreprise)
Code
`CNT-2014-CB` %>%
filter(OPERATION %in% c("B2", "P1E"),
#INDICATEUR == "CNT-COMPTE_EXPLOITATION_BRANCHES",
CNA_PRODUIT %in% c("A17-DE", "D-CNT", "A17-C1"),
VALORISATION %in% c("V", "SO")) %>%
select(OPERATION, CNA_PRODUIT, TIME_PERIOD, OBS_VALUE) %>%
quarter_to_date %>%
spread(OPERATION, OBS_VALUE) %>%
mutate(profit_share = B2/P1E) %>%
left_join(CNA_PRODUIT, by = "CNA_PRODUIT") %>%
filter(date >= as.Date("2010-01-01")) %>%
arrange(desc(date)) %>%
ggplot + geom_line(aes(x = date, y = B2/P1E, color = Cna_produit)) +
scale_color_manual(values = c("forestgreen", "brown", "black")) +
theme_minimal() +
xlab("") + ylab("Taux de marge (% de la production)") +
theme(legend.position = c(0.5, 0.8),
legend.title = element_blank()) +
scale_y_continuous(breaks = 0.01*seq(-100, 500, 2),
labels = percent_format(accuracy = 1)) +
scale_x_date(breaks = seq(1920, 2100, 1) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%Y")) +
labs(title = "Taux de marge (en % de la Production)",
caption = "Source: INSEE, Comptes Trimestriels") +
geom_text(data = . %>%
filter(date == as.Date("2023-10-01")), aes(x = date, y = B2/P1E, label = percent(B2/P1E)))
sans 0
Code
`CNT-2014-CB` %>%
filter(OPERATION %in% c("B2", "B1"),
#INDICATEUR == "CNT-COMPTE_EXPLOITATION_BRANCHES",
CNA_PRODUIT %in% c("A17-DE", "D-CNT", "A17-C1"),
VALORISATION %in% c("V", "SO")) %>%
select(OPERATION, CNA_PRODUIT, TIME_PERIOD, OBS_VALUE) %>%
quarter_to_date %>%
spread(OPERATION, OBS_VALUE) %>%
mutate(profit_share = B2/B1) %>%
left_join(CNA_PRODUIT, by = "CNA_PRODUIT") %>%
filter(date >= as.Date("2017-01-01")) %>%
arrange(desc(date)) %>%
ggplot + geom_line(aes(x = date, y = B2/B1, color = Cna_produit)) +
scale_color_manual(values = c("forestgreen", "brown", "black")) +
theme_minimal() +
xlab("") + ylab("Taux de marge (% de la VA)") +
theme(legend.position = c(0.45, 0.85),
legend.title = element_blank()) +
scale_y_continuous(breaks = 0.01*seq(-100, 500, 5),
labels = percent_format(accuracy = 1)) +
scale_x_date(breaks = seq(1920, 2100, 1) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%Y")) +
labs(title = "Taux de marge (en % de la Valeur Ajoutée)",
caption = "Source: INSEE, Comptes Trimestriels") +
geom_text(data = . %>%
filter(date == as.Date("2023-10-01")), aes(x = date, y = B2/B1, label = percent(B2/B1)))
% of B1 de la branche
Code
`CNT-2014-CB` %>%
filter(OPERATION %in% c("B2", "B1"),
#INDICATEUR == "CNT-COMPTE_EXPLOITATION_BRANCHES",
CNA_PRODUIT %in% c( "D-CNT", "A17-C1"),
VALORISATION %in% c("V", "SO")) %>%
select(OPERATION, CNA_PRODUIT, TIME_PERIOD, OBS_VALUE) %>%
quarter_to_date %>%
spread(OPERATION, OBS_VALUE) %>%
mutate(profit_share = B2/B1) %>%
left_join(CNA_PRODUIT, by = "CNA_PRODUIT") %>%
filter(date >= as.Date("2010-01-01")) %>%
ggplot + geom_line(aes(x = date, y = B2/B1, color = Cna_produit)) +
scale_color_manual(values = c("forestgreen", "black")) +
theme_minimal() +
xlab("") + ylab("Taux de marge (% de la VA)") +
theme(legend.position = c(0.5, 0.2),
legend.title = element_blank()) +
scale_y_continuous(breaks = 0.01*seq(-100, 500, 2),
labels = percent_format(accuracy = 1)) +
scale_x_date(breaks = seq(1920, 2100, 1) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%Y")) +
labs(title = "Taux de marge (en % de la Valeur Ajoutée)",
caption = "Source: INSEE, Comptes Trimestriels") +
geom_text(data = . %>%
