Emploi intérieur, durée effective travaillée et productivité horaire

Data - Insee

Author

François Geerolf

Info

source dataset .html .RData
insee CNA-2014-EMPLOI 2025-08-26 2025-08-28

Données sur l’emploi

source dataset .html .RData
insee CHOMAGE-TRIM-NATIONAL 2025-08-28 2025-08-28
insee CNA-2014-EMPLOI 2025-08-26 2025-08-28
insee DEMANDES-EMPLOIS-NATIONALES 2025-08-26 2025-08-28
insee EMPLOI-BIT-TRIM 2025-08-26 2025-08-28
insee EMPLOI-SALARIE-TRIM-NATIONAL 2025-08-26 2025-08-28
insee TAUX-CHOMAGE 2025-08-26 2025-08-28
insee TCRED-EMPLOI-SALARIE-TRIM 2025-08-26 2025-08-28

LAST_UPDATE

Code 
`CNA-2014-EMPLOI` %>%
  group_by(LAST_UPDATE) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  print_table_conditional()
LAST_UPDATE Nobs
2023-05-31 47203
2022-06-14 1288

Champ

  • 1949-

TITLE_FR

Code 
`CNA-2014-EMPLOI` %>%
  group_by(IDBANK, TITLE_FR) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  print_table_conditional()

INDICATEUR

Code 
`CNA-2014-EMPLOI` %>%
  left_join(INDICATEUR,  by = "INDICATEUR") %>%
  group_by(INDICATEUR, Indicateur) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  print_table_conditional()
INDICATEUR Indicateur Nobs
CNA_EMPLOI_INTERIEUR Emploi intérieur 29030
CNA_VOLUME_HEURES_TRAV Volume d'heures travaillées 9765
CNA_DUREE_TRAVAILLEE Durée annuelle effective travaillée 4883
CNA_PRODUCTIVITE_HORAIRE Productivité horaire 4813

CNA_ACTIVITE

Code 
`CNA-2014-EMPLOI` %>%
  left_join(CNA_ACTIVITE,  by = "CNA_ACTIVITE") %>%
  group_by(CNA_ACTIVITE, Cna_activite) %>%
  summarise(Nobs = n()) %>%
  print_table_conditional()

CNA_TYPE_EMP

Code 
`CNA-2014-EMPLOI` %>%
  left_join(CNA_TYPE_EMP,  by = "CNA_TYPE_EMP") %>%
  group_by(CNA_TYPE_EMP, Cna_type_emp) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  print_table_conditional()
CNA_TYPE_EMP Cna_type_emp Nobs
E10 E10 - Emploi intérieur total 19924
E20 E20 - Emploi intérieur salarié 9778
E21 E21 - Emploi intérieur salarié déclaré 9765
E30 E30 - Emploi intérieur non salarié 9024

TIME_PERIOD

Code 
`CNA-2014-EMPLOI` %>%
  group_by(TIME_PERIOD) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  arrange(desc(TIME_PERIOD)) %>%
  print_table_conditional()

Durée du travail

Durée annuelle effective travaillée

Code 
`CNA-2014-EMPLOI` %>%
  filter(CNA_ACTIVITE %in% c("NNTOTAL"),
         INDICATEUR == "CNA_DUREE_TRAVAILLEE") %>%
  year_to_date %>%
  ggplot + geom_line(aes(x = date, y = OBS_VALUE)) +
  theme_minimal() +
  ylab("") + xlab("") +
  scale_x_date(breaks = seq(1920, 2100,10) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_log10(breaks = seq(100, 3000, 100),
                     labels = dollar_format(prefix = "", suffix = " h / an", acc = 1)) +
  theme(legend.position = c(0.7, 0.9),
        legend.title = element_blank())

Heures travaillées

Code 
`CNA-2014-EMPLOI` %>%
  filter(CNA_ACTIVITE %in% c("NNTOTAL"),
         #INDICATEUR == "CNA_EMPLOI_INTERIEUR",
         #UNIT_MEASURE == "MILLIERS_ACTIFS_OCCUPES_PP",
         CNA_TYPE_EMP == "E10",
         `SECT-INST` == "S10") %>%
  year_to_date %>%
  select(date, UNIT_MEASURE, OBS_VALUE) %>%
  spread(UNIT_MEASURE, OBS_VALUE) %>%
  transmute(date,
            HEURES_TRAVAILLEES_PP = HEURES_TRAVAILLEES/(MILLIERS_ACTIFS_OCCUPES_PP*10^3),
            HEURES_TRAVAILLEES_ETP = HEURES_TRAVAILLEES/(MILLIERS_ACTIFS_OCCUPES_ETP*10^3)) %>%
  gather(variable, OBS_VALUE, -date) %>%
  ggplot + geom_line(aes(x = date, y = OBS_VALUE, color = variable)) +
  theme_minimal() +
  ylab("") + xlab("") +
  scale_x_date(breaks = seq(1920, 2100,10) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_log10(breaks = seq(100, 3000, 100),
                     labels = dollar_format(prefix = "", suffix = " h / an", acc = 1)) +
  theme(legend.position = c(0.7, 0.9),
        legend.title = element_blank())

Emploi Total

1950-

Secteurs

Code 
`CNA-2014-EMPLOI` %>%
  filter(CNA_ACTIVITE %in% c("NNTOTAL"),
         INDICATEUR == "CNA_EMPLOI_INTERIEUR",
         UNIT_MEASURE == "MILLIERS_ACTIFS_OCCUPES_PP",
         CNA_TYPE_EMP == "E10") %>%
  left_join(`SECT-INST`,  by = "SECT-INST") %>%
  year_to_date %>%
  ggplot() + theme_minimal() + ylab("Nombre d'actifs occupés") + xlab("") +
  geom_line(aes(x = date, y = OBS_VALUE/10^3, color = `Sect-Inst`)) +
  
  scale_x_date(breaks = seq(1920, 2100,5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = c(0.3, 0.2),
        legend.title = element_blank()) +
  scale_y_log10(breaks = c(seq(0, 40, 1), seq(0, 1, 0.1), seq(0, 0.1, 0.01)),
                labels = dollar_format(accuracy = 0.01, prefix = "", suffix = "M"))

CNA_TYPE_EMP

Code 
`CNA-2014-EMPLOI` %>%
  filter(CNA_ACTIVITE %in% c("NNTOTAL"),
         `SECT-INST` %in% c("S10"),
         UNIT_MEASURE == "MILLIERS_ACTIFS_OCCUPES_PP") %>%
  left_join(CNA_TYPE_EMP,  by = "CNA_TYPE_EMP") %>%
  year_to_date %>%
  ggplot() + theme_minimal() + ylab("Nombre d'actifs occupés") + xlab("") +
  geom_line(aes(x = date, y = OBS_VALUE/10^3, color = Cna_type_emp)) +
  
  scale_x_date(breaks = seq(1920, 2100,5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = c(0.3, 0.2),
        legend.title = element_blank()) +
  scale_y_log10(breaks = c(seq(0, 40, 1), seq(0, 1, 0.1), seq(0, 0.1, 0.01)),
                labels = dollar_format(accuracy = 0.01, prefix = "", suffix = "M"))