filter(date == as.Date("2023-10-01")), aes(x = date, y = B2/B1, label = percent(B2/B1), color = Cna_produit))
Avec les biens et services
Code
`CNT-2014-CB` %>%
filter(OPERATION %in% c("B2", "B1"),
#INDICATEUR == "CNT-COMPTE_EXPLOITATION_BRANCHES",
CNA_PRODUIT %in% c( "D-CNT", "A17-C1", "A17-GZ"),
VALORISATION %in% c("V", "SO")) %>%
select(OPERATION, CNA_PRODUIT, TIME_PERIOD, OBS_VALUE) %>%
quarter_to_date %>%
spread(OPERATION, OBS_VALUE) %>%
mutate(profit_share = B2/B1) %>%
left_join(CNA_PRODUIT, by = "CNA_PRODUIT") %>%
filter(date >= as.Date("2010-01-01")) %>%
ggplot + geom_line(aes(x = date, y = B2/B1, color = Cna_produit, linetype = Cna_produit)) +
scale_color_manual(values = c("forestgreen", "brown", "black")) +
theme_minimal() +
xlab("") + ylab("Taux de marge (% de la VA)") +
theme(legend.position = c(0.5, 0.9),
legend.title = element_blank()) +
scale_y_continuous(breaks = 0.01*seq(-100, 500, 2),
labels = percent_format(accuracy = 1)) +
scale_x_date(breaks = seq(1920, 2100, 1) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%Y")) +
labs(title = "Taux de marge (en % de la Valeur Ajoutée)",
caption = "Source: INSEE, Comptes Trimestriels du 1er trimestre 2023")
% de la VA
Code
`CNT-2014-CB` %>%
filter(OPERATION %in% c("B1", "B2"),
#INDICATEUR == "CNT-COMPTE_EXPLOITATION_BRANCHES",
CNA_PRODUIT %in% c("A17-DE", "A17-C1"),
VALORISATION %in% c("V", "SO")) %>%
select(OPERATION, CNA_PRODUIT, TIME_PERIOD, OBS_VALUE) %>%
quarter_to_date %>%
spread(OPERATION, OBS_VALUE) %>%
mutate(profit_share = B2/B1) %>%
left_join(CNA_PRODUIT, by = "CNA_PRODUIT") %>%
filter(date >= as.Date("2010-01-01")) %>%
left_join(gdp_quarterly, by = "date") %>%
ggplot + geom_line(aes(x = date, y = B2/gdp, color = Cna_produit)) +
scale_color_manual(values = c("forestgreen", "brown", "black")) +
theme_minimal() +
xlab("") + ylab("Taux de marge (% de la VA)") +
theme(legend.position = c(0.5, 0.2),
legend.title = element_blank()) +
scale_y_continuous(breaks = 0.01*seq(-100, 500, 5),
labels = percent_format(accuracy = 1)) +
scale_x_date(breaks = seq(1920, 2100, 1) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%Y")) +
labs(title = "Taux de marge (en % de la Valeur Ajoutée)",
caption = "Source: INSEE, Comptes Trimestriels")
Total VS Raffinerie
Code
`CNT-2014-CB` %>%
filter(OPERATION %in% c("B2", "B1"),
#INDICATEUR == "CNT-COMPTE_EXPLOITATION_BRANCHES",
CNA_PRODUIT %in% c("A17-C2", "D-CNT"),
VALORISATION %in% c("V", "SO")) %>%
select(OPERATION, CNA_PRODUIT, TIME_PERIOD, OBS_VALUE) %>%
quarter_to_date %>%
spread(OPERATION, OBS_VALUE) %>%
mutate(profit_share = B2/B1) %>%
left_join(CNA_PRODUIT, by = "CNA_PRODUIT") %>%
filter(date >= as.Date("1990-01-01")) %>%
ggplot + geom_line(aes(x = date, y = B2/B1, color = Cna_produit)) +
scale_color_manual(values = c("brown", "black")) +
theme_minimal() +
xlab("") + ylab("Taux de marge (% de la VA)") +
theme(legend.position = c(0.4, 0.3),
legend.title = element_blank()) +
scale_y_continuous(breaks = 0.01*seq(-100, 500, 5),
labels = percent_format(accuracy = 1),
limits = c(0, 0.75)) +
scale_x_date(breaks = seq(1920, 2100, 5) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%Y"))
Total VS Services de Transport
Code
`CNT-2014-CB` %>%
filter(OPERATION %in% c("B2", "B1"),
#INDICATEUR == "CNT-COMPTE_EXPLOITATION_BRANCHES",
CNA_PRODUIT %in% c("A17-HZ", "D-CNT"),
VALORISATION %in% c("V", "SO")) %>%
select(OPERATION, CNA_PRODUIT, TIME_PERIOD, OBS_VALUE) %>%
quarter_to_date %>%
spread(OPERATION, OBS_VALUE) %>%
mutate(profit_share = B2/B1) %>%
left_join(CNA_PRODUIT, by = "CNA_PRODUIT") %>%
filter(date >= as.Date("1990-01-01")) %>%
ggplot + geom_line(aes(x = date, y = B2/B1, color = Cna_produit)) +
scale_color_manual(values = c("brown", "black")) +
theme_minimal() +
xlab("") + ylab("Taux de marge (% de la VA)") +
theme(legend.position = c(0.4, 0.9),
legend.title = element_blank()) +
scale_y_continuous(breaks = 0.01*seq(-100, 500, 5),
labels = percent_format(accuracy = 1),
limits = c(0, 0.75)) +
scale_x_date(breaks = seq(1920, 2100, 5) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%Y"))
Transports, Energie, Alimentation
Code
`CNT-2014-CB` %>%
filter(OPERATION %in% c("B1", "B2"),
#INDICATEUR == "CNT-COMPTE_EXPLOITATION_BRANCHES",
CNA_PRODUIT %in% c("A17-DE", "A17-HZ", "A17-C1"),
VALORISATION %in% c("V", "SO")) %>%
select(OPERATION, CNA_PRODUIT, TIME_PERIOD, OBS_VALUE) %>%
quarter_to_date %>%
spread(OPERATION, OBS_VALUE) %>%
mutate(profit_share = B2/B1) %>%
left_join(CNA_PRODUIT, by = "CNA_PRODUIT") %>%
left_join(gdp_quarterly, by = "date") %>%
ggplot + geom_line(aes(x = date, y = B2/gdp, color = Cna_produit)) +
theme_minimal() +
xlab("") + ylab("Excédent brut d'exploitation (% du PIB)") +
theme(legend.position = c(0.5, 0.9),
legend.title = element_blank()) +
scale_y_continuous(breaks = 0.01*seq(-100, 500, 1),
labels = percent_format(accuracy = 1)) +
scale_x_date(breaks = seq(1920, 2100, 10) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%Y"))
Services: IZ, KZ, HZ, RU, JZ
All
Code
`CNT-2014-CB` %>%
filter(OPERATION %in% c("B2", "B1"),
#INDICATEUR == "CNT-COMPTE_EXPLOITATION_BRANCHES",
CNA_PRODUIT %in% c("A17-IZ", "A17-KZ", "A17-HZ", "A17-RU", "A17-JZ"),
VALORISATION %in% c("V", "SO")) %>%
select(OPERATION, CNA_PRODUIT, TIME_PERIOD, OBS_VALUE) %>%
quarter_to_date %>%
spread(OPERATION, OBS_VALUE) %>%
mutate(profit_share = B2/B1) %>%
left_join(CNA_PRODUIT, by = "CNA_PRODUIT") %>%
ggplot + geom_line(aes(x = date, y = B2/B1, color = Cna_produit)) +
theme_minimal() +
xlab("") + ylab("") +
theme(legend.position = c(0.5, 0.8),
legend.title = element_blank()) +
scale_y_continuous(breaks = 0.01*seq(-100, 500, 10),
labels = percent_format(accuracy = 1)) +
scale_x_date(breaks = seq(1920, 2100, 10) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%Y"))
2010-
Code
`CNT-2014-CB` %>%
filter(OPERATION %in% c("B2", "B1"),
#INDICATEUR == "CNT-COMPTE_EXPLOITATION_BRANCHES",
CNA_PRODUIT %in% c("A17-IZ", "A17-KZ", "A17-HZ", "A17-RU", "A17-JZ"),
VALORISATION %in% c("V", "SO")) %>%
select(OPERATION, CNA_PRODUIT, TIME_PERIOD, OBS_VALUE) %>%
quarter_to_date %>%
filter(date >= as.Date("2010-01-01")) %>%
spread(OPERATION, OBS_VALUE) %>%
mutate(profit_share = B2/B1) %>%
left_join(CNA_PRODUIT, by = "CNA_PRODUIT") %>%
ggplot + geom_line(aes(x = date, y = B2/B1, color = Cna_produit)) +
theme_minimal() +
xlab("") + ylab("") +
theme(legend.position = c(0.3, 0.8),
legend.title = element_blank()) +
scale_y_continuous(breaks = 0.01*seq(-100, 500, 10),
labels = percent_format(accuracy = 1)) +
scale_x_date(breaks = seq(1920, 2100, 1) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%Y"))
DE, AZ, C1
Code
`CNT-2014-CB` %>%
filter(OPERATION %in% c("B2", "B1"),
#INDICATEUR == "CNT-COMPTE_EXPLOITATION_BRANCHES",
CNA_PRODUIT %in% c("A17-DE", "A17-AZ", "A17-C1"),