1995-

Code 
`CNA-2014-EMPLOI` %>%
  filter(CNA_ACTIVITE %in% c("NNTOTAL"),
         UNIT_MEASURE == "MILLIERS_ACTIFS_OCCUPES_PP",
         `SECT-INST` %in% c("S10"),
         CNA_TYPE_EMP == "E10") %>%
  left_join(CNA_TYPE_EMP,  by = "CNA_TYPE_EMP") %>%
  year_to_date %>%
  filter(date >= as.Date("1995-01-01")) %>%
  mutate(OBS_VALUE = as.numeric(OBS_VALUE)) %>%
  ggplot() + theme_minimal() + ylab("Nombre d'actifs occupés") + xlab("") +
  geom_line(aes(x = date, y = OBS_VALUE/10^3, color = `SECT-INST`, linetype = `SECT-INST`)) +
  
  scale_x_date(breaks = seq(1920, 2100,2) %>% 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, 1), seq(0, 1, 0.1), seq(0, 0.1, 0.01)),
                labels = dollar_format(accuracy = 1, prefix = "", suffix = "M"))

Heures travaillées

A5

Code 
`CNA-2014-EMPLOI` %>%
  filter(CNA_TYPE_EMP == "E10",
         TIME_PERIOD == "2018",
         grepl("A5", CNA_ACTIVITE)) %>%
  arrange(CNA_ACTIVITE) %>%
  left_join(CNA_ACTIVITE,  by = "CNA_ACTIVITE") %>%
  select(Cna_activite, UNIT_MEASURE, OBS_VALUE) %>%
  spread(UNIT_MEASURE, OBS_VALUE) %>%
  setNames(c("Secteur", "Heures", "ETP", "PP", "%")) %>%
  {if (is_html_output()) print_table(.) else .}
Secteur Heures ETP PP %
A5-AZ - Agriculture, sylviculture et pêche 1676549970 788.7 754.1 4.2
A5-BE - Industrie manufacturière, industries extractives et autres 4513166760 2784.9 2876.9 1.4
A5-FZ - Construction 3003677122 1750.0 1743.3 -1.4
A5-GU - Services principalement marchands 22362627335 13472.3 14433.0 -0.2
A5-OQ - Services principalement non marchands 11086745049 7722.5 8350.7 1.2

A10

Code 
`CNA-2014-EMPLOI` %>%
  filter(CNA_TYPE_EMP == "E10",
         TIME_PERIOD == "2018",
         grepl("A10", CNA_ACTIVITE)) %>%
  arrange(CNA_ACTIVITE) %>%
  left_join(CNA_ACTIVITE,  by = "CNA_ACTIVITE") %>%
  select(Cna_activite, UNIT_MEASURE, OBS_VALUE) %>%
  spread(UNIT_MEASURE, OBS_VALUE) %>%
  setNames(c("Secteur", "Heures", "ETP", "PP", "%")) %>%
  {if (is_html_output()) print_table(.) else .}
Secteur Heures ETP PP %
A10-AZ - Agriculture, sylviculture et pêche 1676549970 788.7 754.1 4.2
A10-BE - Industrie manufacturière, industries extractives et autres 4513166760 2784.9 2876.9 1.4
A10-FZ - Construction 3003677122 1750.0 1743.3 -1.4
A10-GI - Commerce de gros et de détail, transports, hébergement et restauration 10108707570 5988.4 6453.0 -1.7
A10-JZ - Information et communication 1467543035 867.4 890.3 -0.2
A10-KZ - Activités financières et d'assurance 1236254630 767.1 787.4 5.9
A10-LZ - Activités immobilières 590932478 362.2 382.6 0.4
A10-MN - Activités spécialisées, scientifiques et techniques et activités de services administratifs et de soutien 6872417655 4145.8 4421.6 -0.6
A10-OQ - Administration publique, enseignement, santé humaine et action sociale 11086745049 7722.5 8350.7 1.2
A10-RU - Autres activités de services 2086771967 1341.4 1498.1 2.0

A17

Code 
`CNA-2014-EMPLOI` %>%
  filter(CNA_TYPE_EMP == "E10",
         TIME_PERIOD == "2018",
         grepl("A17", CNA_ACTIVITE)) %>%
  arrange(CNA_ACTIVITE) %>%
  left_join(CNA_ACTIVITE,  by = "CNA_ACTIVITE") %>%
  select(CNA_ACTIVITE, Cna_activite, UNIT_MEASURE, OBS_VALUE) %>%
  spread(UNIT_MEASURE, OBS_VALUE) %>%
  setNames(c("CNA_ACTIVITE", "Secteur", "Heures", "ETP", "PP", "%")) %>%
  {if (is_html_output()) print_table(.) else .}
CNA_ACTIVITE Secteur Heures ETP PP %
A17-AZ A17-AZ - Agriculture, sylviculture et pêche 1676549970 788.7 754.1 4.2
A17-C1 A17-C1 - Fabrication de denrées alimentaires, de boissons et de produits à base de tabac 971685139 593.9 618.8 0.5
A17-C2 A17-C2 - Cokéfaction et raffinage 12718435 8.5 8.8 19.7
A17-C3 A17-C3 - Fabrication d'équipements électriques, électroniques, informatiques ; fabrication de machines 487614952 301.1 309.1 -0.4
A17-C4 A17-C4 - Fabrication de matériels de transport 295014688 183.7 188.8 5.7
A17-C5 A17-C5 - Fabrication d'autres produits industriels 2275694360 1397.5 1443.2 -0.5
A17-DE A17-DE - Industries extractives, énergie, eau, gestion des déchets et dépollution 470439187 300.2 308.2 3.6
A17-FZ A17-FZ - Construction 3003677122 1750.0 1743.3 -1.4
A17-GZ A17-GZ - Commerce ; réparation d'automobiles et de motocycles 5890323015 3522.4 3785.9 -0.6
A17-HZ A17-HZ - Transports et entreposage 2164789823 1341.8 1408.8 -4.3
A17-IZ A17-IZ - Hébergement et restauration 2053594732 1124.2 1258.3 -1.2
A17-JZ A17-JZ - Information et communication 1467543035 867.4 890.3 -0.2
A17-KZ A17-KZ - Activités financières et d'assurance 1236254630 767.1 787.4 5.9
A17-LZ A17-LZ - Activités immobilières 590932478 362.2 382.6 0.4
A17-MN A17-MN - Activités scientifiques et techniques ; services administratifs et de soutien 6872417655 4145.8 4421.6 -0.6
A17-OQ A17-OQ - Administration publique, enseignement, santé humaine et action sociale 11086745049 7722.5 8350.7 1.2
A17-RU A17-RU - Autres activités de services 2086771967 1341.4 1498.1 2.0

A38

Code 
`CNA-2014-EMPLOI` %>%
  filter(CNA_TYPE_EMP == "E10",
         TIME_PERIOD == "2017",
         grepl("A38", CNA_ACTIVITE)) %>%
  arrange(CNA_ACTIVITE) %>%
  left_join(CNA_ACTIVITE,  by = "CNA_ACTIVITE") %>%
  select(CNA_ACTIVITE, Cna_activite, UNIT_MEASURE, OBS_VALUE) %>%
  spread(UNIT_MEASURE, OBS_VALUE) %>%
  setNames(c("CNA_ACTIVITE", "Secteur", "Heures", "ETP", "PP", "%")) %>%
  {if (is_html_output()) print_table(.) else .}
CNA_ACTIVITE Secteur Heures ETP PP %
A38-AZ A38-AZ - Agriculture, sylviculture et pêche 1681125349 793.2 752.4 10.3
A38-BZ A38-BZ - Industries extractives 24043805 15.1 15.4 4.6
A38-CA A38-CA - Fabrication de denrées alimentaires, de boissons et de produits à base de tabac 980991568 602.1 630.1 3.1
A38-CB A38-CB - Fabrication de textiles, industries de l'habillement, industrie du cuir et de la chaussure 152250237 94.6 97.7 4.7
A38-CC A38-CC - Travail du bois, industries du papier et imprimerie 283499198 174.0 179.9 4.9
A38-CD A38-CD - Cokéfaction et raffinage 12795620 8.4 8.6 2.1
A38-CE A38-CE - Industrie chimique 167404769 107.7 111.4 3.6
A38-CF A38-CF - Industrie pharmaceutique 67645545 44.1 46.3 4.5
A38-CG A38-CG - Fabrication de produits en caoutchouc et en plastique ainsi que d'autres produits minéraux non métalliques 375938270 238.6 245.5 2.4
A38-CH A38-CH - Métallurgie et fabrication de produits métalliques à l'exception des machines et des équipements 597517010 368.3 378.7 4.3
A38-CI A38-CI - Fabrication de produits informatiques, électroniques et optiques 131934142 82.2 84.9 6.2
A38-CJ A38-CJ - Fabrication d'équipements électriques 121485896 76.6 78.8 5.0
A38-CK A38-CK - Fabrication de machines et équipements n.c.a. 222904756 138.3 141.8 4.0
A38-CL A38-CL - Fabrication de matériels de transport 290347352 181.7 186.7 3.7
A38-CM A38-CM - Autres industries manufacturières ; réparation et installation de machines et d'équipements 608099845 368.4 379.0 3.0
A38-DZ A38-DZ - Production et distribution d'électricité, de gaz, de vapeur et d'air conditionné 197076762 127.2 131.9 -4.8
A38-EZ A38-EZ - Production et distribution d'eau ; assainissement, gestion des déchets et dépollution 245547469 156.0 158.8 4.6
A38-FZ A38-FZ - Construction 2930430016 1718.8 1717.9 3.6
A38-GZ A38-GZ - Commerce; réparation d'automobiles et de motocycles 5797265772 3484.9 3754.4 1.5
A38-HZ A38-HZ - Transports et entreposage 2126939576 1323.6 1387.1 2.2
A38-IZ A38-IZ - Hébergement et restauration 1991643556 1087.6 1217.7 -0.7
A38-JA A38-JA - Édition, audiovisuel et diffusion 334823674 200.8 208.2 9.5
A38-JB A38-JB - Télécommunications 150768265 100.8 107.6 10.1
A38-JC A38-JC - Activités informatiques et services d'information 902547811 531.9 540.5 3.9
A38-KZ A38-KZ - Activités financières et d'assurance 1221471311 759.7 781.1 2.1
A38-LZ A38-LZ - Activités immobilières 585537321 357.2 376.4 -1.6
A38-MA A38-MA - Activités juridiques, comptables, de gestion, d'architecture, d'ingénierie, de contrôle et d'analyses techniques 2084958737 1217.1 1294.4 3.1
A38-MB A38-MB - Recherche-développement scientifique 692692871 429.1 450.9 4.3
A38-MC A38-MC - Autres activités spécialisées, scientifiques et techniques 439726261 253.9 279.1 4.2
A38-NZ A38-NZ - Activités de services administratifs et de soutien 3383029956 2097.4 2270.3 -1.2
A38-OZ A38-OZ - Administration publique 3364512366 2292.9 2452.0 0.7
A38-PZ A38-PZ - Enseignement 2312532354 1903.3 1999.5 2.1
A38-QA A38-QA - Activités pour la santé humaine 2926753725 1802.1 1938.2 2.9
A38-QB A38-QB - Hébergement médico-social et social et action sociale sans hébergement 2536151112 1775.4 1971.9 2.0
A38-RZ A38-RZ - Arts, spectacles et activités récréatives 800992393 520.8 606.1 2.1
A38-SZ A38-SZ - Autres activités de services 977689028 623.5 738.1 2.9
A38-TZ A38-TZ - Activités des ménages en tant qu'employeurs ; activités indifférenciées des ménages en tant que producteurs de biens et services pour usage propre 312456676 202.6 162.0 2.5

Emploi salarié, non salarié

Code 
`CNA-2014-EMPLOI` %>%
  filter(CNA_ACTIVITE %in% c("NNTOTAL"),
         UNIT_MEASURE == "MILLIERS_ACTIFS_OCCUPES_PP",
         `SECT-INST` == "S10") %>%
  left_join(CNA_TYPE_EMP,  by = "CNA_TYPE_EMP") %>%
  year_to_date %>%
  filter(date >= as.Date("2016-01-01")) %>%
  group_by(Cna_type_emp) %>%
  arrange(date) %>%
  mutate(OBS_VALUE = OBS_VALUE-OBS_VALUE[1]) %>%
  ggplot() + theme_minimal() + ylab("") + xlab("") +
  geom_line(aes(x = date, y = OBS_VALUE, color = Cna_type_emp)) +
  
  scale_x_date(breaks = seq(1920, 2100,1) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = c(0.3, 0.8),
        legend.title = element_blank()) +
  scale_y_continuous(breaks = seq(-200, 100000, 100))

Emploi Industrie, Manufacturier

BE: Manuf

Code 
`CNA-2014-EMPLOI` %>%
  filter(CNA_ACTIVITE %in% c("A10-BE"),
         UNIT_MEASURE == "MILLIERS_ACTIFS_OCCUPES_PP") %>%
  left_join(CNA_TYPE_EMP,  by = "CNA_TYPE_EMP") %>%
  year_to_date %>%
  filter(date >= as.Date("2016-01-01")) %>%
  group_by(Cna_type_emp) %>%
  arrange(date) %>%
  mutate(OBS_VALUE = 100*OBS_VALUE/OBS_VALUE[1]) %>%
  ggplot() + theme_minimal() + ylab("Base 100 = 1990") + xlab("") +
  geom_line(aes(x = date, y = OBS_VALUE, color = Cna_type_emp)) +
  
  scale_x_date(breaks = seq(1920, 2100,1) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = c(0.3, 0.8),
        legend.title = element_blank()) +
  scale_y_log10(breaks = seq(10, 200, 1))