VALORISATION %in% c("V", "SO")) %>%
select(OPERATION, CNA_PRODUIT, TIME_PERIOD, OBS_VALUE) %>%
quarter_to_date %>%
spread(OPERATION, OBS_VALUE) %>%
mutate(profit_share = B2/B1) %>%
left_join(CNA_PRODUIT, by = "CNA_PRODUIT") %>%
ggplot + geom_line(aes(x = date, y = B2/B1, color = Cna_produit)) +
theme_minimal() +
xlab("") + ylab("") +
theme(legend.position = c(0.5, 0.2),
legend.title = element_blank()) +
scale_y_continuous(breaks = 0.01*seq(-100, 500, 10),
labels = percent_format(accuracy = 1)) +
scale_x_date(breaks = seq(1920, 2100, 10) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%Y"))
C2, C3, C5
All
Code
`CNT-2014-CB` %>%
filter(OPERATION %in% c("B2", "B1"),
#INDICATEUR == "CNT-COMPTE_EXPLOITATION_BRANCHES",
CNA_PRODUIT %in% c("A17-C5", "A17-C3", "A17-C4"),
VALORISATION %in% c("V", "SO")) %>%
select(OPERATION, CNA_PRODUIT, TIME_PERIOD, OBS_VALUE) %>%
quarter_to_date %>%
spread(OPERATION, OBS_VALUE) %>%
mutate(profit_share = B2/B1) %>%
left_join(CNA_PRODUIT, by = "CNA_PRODUIT") %>%
ggplot + geom_line(aes(x = date, y = B2/B1, color = Cna_produit)) +
theme_minimal() +
xlab("") + ylab("") +
theme(legend.position = c(0.5, 0.2),
legend.title = element_blank()) +
scale_y_continuous(breaks = 0.01*seq(-100, 500, 10),
labels = percent_format(accuracy = 1)) +
scale_x_date(breaks = seq(1920, 2100, 10) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%Y"))
2010-
Code
`CNT-2014-CB` %>%
filter(OPERATION %in% c("B2", "B1"),
#INDICATEUR == "CNT-COMPTE_EXPLOITATION_BRANCHES",
CNA_PRODUIT %in% c("A17-C5", "A17-C3", "A17-C4"),
VALORISATION %in% c("V", "SO")) %>%
select(OPERATION, CNA_PRODUIT, TIME_PERIOD, OBS_VALUE) %>%
quarter_to_date %>%
filter(date >= as.Date("2010-01-01")) %>%
spread(OPERATION, OBS_VALUE) %>%
mutate(profit_share = B2/B1) %>%
left_join(CNA_PRODUIT, by = "CNA_PRODUIT") %>%
ggplot + geom_line(aes(x = date, y = B2/B1, color = Cna_produit)) +
theme_minimal() +
xlab("") + ylab("") +
theme(legend.position = c(0.5, 0.2),
legend.title = element_blank()) +
scale_y_continuous(breaks = 0.01*seq(-100, 500, 10),
labels = percent_format(accuracy = 1)) +
scale_x_date(breaks = seq(1920, 2100, 1) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%Y"))
DI-CNT, DIM-CNT, DS-CNT
All
Code
`CNT-2014-CB` %>%
filter(OPERATION %in% c("B2", "B1"),
#INDICATEUR == "CNT-COMPTE_EXPLOITATION_BRANCHES",
CNA_PRODUIT %in% c("DI-CNT", "DIM-CNT", "DS-CNT"),
VALORISATION %in% c("V", "SO")) %>%
select(OPERATION, CNA_PRODUIT, TIME_PERIOD, OBS_VALUE) %>%
quarter_to_date %>%
spread(OPERATION, OBS_VALUE) %>%
mutate(profit_share = B2/B1) %>%
left_join(CNA_PRODUIT, by = "CNA_PRODUIT") %>%
ggplot + geom_line(aes(x = date, y = B2/B1, color = Cna_produit)) +
theme_minimal() +
xlab("") + ylab("") +
theme(legend.position = c(0.6, 0.8),
legend.title = element_blank()) +
scale_y_continuous(breaks = 0.01*seq(-100, 500, 5),
labels = percent_format(accuracy = 1)) +
scale_x_date(breaks = seq(1920, 2100, 10) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%Y"))
2010-
Code
`CNT-2014-CB` %>%
filter(OPERATION %in% c("B2", "B1"),
#INDICATEUR == "CNT-COMPTE_EXPLOITATION_BRANCHES",
CNA_PRODUIT %in% c("DI-CNT", "DIM-CNT", "DS-CNT"),
VALORISATION %in% c("V", "SO")) %>%
select(OPERATION, CNA_PRODUIT, TIME_PERIOD, OBS_VALUE) %>%
quarter_to_date %>%
filter(date >= as.Date("2010-01-01")) %>%
spread(OPERATION, OBS_VALUE) %>%