Nombre d’emplois

Code 
`CNA-2014-EMPLOI` %>%
  filter(CNA_ACTIVITE %in% c("A10-BE"),
         UNIT_MEASURE == "MILLIERS_ACTIFS_OCCUPES_PP") %>%
  left_join(CNA_TYPE_EMP,  by = "CNA_TYPE_EMP") %>%
  year_to_date %>%
  filter(date >= as.Date("2016-01-01")) %>%
  group_by(Cna_type_emp) %>%
  arrange(date) %>%
  mutate(OBS_VALUE = OBS_VALUE-OBS_VALUE[1]) %>%
  ggplot() + theme_minimal() + ylab("") + xlab("") +
  geom_line(aes(x = date, y = OBS_VALUE, color = Cna_type_emp)) +
  
  scale_x_date(breaks = seq(1920, 2100,1) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = c(0.3, 0.8),
        legend.title = element_blank()) +
  scale_y_continuous(breaks = seq(-200, 200, 10))

Emploi 10 Branches (2010-)

AZ-BE-FZ: Construction - Manuf - Agriculture

Code 
`CNA-2014-EMPLOI` %>%
  filter(CNA_TYPE_EMP == "E10",
         CNA_ACTIVITE %in% c("A10-FZ", "A10-BE", "A10-AZ"),
         UNIT_MEASURE == "MILLIERS_ACTIFS_OCCUPES_PP") %>%
  left_join(CNA_ACTIVITE,  by = "CNA_ACTIVITE") %>%
  year_to_date %>%
  filter(date >= as.Date("2010-01-01")) %>%
  ggplot() + theme_minimal() + ylab("Nombre d'actifs occupés") + xlab("") +
  geom_line(aes(x = date, y = OBS_VALUE/10^3, color = Cna_activite, linetype = Cna_activite)) +
  
  scale_x_date(breaks = seq(1920, 2100,1) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = c(0.4, 0.1),
        legend.title = element_blank()) +
  scale_y_log10(breaks = c(seq(0, 6, 0.5), seq(0, 1, 0.1)),
                labels = dollar_format(accuracy = 0.1, prefix = "", suffix = "M"))

GI-MN-OQ-RU: Administration publique (OQ) - Commerce de Gros (GI) - Activités spécialisées (MN) - RU

Code 
`CNA-2014-EMPLOI` %>%
  filter(CNA_TYPE_EMP == "E10",
         CNA_ACTIVITE %in% c("A10-OQ", "A10-GI", "A10-MN", "A10-RU"),
         UNIT_MEASURE == "MILLIERS_ACTIFS_OCCUPES_PP") %>%
  left_join(CNA_ACTIVITE,  by = "CNA_ACTIVITE") %>%
  year_to_date %>%
  filter(date >= as.Date("2010-01-01")) %>%
  ggplot() + 
  geom_line(aes(x = date, y = OBS_VALUE/1000000, color = Cna_activite, linetype = Cna_activite)) +
  
  theme_minimal() +
  scale_x_date(breaks = seq(1920, 2100,5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = c(0.5, 0.9),
        legend.title = element_blank()) +
  scale_y_log10(breaks = seq(0, 10, 1),
                labels = dollar_format(accuracy = 0.1, prefix = "", suffix = "M"),
                limits = c(0.5, 15)) +
  ylab("Nombre d'actifs occupés") + xlab("")

JZ-KZ-LZ: Information-Communication - Activités Financières - Immobilières

Code 
`CNA-2014-EMPLOI` %>%
  filter(CNA_TYPE_EMP == "E10",
         CNA_ACTIVITE %in% c("A10-JZ", "A10-KZ", "A10-LZ"),
         UNIT_MEASURE == "MILLIERS_ACTIFS_OCCUPES_PP") %>%
  left_join(CNA_ACTIVITE,  by = "CNA_ACTIVITE") %>%
  year_to_date %>%
  filter(date >= as.Date("2010-01-01")) %>%
  ggplot() + 
  geom_line(aes(x = date, y = OBS_VALUE/1000000, color = Cna_activite, linetype = Cna_activite)) +
  
  theme_minimal() +
  scale_x_date(breaks = seq(1920, 2100,1) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = c(0.7, 0.2),
        legend.title = element_blank()) +
  scale_y_log10(breaks = seq(0, 6, 0.1),
                labels = dollar_format(accuracy = 0.1, prefix = "", suffix = "M")) +
  ylab("Nombre d'actifs occupés") + xlab("")

Emploi 10 Branches

AZ-BE-FZ: Construction - Manuf - Agriculture

Code 
`CNA-2014-EMPLOI` %>%
  filter(CNA_TYPE_EMP == "E10",
         CNA_ACTIVITE %in% c("A10-FZ", "A10-BE", "A10-AZ"),
         UNIT_MEASURE == "MILLIERS_ACTIFS_OCCUPES_PP") %>%
  left_join(CNA_ACTIVITE,  by = "CNA_ACTIVITE") %>%
  year_to_date %>%
  ggplot() + theme_minimal() + ylab("Nombre d'actifs occupés") + xlab("") +
  geom_line(aes(x = date, y = OBS_VALUE/10^3, color = Cna_activite, linetype = Cna_activite)) +
  
  scale_x_date(breaks = seq(1920, 2100,5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = c(0.4, 0.1),
        legend.title = element_blank()) +
  scale_y_log10(breaks = c(seq(0, 6, 0.5), seq(0, 1, 0.1)),
                labels = dollar_format(accuracy = 0.1, prefix = "", suffix = "M"))

GI-MN-OQ-RU: Administration publique (OQ) - Commerce de Gros (GI) - Activités spécialisées (MN) - RU

Code 
`CNA-2014-EMPLOI` %>%
  filter(CNA_TYPE_EMP == "E10",
         CNA_ACTIVITE %in% c("A10-OQ", "A10-GI", "A10-MN", "A10-RU"),
         UNIT_MEASURE == "MILLIERS_ACTIFS_OCCUPES_PP") %>%
  left_join(CNA_ACTIVITE,  by = "CNA_ACTIVITE") %>%
  year_to_date %>%
  ggplot() + 
  geom_line(aes(x = date, y = OBS_VALUE/1000000, color = Cna_activite, linetype = Cna_activite)) +
  
  theme_minimal() +
  scale_x_date(breaks = seq(1920, 2100,5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = c(0.5, 0.9),
        legend.title = element_blank()) +
  scale_y_log10(breaks = seq(0, 10, 1),
                labels = dollar_format(accuracy = 0.1, prefix = "", suffix = "M"),
                limits = c(0.5, 15)) +
  ylab("Nombre d'actifs occupés") + xlab("")

JZ-KZ-LZ: Information-Communication - Activités Financières - Immobilières

Code 
`CNA-2014-EMPLOI` %>%
  filter(CNA_TYPE_EMP == "E10",
         CNA_ACTIVITE %in% c("A10-JZ", "A10-KZ", "A10-LZ"),
         UNIT_MEASURE == "MILLIERS_ACTIFS_OCCUPES_PP") %>%
  left_join(CNA_ACTIVITE,  by = "CNA_ACTIVITE") %>%
  year_to_date %>%
  ggplot() + 
  geom_line(aes(x = date, y = OBS_VALUE/1000000, color = Cna_activite, linetype = Cna_activite)) +
  
  theme_minimal() +
  scale_x_date(breaks = seq(1920, 2100,5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = c(0.7, 0.2),
        legend.title = element_blank()) +
  scale_y_log10(breaks = seq(0, 6, 0.1),
                labels = dollar_format(accuracy = 0.1, prefix = "", suffix = "M")) +
  ylab("Nombre d'actifs occupés") + xlab("")

Emploi 17 Branches

Transport, Matériel électrique

Code 
`CNA-2014-EMPLOI` %>%
  filter(CNA_TYPE_EMP == "E10",
         CNA_ACTIVITE %in% c("A17-C4", "A17-C3"),
         UNIT_MEASURE == "MILLIERS_ACTIFS_OCCUPES_PP") %>%
  left_join(CNA_ACTIVITE,  by = "CNA_ACTIVITE") %>%
  year_to_date %>%
  filter(date >= as.Date("1990-01-01")) %>%
  ggplot() + theme_minimal() + ylab("Nombre d'actifs occupés") + xlab("") +
  geom_line(aes(x = date, y = OBS_VALUE/10^3, color = Cna_activite, linetype = Cna_activite)) +
  
  scale_x_date(breaks = seq(1920, 2100,5) %>% 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, 6, 0.5), seq(0, 1, 0.1), seq(0, 0.1, 0.01)),
                labels = dollar_format(accuracy = 0.01, prefix = "", suffix = "M"),
                limits = c(0.1, 0.7))

C1-C3-C4: Fabrication denrées alimentaires, équipements électriques, matériels de transport

Tous

Code 
`CNA-2014-EMPLOI` %>%
  filter(CNA_TYPE_EMP == "E10",
         CNA_ACTIVITE %in% c("A17-C1", "A17-C4", "A17-C3"),
         UNIT_MEASURE == "MILLIERS_ACTIFS_OCCUPES_PP") %>%
  left_join(CNA_ACTIVITE,  by = "CNA_ACTIVITE") %>%
  year_to_date %>%
  ggplot() + theme_minimal() + ylab("Nombre d'actifs occupés") + xlab("") +
  geom_line(aes(x = date, y = OBS_VALUE/10^3, color = Cna_activite, linetype = Cna_activite)) +
  
  scale_x_date(breaks = seq(1920, 2100,5) %>% 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, 6, 0.5), seq(0, 1, 0.1), seq(0, 0.1, 0.01)),
                labels = dollar_format(accuracy = 0.01, prefix = "", suffix = "M"),
                limits = c(0.1, 0.7))

1990-

Code 
`CNA-2014-EMPLOI` %>%
  filter(CNA_TYPE_EMP == "E10",
         CNA_ACTIVITE %in% c("A17-C1", "A17-C4", "A17-C3"),
         UNIT_MEASURE == "MILLIERS_ACTIFS_OCCUPES_PP") %>%
  left_join(CNA_ACTIVITE,  by = "CNA_ACTIVITE") %>%
  year_to_date %>%
  filter(date >= as.Date("1990-01-01")) %>%
  ggplot() + theme_minimal() + ylab("Nombre d'actifs occupés") + xlab("") +
  geom_line(aes(x = date, y = OBS_VALUE/10^3, color = Cna_activite, linetype = Cna_activite)) +
  
  scale_x_date(breaks = seq(1920, 2100,5) %>% 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, 6, 0.5), seq(0, 1, 0.1), seq(0, 0.1, 0.01)),
                labels = dollar_format(accuracy = 0.01, prefix = "", suffix = "M"),
                limits = c(0.1, 0.7))

C2-C5-DE: Cokéfaction - Autres produits - Industries extractives

Code 
`CNA-2014-EMPLOI` %>%
  filter(CNA_TYPE_EMP == "E10",
         CNA_ACTIVITE %in% c("A17-C2", "A17-C5", "A17-DE"),
         UNIT_MEASURE == "MILLIERS_ACTIFS_OCCUPES_PP") %>%
  left_join(CNA_ACTIVITE,  by = "CNA_ACTIVITE") %>%
  year_to_date %>%
  ggplot() + theme_minimal() + ylab("Nombre d'actifs occupés") + xlab("") +
  geom_line(aes(x = date, y = OBS_VALUE/10^3, color = Cna_activite, linetype = Cna_activite)) +
  
  scale_x_date(breaks = seq(1920, 2100,5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = c(0.5, 0.45),
        legend.title = element_blank()) +
  scale_y_log10(breaks = c(seq(0, 6, 0.5), seq(0, 1, 0.1), seq(0, 0.1, 0.01)),
                labels = dollar_format(accuracy = 0.01, prefix = "", suffix = "M"))

Emploi 38 Branches

QA-QB-GZ: Commerce; réparation; Santé; Hébergement médico-social

Code 
`CNA-2014-EMPLOI` %>%
  filter(CNA_TYPE_EMP == "E10",
         CNA_ACTIVITE %in% c("A38-QA", "A38-QB", "A38-GZ"),
         UNIT_MEASURE == "MILLIERS_ACTIFS_OCCUPES_PP") %>%
  left_join(CNA_ACTIVITE,  by = "CNA_ACTIVITE") %>%
  year_to_date %>%
  ggplot() + theme_minimal() + ylab("Nombre d'actifs occupés") + xlab("") +
  geom_line(aes(x = date, y = OBS_VALUE/10^3, color = Cna_activite, linetype = Cna_activite)) +
  
  scale_x_date(breaks = seq(1920, 2100,5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = c(0.6, 0.15),
        legend.title = element_blank()) +
  scale_y_log10(breaks = c(seq(0, 6, 0.5), seq(0, 1, 0.1), seq(0, 0.1, 0.01)),
                labels = dollar_format(accuracy = 0.01, prefix = "", suffix = "M"),
                limits = c(0.3, 4))

OZ-NZ-PZ: Administration publique, Activités de service administratifs, Enseignement

Code 
`CNA-2014-EMPLOI` %>%
  filter(CNA_TYPE_EMP == "E10",
         CNA_ACTIVITE %in% c("A38-OZ", "A38-NZ", "A38-c"),
         UNIT_MEASURE == "MILLIERS_ACTIFS_OCCUPES_PP") %>%
  left_join(CNA_ACTIVITE,  by = "CNA_ACTIVITE") %>%
  year_to_date %>%
  ggplot() + theme_minimal() + ylab("Nombre d'actifs occupés") + xlab("") +
  geom_line(aes(x = date, y = OBS_VALUE/10^3, color = Cna_activite, linetype = Cna_activite)) +
  
  scale_x_date(breaks = seq(1920, 2100,5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = c(0.7, 0.2),
        legend.title = element_blank()) +
  scale_y_log10(breaks = c(seq(0, 6, 0.5), seq(0, 1, 0.1), seq(0, 0.1, 0.01)),
                labels = dollar_format(accuracy = 0.01, prefix = "", suffix = "M"))