mutate(profit_share = B2/B1) %>%
left_join(CNA_PRODUIT, by = "CNA_PRODUIT") %>%
ggplot + geom_line(aes(x = date, y = B2/B1, color = Cna_produit)) +
theme_minimal() +
xlab("") + ylab("") +
theme(legend.position = c(0.6, 0.8),
legend.title = element_blank()) +
scale_y_continuous(breaks = 0.01*seq(-100, 500, 1),
labels = percent_format(accuracy = 1)) +
scale_x_date(breaks = seq(1920, 2100, 1) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%Y"))
C1, C2, C3, C4, C5
2017T2-
Code
`CNT-2014-CB` %>%
filter(CNA_PRODUIT %in% c("A17-C1", "A17-C2", "A17-C3", "A17-C4", "A17-C5"),
OPERATION == "B1",
VALORISATION == "L") %>%
select_if(~ n_distinct(.) > 1) %>%
quarter_to_date %>%
left_join(CNA_PRODUIT, by = "CNA_PRODUIT") %>%
filter(date >= as.Date("2017-04-01")) %>%
group_by(CNA_PRODUIT) %>%
mutate(OBS_VALUE = 100*OBS_VALUE / OBS_VALUE[date == as.Date("2017-04-01")]) %>%
ggplot + geom_line(aes(x = date, y = OBS_VALUE, color = Cna_produit)) +
xlab("") + ylab("") + theme_minimal() +
scale_x_date(breaks = seq.Date(from = as.Date("2017-04-01"), to = as.Date("2023-10-01"), by = "6 months"),
labels = date_format("%b %y")) +
scale_y_log10(breaks = seq(0, 400, 20)) +
theme(legend.position = c(0.5, 0.8),
legend.title = element_blank())
2019T4-
Code
`CNT-2014-CB` %>%
filter(CNA_PRODUIT %in% c("A17-C1", "A17-C2", "A17-C3", "A17-C4", "A17-C5"),
OPERATION == "B1",
VALORISATION == "L") %>%
select_if(~ n_distinct(.) > 1) %>%
quarter_to_date %>%
left_join(CNA_PRODUIT, by = "CNA_PRODUIT") %>%
filter(date >= as.Date("2019-10-01")) %>%
group_by(CNA_PRODUIT) %>%
mutate(OBS_VALUE = 100*OBS_VALUE / OBS_VALUE[date == as.Date("2019-10-01")]) %>%
ggplot + geom_line(aes(x = date, y = OBS_VALUE, color = Cna_produit)) +
xlab("") + ylab("") + theme_minimal() +
scale_x_date(breaks = seq.Date(from = as.Date("2019-10-01"), to = as.Date("2023-10-01"), by = "quarter"),
labels = date_format("%b %y")) +
scale_y_log10(breaks = seq(0, 400, 20)) +
theme(legend.position = c(0.5, 0.8),
legend.title = element_blank())
Volume des Branches: Services Non Marchands, Marchands, Industrie
2011T1-
Code
`CNT-2014-CB` %>%
filter(CNA_PRODUIT %in% c("DSN-CNT", "DSM-CNT", "DIM-CNT", "A17-FZ"),
OPERATION == "B1",
VALORISATION == "L") %>%
select_if(~ n_distinct(.) > 1) %>%
quarter_to_date %>%
left_join(CNA_PRODUIT, by = "CNA_PRODUIT") %>%
filter(date >= as.Date("2011-01-01")) %>%
group_by(CNA_PRODUIT) %>%
mutate(OBS_VALUE = 100*OBS_VALUE / OBS_VALUE[date == as.Date("2017-04-01")]) %>%
ggplot + geom_line(aes(x = date, y = OBS_VALUE, color = Cna_produit)) +
xlab("") + ylab("Emploi Trimestriel (100 = 2017T2)") + theme_minimal() +
scale_x_date(breaks = seq(1960, 2023, 1) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%Y")) +
scale_y_log10(breaks = seq(0, 120, 2)) +
theme(legend.position = c(0.7, 0.2),
legend.title = element_blank())
2017T2-
Code
`CNT-2014-CB` %>%
filter(CNA_PRODUIT %in% c("DSN-CNT", "DSM-CNT", "DIM-CNT", "A17-FZ"),
OPERATION == "B1",
VALORISATION == "L") %>%
select_if(~ n_distinct(.) > 1) %>%
quarter_to_date %>%
left_join(CNA_PRODUIT, by = "CNA_PRODUIT") %>%
filter(date >= as.Date("2017-04-01")) %>%
group_by(CNA_PRODUIT) %>%
mutate(OBS_VALUE = 100*OBS_VALUE / OBS_VALUE[date == as.Date("2017-04-01")]) %>%
ggplot + geom_line(aes(x = date, y = OBS_VALUE, color = Cna_produit)) +
xlab("") + ylab("Emploi Trimestriel (100 = 2017T2)") + theme_minimal() +