FZ-HZ-MA: Construction; Transports et entreposage; Activités juridiques, comptables, de gestion, d’architecture, d’ingénierie, de contrôle et d’analyses techniques

Code 
`CNA-2014-EMPLOI` %>%
  filter(CNA_TYPE_EMP == "E10",
         CNA_ACTIVITE %in% c("A38-FZ", "A38-HZ", "A38-MA"),
         UNIT_MEASURE == "MILLIERS_ACTIFS_OCCUPES_PP") %>%
  left_join(CNA_ACTIVITE,  by = "CNA_ACTIVITE") %>%
  year_to_date %>%
  ggplot() + theme_minimal() + ylab("Nombre d'actifs occupés") + xlab("") +
  geom_line(aes(x = date, y = OBS_VALUE/10^3, color = Cna_activite, linetype = Cna_activite)) +
  
  scale_x_date(breaks = seq(1920, 2100,5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = c(0.59, 0.14),
        legend.title = element_blank()) +
  scale_y_log10(breaks = c(seq(0, 6, 0.5), seq(0, 1, 0.1), seq(0, 0.1, 0.01)),
                labels = dollar_format(accuracy = 0.01, prefix = "", suffix = "M"),
                limits = c(0.1, 2.1))

IZ-AZ-KZ: Hébergement et restauration; Agriculture, sylviculture et pêche; Activités financières et d’assurance

Code 
`CNA-2014-EMPLOI` %>%
  filter(CNA_TYPE_EMP == "E10",
         CNA_ACTIVITE %in% c("A38-IZ", "A38-AZ", "A38-KZ"),
         UNIT_MEASURE == "MILLIERS_ACTIFS_OCCUPES_PP") %>%
  left_join(CNA_ACTIVITE,  by = "CNA_ACTIVITE") %>%
  year_to_date %>%
  ggplot() + theme_minimal() + ylab("Nombre d'actifs occupés") + xlab("") +
  geom_line(aes(x = date, y = OBS_VALUE/10^3, color = Cna_activite, linetype = Cna_activite)) +
  
  scale_x_date(breaks = seq(1920, 2100,5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = c(0.59, 0.2),
        legend.title = element_blank()) +
  scale_y_log10(breaks = c(seq(0, 6, 0.5), seq(0, 1, 0.1), seq(0, 0.1, 0.01)),
                labels = dollar_format(accuracy = 0.01, prefix = "", suffix = "M"),
                limits = c(0.1, 5))

SZ-CA-JC: Autres activités de services; Fabrication de denrées alimentaires, de boissons et de produits à base de tabac; Activités informatiques et services d’information

Code 
`CNA-2014-EMPLOI` %>%
  filter(CNA_TYPE_EMP == "E10",
         CNA_ACTIVITE %in% c("A38-SZ", "A38-CA", "A38-JC"),
         UNIT_MEASURE == "MILLIERS_ACTIFS_OCCUPES_PP") %>%
  left_join(CNA_ACTIVITE,  by = "CNA_ACTIVITE") %>%
  year_to_date %>%
  ggplot() + theme_minimal() + ylab("Nombre d'actifs occupés") + xlab("") +
  geom_line(aes(x = date, y = OBS_VALUE/10^3, color = Cna_activite, linetype = Cna_activite)) +
  
  scale_x_date(breaks = seq(1920, 2100,5) %>% 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, 6, 0.5), seq(0, 1, 0.1), seq(0, 0.1, 0.01)),
                labels = dollar_format(accuracy = 0.01, prefix = "", suffix = "M"),
                limits = c(0.01, 1))

RZ-MB-CH: Arts, spectacles et activités récréatives ; Recherche-développement scientifique; Métallurgie et fabrication de produits métalliques à l’exception des machines et des équipements

Code 
`CNA-2014-EMPLOI` %>%
  filter(CNA_TYPE_EMP == "E10",
         CNA_ACTIVITE %in% c("A38-RZ", "A38-MB", "A38-CH"),
         UNIT_MEASURE == "MILLIERS_ACTIFS_OCCUPES_PP") %>%
  left_join(CNA_ACTIVITE,  by = "CNA_ACTIVITE") %>%
  year_to_date %>%
  ggplot() + theme_minimal() + ylab("Nombre d'actifs occupés") + xlab("") +
  geom_line(aes(x = date, y = OBS_VALUE/10^3, color = Cna_activite, linetype = Cna_activite)) +
  
  scale_x_date(breaks = seq(1920, 2100,5) %>% 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, 6, 0.5), seq(0, 1, 0.1), seq(0, 0.1, 0.01)),
                labels = dollar_format(accuracy = 0.01, prefix = "", suffix = "M"),
                limits = c(0.1, 1))

CM-LZ-MC: Autres industries manufacturières ; réparation et installation de machines et d’équipements ; Activités immobilières; Autres activités spécialisées, scientifiques et techniques

Code 
`CNA-2014-EMPLOI` %>%
  filter(CNA_TYPE_EMP == "E10",
         CNA_ACTIVITE %in% c("A38-CM", "A38-LZ", "A38-MC"),
         UNIT_MEASURE == "MILLIERS_ACTIFS_OCCUPES_PP") %>%
  left_join(CNA_ACTIVITE,  by = "CNA_ACTIVITE") %>%
  year_to_date %>%
  ggplot() + theme_minimal() + ylab("Nombre d'actifs occupés") + xlab("") +
  geom_line(aes(x = date, y = OBS_VALUE/10^3, color = Cna_activite, linetype = Cna_activite)) +
  
  scale_x_date(breaks = seq(1920, 2100,5) %>% 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, 6, 0.5), seq(0, 1, 0.1), seq(0, 0.1, 0.01)),
                labels = dollar_format(accuracy = 0.01, prefix = "", suffix = "M"),
                limits = c(0.06, 0.7))

CG-TZ-JA: Fabrication de produits en caoutchouc et en plastique ainsi que d’autres produits minéraux non métalliques ; Activités des ménages en tant qu’employeurs ; activités indifférenciées des ménages en tant que producteurs de biens et services pour usage propre ; Édition, audiovisuel et diffusion

Code 
`CNA-2014-EMPLOI` %>%
  filter(CNA_TYPE_EMP == "E10",
         CNA_ACTIVITE %in% c("A38-CG", "A38-TZ", "A38-JA"),
         UNIT_MEASURE == "MILLIERS_ACTIFS_OCCUPES_PP") %>%
  left_join(CNA_ACTIVITE,  by = "CNA_ACTIVITE") %>%
  year_to_date %>%
  ggplot() + theme_minimal() + ylab("Nombre d'actifs occupés") + xlab("") +
  geom_line(aes(x = date, y = OBS_VALUE/10^3, color = Cna_activite, linetype = Cna_activite)) +
  
  scale_x_date(breaks = seq(1920, 2100,5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = c(0.7, 0.15),
        legend.title = element_blank()) +
  scale_y_log10(breaks = c(seq(0, 6, 0.5), seq(0, 1, 0.1), seq(0, 0.1, 0.01)),
                labels = dollar_format(accuracy = 0.01, prefix = "", suffix = "M"),
                limits = c(0.03, 0.55))