scale_x_date(breaks = seq(1960, 2023, 1) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%Y")) +
scale_y_log10(breaks = seq(0, 120, 2)) +
theme(legend.position = c(0.32, 0.2),
legend.title = element_blank())
2019T4-
Code
`CNT-2014-CB` %>%
filter(CNA_PRODUIT %in% c("DSN-CNT", "DSM-CNT", "DIM-CNT", "A17-FZ"),
OPERATION == "B1",
VALORISATION == "L") %>%
select_if(~ n_distinct(.) > 1) %>%
quarter_to_date %>%
left_join(CNA_PRODUIT, by = "CNA_PRODUIT") %>%
filter(date >= as.Date("2019-10-01")) %>%
arrange(date) %>%
group_by(CNA_PRODUIT) %>%
mutate(OBS_VALUE = 100*OBS_VALUE/OBS_VALUE[date == as.Date("2019-10-01")]) %>%
ggplot + geom_line(aes(x = date, y = OBS_VALUE, color = Cna_produit)) +
xlab("") + ylab("") + theme_minimal() +
scale_x_date(breaks = seq.Date(from = as.Date("2019-10-01"), to = as.Date("2023-10-01"), by = "quarter"),
labels = date_format("%b %y")) +
scale_y_log10(breaks = seq(0, 120, 5)) +
theme(legend.position = c(0.7, 0.2),
legend.title = element_blank())
Valeur VS Volume
C1 - Fabrication de denrées alimentaires, de boissons et de produits à base de tabac
Code
`CNT-2014-CB` %>%
filter(INDICATEUR == "CNT-COMPTE_PRODUCTION_BRANCHES",
CNA_PRODUIT == "A17-C1",
OPERATION == "B1") %>%
select(VALORISATION, OBS_VALUE, TIME_PERIOD) %>%
quarter_to_date %>%
left_join(VALORISATION, by = "VALORISATION") %>%
ggplot() + theme_minimal() + ylab("") + xlab("") +
geom_line(aes(x = date, y = OBS_VALUE/10^3, color = Valorisation, linetype = Valorisation)) +
scale_color_manual(values = viridis(3)[1:2]) +
theme(legend.position = c(0.5, 0.2),
legend.title = element_blank()) +
scale_x_date(breaks = seq(1920, 2100, 5) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%y")) +
scale_y_log10(breaks = c(0.1, 0.2, 0.3, 0.5, 0.8, 1, 2, 3, 5, 10, 20, 50),
labels = dollar_format(accuracy = 0.1, prefix = "", suffix = "M"))
C2 - Cokéfaction et raffinage
Code
`CNT-2014-CB` %>%
filter(INDICATEUR == "CNT-COMPTE_PRODUCTION_BRANCHES",
CNA_PRODUIT == "A17-C2",
OPERATION == "B1") %>%
select(VALORISATION, OBS_VALUE, TIME_PERIOD) %>%
quarter_to_date %>%
left_join(VALORISATION, by = "VALORISATION") %>%
ggplot() + theme_minimal() + ylab("") + xlab("") +
geom_line(aes(x = date, y = OBS_VALUE/10^3, color = Valorisation, linetype = Valorisation)) +
scale_color_manual(values = viridis(3)[1:2]) +
theme(legend.position = c(0.5, 0.2),
legend.title = element_blank()) +
scale_x_date(breaks = seq(1920, 2100, 5) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%y")) +
scale_y_log10(breaks = c(0.01, 0.02, 0.05, 0.1, 0.2, 0.3, 0.5, 0.8, 1, 2, 3, 5, 10, 20, 50),
labels = dollar_format(accuracy = 0.01, prefix = "", suffix = "M"))
C3 - Fabrication d’équipements électriques, électroniques, informatiques ; fabrication de machines
Code
`CNT-2014-CB` %>%
filter(INDICATEUR == "CNT-COMPTE_PRODUCTION_BRANCHES",
CNA_PRODUIT == "A17-C3",
OPERATION == "B1") %>%
select(VALORISATION, OBS_VALUE, TIME_PERIOD) %>%
quarter_to_date %>%
left_join(VALORISATION, by = "VALORISATION") %>%
ggplot() + theme_minimal() + ylab("") + xlab("") +
geom_line(aes(x = date, y = OBS_VALUE/10^3, color = Valorisation, linetype = Valorisation)) +
scale_color_manual(values = viridis(3)[1:2]) +
theme(legend.position = c(0.5, 0.2),
legend.title = element_blank()) +
scale_x_date(breaks = seq(1920, 2100, 5) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%y")) +
scale_y_log10(breaks = c(0.1, 0.2, 0.3, 0.5, 0.8, 1, 2, 3, 5, 10, 20, 50),
labels = dollar_format(accuracy = 0.1, prefix = "", suffix = "M"))
C4 - Fabrication de matériels de transport
Code
`CNT-2014-CB` %>%
filter(INDICATEUR == "CNT-COMPTE_PRODUCTION_BRANCHES",
CNA_PRODUIT == "A17-C4",
OPERATION == "B1") %>%
select(VALORISATION, OBS_VALUE, TIME_PERIOD) %>%
quarter_to_date %>%
left_join(VALORISATION, by = "VALORISATION") %>%
ggplot() + theme_minimal() + ylab("") + xlab("") +
geom_line(aes(x = date, y = OBS_VALUE/10^3, color = Valorisation, linetype = Valorisation)) +
scale_color_manual(values = viridis(3)[1:2]) +
theme(legend.position = c(0.5, 0.2),
legend.title = element_blank()) +
scale_x_date(breaks = seq(1920, 2100, 5) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%y")) +
scale_y_log10(breaks = c(0.1, 0.2, 0.3, 0.5, 0.8, 1, 2, 3, 5, 10, 20, 50),
labels = dollar_format(accuracy = 0.1, prefix = "", suffix = "M"))
C5 - Fabrication d’autres produits industriels
Code
`CNT-2014-CB` %>%
filter(INDICATEUR == "CNT-COMPTE_PRODUCTION_BRANCHES",
CNA_PRODUIT == "A17-C5",
OPERATION == "B1") %>%
select(VALORISATION, OBS_VALUE, TIME_PERIOD) %>%
quarter_to_date %>%
left_join(VALORISATION, by = "VALORISATION") %>%
ggplot() + theme_minimal() + ylab("") + xlab("") +
geom_line(aes(x = date, y = OBS_VALUE/10^3, color = Valorisation, linetype = Valorisation)) +
scale_color_manual(values = viridis(3)[1:2]) +
theme(legend.position = c(0.5, 0.2),
legend.title = element_blank()) +
scale_x_date(breaks = seq(1920, 2100, 5) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%y")) +
scale_y_log10(breaks = c(0.1, 0.2, 0.3, 0.5, 0.8, 1, 2, 3, 5, 10, 20, 50),
labels = dollar_format(accuracy = 0.1, prefix = "", suffix = "M"))
DIM-CNT - C1+C2+C3+C4+C5 - Industrie manuf.
Code
`CNT-2014-CB` %>%
filter(INDICATEUR == "CNT-COMPTE_PRODUCTION_BRANCHES",
CNA_PRODUIT == "DIM-CNT",
OPERATION == "B1") %>%
select(VALORISATION, OBS_VALUE, TIME_PERIOD) %>%
quarter_to_date %>%
left_join(VALORISATION, by = "VALORISATION") %>%
ggplot() + theme_minimal() + ylab("") + xlab("") +
geom_line(aes(x = date, y = OBS_VALUE/10^3, color = Valorisation, linetype = Valorisation)) +
scale_color_manual(values = viridis(3)[1:2]) +
theme(legend.position = c(0.5, 0.2),
legend.title = element_blank()) +
scale_x_date(breaks = seq(1920, 2100, 5) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%y")) +
scale_y_log10(breaks = c(0.1, 0.2, 0.3, 0.5, 0.8, 1, 2, 3, 5, 10, 20, 50),
labels = dollar_format(accuracy = 0.1, prefix = "", suffix = "M"))
DI-CNT
Code
`CNT-2014-CB` %>%
filter(INDICATEUR == "CNT-COMPTE_PRODUCTION_BRANCHES",
CNA_PRODUIT == "DI-CNT",
OPERATION == "B1") %>%
select(VALORISATION, OBS_VALUE, TIME_PERIOD) %>%
quarter_to_date %>%
left_join(VALORISATION, by = "VALORISATION") %>%
ggplot() + theme_minimal() + ylab("") + xlab("") +
geom_line(aes(x = date, y = OBS_VALUE/10^3, color = Valorisation, linetype = Valorisation)) +
scale_color_manual(values = viridis(3)[1:2]) +
theme(legend.position = c(0.5, 0.2),
legend.title = element_blank()) +
scale_x_date(breaks = seq(1920, 2100, 5) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%y")) +
scale_y_log10(breaks = c(0.1, 0.2, 0.3, 0.5, 0.8, 1, 2, 3, 5, 10, 20, 50),
labels = dollar_format(accuracy = 0.1, prefix = "", suffix = "M"))
DS-CNT
Code
`CNT-2014-CB` %>%
filter(INDICATEUR == "CNT-COMPTE_PRODUCTION_BRANCHES",
CNA_PRODUIT == "DS-CNT",