CL-CC-EZ: Fabrication de matériels de transport ; Travail du bois, industries du papier et imprimerie ; Production et distribution d’eau ; assainissement, gestion des déchets et dépollution

Code 
`CNA-2014-EMPLOI` %>%
  filter(CNA_TYPE_EMP == "E10",
         CNA_ACTIVITE %in% c("A38-CL", "A38-CC", "A38-EZ"),
         UNIT_MEASURE == "MILLIERS_ACTIFS_OCCUPES_PP") %>%
  left_join(CNA_ACTIVITE,  by = "CNA_ACTIVITE") %>%
  year_to_date %>%
  ggplot() + theme_minimal() + ylab("Nombre d'actifs occupés") + xlab("") +
  geom_line(aes(x = date, y = OBS_VALUE/10^3, color = Cna_activite, linetype = Cna_activite)) +
  
  scale_x_date(breaks = seq(1920, 2100,5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = c(0.5, 0.15),
        legend.title = element_blank()) +
  scale_y_log10(breaks = c(seq(0, 6, 0.5), seq(0, 1, 0.1), seq(0, 0.1, 0.01)),
                labels = dollar_format(accuracy = 0.01, prefix = "", suffix = "M"),
                limits = c(0.03, 0.5))

A38-CK - Fabrication de machines et équipements n.c.a.
A38-DZ - Production et distribution d’électricité, de gaz, de vapeur et d’air conditionné
A38-CE - Industrie chimique

Code 
`CNA-2014-EMPLOI` %>%
  filter(CNA_TYPE_EMP == "E10",
         CNA_ACTIVITE %in% c("A38-CK", "A38-DZ", "A38-CE"),
         UNIT_MEASURE == "MILLIERS_ACTIFS_OCCUPES_PP") %>%
  left_join(CNA_ACTIVITE,  by = "CNA_ACTIVITE") %>%
  year_to_date %>%
  ggplot() + theme_minimal() + ylab("Nombre d'actifs occupés") + xlab("") +
  geom_line(aes(x = date, y = OBS_VALUE/10^3, color = Cna_activite, linetype = Cna_activite)) +
  
  scale_x_date(breaks = seq(1920, 2100,5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = c(0.5, 0.15),
        legend.title = element_blank()) +
  scale_y_log10(breaks = c(seq(0, 6, 0.5), seq(0, 1, 0.1), seq(0, 0.1, 0.01)),
                labels = dollar_format(accuracy = 0.01, prefix = "", suffix = "M"),
                limits = c(0.07, 0.35))

A38-JB - Télécommunications A38-CB - Fabrication de textiles, industries de l’habillement, industrie du cuir et de la chaussure A38-CI - Fabrication de produits informatiques, électroniques et optiques

Code 
`CNA-2014-EMPLOI` %>%
  filter(CNA_TYPE_EMP == "E10",
         CNA_ACTIVITE %in% c("A38-JB", "A38-CB", "A38-CI"),
         UNIT_MEASURE == "MILLIERS_ACTIFS_OCCUPES_PP") %>%
  left_join(CNA_ACTIVITE,  by = "CNA_ACTIVITE") %>%
  year_to_date %>%
  ggplot() + theme_minimal() + ylab("Nombre d'actifs occupés") + xlab("") +
  geom_line(aes(x = date, y = OBS_VALUE/10^3, color = Cna_activite, linetype = Cna_activite)) +
  
  scale_x_date(breaks = seq(1920, 2100,5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = c(0.5, 0.15),
        legend.title = element_blank()) +
  scale_y_log10(breaks = c(seq(0, 6, 0.5), seq(0, 1, 0.1), seq(0, 0.1, 0.01)),
                labels = dollar_format(accuracy = 0.01, prefix = "", suffix = "M"),
                limits = c(0.07, 1))

A38-CJ - Fabrication d’équipements électriques
A38-CF - Industrie pharmaceutique
A38-BZ - Industries extractives

Code 
`CNA-2014-EMPLOI` %>%
  filter(CNA_TYPE_EMP == "E10",
         CNA_ACTIVITE %in% c("A38-CJ", "A38-CF", "A38-BZ"),
         UNIT_MEASURE == "MILLIERS_ACTIFS_OCCUPES_PP") %>%
  left_join(CNA_ACTIVITE,  by = "CNA_ACTIVITE") %>%
  year_to_date %>%
  ggplot() + theme_minimal() + ylab("Nombre d'actifs occupés") + xlab("") +
  geom_line(aes(x = date, y = OBS_VALUE/10^3, color = Cna_activite, linetype = Cna_activite)) +
  
  scale_x_date(breaks = seq(1920, 2100,5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = c(0.4, 0.25),
        legend.title = element_blank()) +
  scale_y_log10(breaks = c(seq(0, 6, 0.5), seq(0, 1, 0.1), seq(0, 0.1, 0.01)),
                labels = dollar_format(accuracy = 0.01, prefix = "", suffix = "M"),
                limits = c(0.01, 0.2))

CD - Cokéfaction et raffinage

Code 
`CNA-2014-EMPLOI` %>%
  filter(CNA_TYPE_EMP == "E10",
         CNA_ACTIVITE %in% c("A38-CD"),
         UNIT_MEASURE == "MILLIERS_ACTIFS_OCCUPES_PP") %>%
  left_join(CNA_ACTIVITE,  by = "CNA_ACTIVITE") %>%
  year_to_date %>%
  ggplot() + theme_minimal() + ylab("Nombre d'actifs occupés") + xlab("") +
  geom_line(aes(x = date, y = OBS_VALUE/10^3, color = Cna_activite, linetype = Cna_activite)) +
  
  scale_x_date(breaks = seq(1920, 2100,5) %>% 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, 6, 0.5), seq(0, 1, 0.1), seq(0, 0.1, 0.01)),
                labels = dollar_format(accuracy = 0.01, prefix = "", suffix = "M"),
                limits = c(0.005, 0.06))

Emploi 38 Branches - Industrie

CA-CB-CC-CD

Code 
`CNA-2014-EMPLOI` %>%
  filter(CNA_TYPE_EMP == "E10",
         CNA_ACTIVITE %in% c("A38-CA", "A38-CB", "A38-CC", "A38-CD"),
         UNIT_MEASURE == "MILLIERS_ACTIFS_OCCUPES_PP") %>%
  left_join(CNA_ACTIVITE,  by = "CNA_ACTIVITE") %>%
  year_to_date %>%
  ggplot() + theme_minimal() + ylab("Nombre d'actifs occupés") + xlab("") +
  geom_line(aes(x = date, y = OBS_VALUE/10^3, color = Cna_activite, linetype = Cna_activite)) +
  
  scale_x_date(breaks = seq(1920, 2100,5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = c(0.55, 0.4),
        legend.title = element_blank()) +
  scale_y_log10(breaks = c(seq(0, 6, 0.5), seq(0, 1, 0.1), seq(0, 0.1, 0.01)),
                labels = dollar_format(accuracy = 0.01, prefix = "", suffix = "M"))