OPERATION == "B1") %>%
select(VALORISATION, OBS_VALUE, TIME_PERIOD) %>%
quarter_to_date %>%
left_join(VALORISATION, by = "VALORISATION") %>%
ggplot() + theme_minimal() + ylab("") + xlab("") +
geom_line(aes(x = date, y = OBS_VALUE/10^3, color = Valorisation, linetype = Valorisation)) +
scale_color_manual(values = viridis(3)[1:2]) +
theme(legend.position = c(0.5, 0.2),
legend.title = element_blank()) +
scale_x_date(breaks = seq(1920, 2100, 5) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%y")) +
scale_y_log10(breaks = c(0.1, 0.2, 0.3, 0.5, 0.8, 1, 2, 3, 5, 10, 20, 50, 100, 200, 500),
labels = dollar_format(accuracy = 0.1, prefix = "", suffix = "M"))
GZ
Code
`CNT-2014-CB` %>%
filter(INDICATEUR == "CNT-COMPTE_PRODUCTION_BRANCHES",
CNA_PRODUIT == "A17-GZ",
OPERATION == "B1") %>%
select(VALORISATION, OBS_VALUE, TIME_PERIOD) %>%
quarter_to_date %>%
left_join(VALORISATION, by = "VALORISATION") %>%
ggplot() + theme_minimal() + ylab("") + xlab("") +
geom_line(aes(x = date, y = OBS_VALUE/10^3, color = Valorisation, linetype = Valorisation)) +
scale_color_manual(values = viridis(3)[1:2]) +
theme(legend.position = c(0.5, 0.2),
legend.title = element_blank()) +
scale_x_date(breaks = seq(1920, 2100, 5) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%y")) +
scale_y_log10(breaks = c(0.1, 0.2, 0.3, 0.5, 0.8, 1, 2, 3, 5, 10, 20, 50),
labels = dollar_format(accuracy = 0.1, prefix = "", suffix = "M"))
Emploi Total 1995-
Industrie, Construction
Code
`CNT-2014-CB` %>%
filter(OPERATION == "EMPS",
CNA_PRODUIT %in% c("A17-FZ", "DIM-CNT", ""),
UNIT_MEASURE == "INDIVIDUS") %>%
quarter_to_date %>%
left_join(CNA_PRODUIT, by = "CNA_PRODUIT") %>%
arrange(CNA_PRODUIT, date) %>%
filter(date >= as.Date("2011-01-01")) %>%
ggplot() + theme_minimal() + ylab("Nombre d'actifs occupés") + xlab("") +
geom_line(aes(x = date, y = OBS_VALUE/10^3, color = Cna_produit, linetype = Cna_produit)) +
scale_x_date(breaks = seq(1920, 2100, 1) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%y")) +
theme(legend.position = c(0.5, 0.2),
legend.title = element_blank()) +
scale_y_log10(breaks = c(seq(0, 40, 0.1), seq(0, 1, 0.1), seq(0, 0.1, 0.01)),
labels = dollar_format(accuracy = 0.1, prefix = "", suffix = "M"))
Services
Code
`CNT-2014-CB` %>%
filter(OPERATION == "EMPS",
CNA_PRODUIT %in% c("DSM-CNT", "DSN-CNT ", ""),
UNIT_MEASURE == "INDIVIDUS") %>%
quarter_to_date %>%
left_join(CNA_PRODUIT, by = "CNA_PRODUIT") %>%
arrange(CNA_PRODUIT, date) %>%
filter(date >= as.Date("2011-01-01")) %>%
ggplot() + theme_minimal() + ylab("Nombre d'actifs occupés") + xlab("") +
geom_line(aes(x = date, y = OBS_VALUE/10^3, color = Cna_produit, linetype = Cna_produit)) +
scale_x_date(breaks = seq(1920, 2100, 1) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%y")) +
theme(legend.position = c(0.5, 0.2),
legend.title = element_blank()) +
scale_y_log10(breaks = c(seq(0, 40, 0.1), seq(0, 1, 0.1), seq(0, 0.1, 0.01)),
labels = dollar_format(accuracy = 0.1, prefix = "", suffix = "M"))
Taux de marge par branches
Code
`CNT-2014-CB` %>%
filter(OPERATION %in% c("B1", "B2"),
grepl("A17", CNA_PRODUIT)) %>%
mutate(variable = paste0(OPERATION, "_", VALORISATION)) %>%
quarterend_to_date() %>%
arrange(CNA_PRODUIT, date, variable) %>%
select(CNA_PRODUIT, date, variable, OBS_VALUE) %>%
spread(variable, OBS_VALUE) %>%
{if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}