CE-CF-CG-CH

Code 
`CNA-2014-EMPLOI` %>%
  filter(CNA_TYPE_EMP == "E10",
         CNA_ACTIVITE %in% c("A38-CE", "A38-CF", "A38-CG", "A38-CH"),
         UNIT_MEASURE == "MILLIERS_ACTIFS_OCCUPES_PP") %>%
  left_join(CNA_ACTIVITE,  by = "CNA_ACTIVITE") %>%
  year_to_date %>%
  ggplot() + theme_minimal() + ylab("Nombre d'actifs occupés") + xlab("") +
  geom_line(aes(x = date, y = OBS_VALUE/10^3, color = Cna_activite, linetype = Cna_activite)) +
  
  scale_x_date(breaks = seq(1920, 2100,5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = c(0.55, 0.35),
        legend.title = element_blank()) +
  scale_y_log10(breaks = c(seq(0, 6, 0.5), seq(0, 1, 0.1), seq(0, 0.1, 0.01)),
                labels = dollar_format(accuracy = 0.01, prefix = "", suffix = "M"))

CI-CJ-CK-CL

Code 
`CNA-2014-EMPLOI` %>%
  filter(CNA_TYPE_EMP == "E10",
         CNA_ACTIVITE %in% c("A38-CI", "A38-CJ", "A38-CK", "A38-CL"),
         UNIT_MEASURE == "MILLIERS_ACTIFS_OCCUPES_PP") %>%
  left_join(CNA_ACTIVITE,  by = "CNA_ACTIVITE") %>%
  year_to_date %>%
  ggplot() + theme_minimal() + ylab("Nombre d'actifs occupés") + xlab("") +
  geom_line(aes(x = date, y = OBS_VALUE/10^3, color = Cna_activite, linetype = Cna_activite)) +
  
  scale_x_date(breaks = seq(1920, 2100,5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = c(0.55, 0.15),
        legend.title = element_blank()) +
  scale_y_log10(breaks = c(seq(0, 6, 0.5), seq(0, 1, 0.1), seq(0, 0.1, 0.01)),
                labels = dollar_format(accuracy = 0.01, prefix = "", suffix = "M"))

CM-DZ-EZ-BZ

Code 
`CNA-2014-EMPLOI` %>%
  filter(CNA_TYPE_EMP == "E10",
         CNA_ACTIVITE %in% c("A38-CM", "A38-DZ", "A38-EZ", "A38-BZ"),
         UNIT_MEASURE == "MILLIERS_ACTIFS_OCCUPES_PP") %>%
  left_join(CNA_ACTIVITE,  by = "CNA_ACTIVITE") %>%
  year_to_date %>%
  ggplot() + theme_minimal() + ylab("Nombre d'actifs occupés") + xlab("") +
  geom_line(aes(x = date, y = OBS_VALUE/10^3, color = Cna_activite, linetype = Cna_activite)) +
  
  scale_x_date(breaks = seq(1920, 2100,5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = c(0.45, 0.15),
        legend.title = element_blank()) +
  scale_y_log10(breaks = c(seq(0, 6, 0.5), seq(0, 1, 0.1), seq(0, 0.1, 0.01)),
                labels = dollar_format(accuracy = 0.01, prefix = "", suffix = "M"),
                limits = c(0.01, 0.7))

BZ-CD-CF-CJ: Fabrication de produits en caoutchouc et en plastique ainsi que d’autres produits minéraux non métalliques ; Activités des ménages en tant qu’employeurs ; activités indifférenciées des ménages en tant que producteurs de biens et services pour usage propre ; Édition, audiovisuel et diffusion ; Cokéfaction et raffinage

Code 
`CNA-2014-EMPLOI` %>%
  filter(CNA_TYPE_EMP == "E10",
         CNA_ACTIVITE %in% c("A38-CJ", "A38-CF", "A38-BZ", "A38-CD"),
         UNIT_MEASURE == "MILLIERS_ACTIFS_OCCUPES_PP") %>%
  left_join(CNA_ACTIVITE,  by = "CNA_ACTIVITE") %>%
  year_to_date %>%
  ggplot() + theme_minimal() + ylab("Nombre d'actifs occupés") + xlab("") +
  geom_line(aes(x = date, y = OBS_VALUE/10^3, color = Cna_activite, linetype = Cna_activite)) +
  
  scale_x_date(breaks = seq(1920, 2100,5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = c(0.22, 0.18),
        legend.title = element_blank()) +
  scale_y_log10(breaks = c(seq(0, 6, 0.5), seq(0, 1, 0.1), seq(0, 0.1, 0.01)),
                labels = dollar_format(accuracy = 0.01, prefix = "", suffix = "M"),
                limits = c(0.01, 0.2))

CC-CL-CG-CM: Fabrication de produits en caoutchouc et en plastique ainsi que d’autres produits minéraux non métalliques ; Activités des ménages en tant qu’employeurs ; activités indifférenciées des ménages en tant que producteurs de biens et services pour usage propre ; Édition, audiovisuel et diffusion ; Cokéfaction et raffinage

Code 
`CNA-2014-EMPLOI` %>%
  filter(CNA_TYPE_EMP == "E10",
         CNA_ACTIVITE %in% c("A38-CC", "A38-CL", "A38-CG", "A38-CM"),
         UNIT_MEASURE == "MILLIERS_ACTIFS_OCCUPES_PP") %>%
  left_join(CNA_ACTIVITE,  by = "CNA_ACTIVITE") %>%
  year_to_date %>%
  ggplot() + theme_minimal() + ylab("Nombre d'actifs occupés") + xlab("") +
  geom_line(aes(x = date, y = OBS_VALUE/10^3, color = Cna_activite, linetype = Cna_activite)) +
  
  scale_x_date(breaks = seq(1920, 2100,5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = c(0.5, 0.18),
        legend.title = element_blank()) +
  scale_y_log10(breaks = c(seq(0, 6, 0.5), seq(0, 1, 0.1), seq(0, 0.1, 0.01)),
                labels = dollar_format(accuracy = 0.01, prefix = "", suffix = "M"),
                limits = c(0.1, 0.7))

Code 
`CNA-2014-EMPLOI` %>%
  filter(CNA_TYPE_EMP == "E10",
         CNA_ACTIVITE %in% c("A38-CD"),
         UNIT_MEASURE == "MILLIERS_ACTIFS_OCCUPES_PP") %>%
  left_join(CNA_ACTIVITE,  by = "CNA_ACTIVITE") %>%
  year_to_date %>%
  ggplot() + theme_minimal() + ylab("Nombre d'actifs occupés") + xlab("") +
  geom_line(aes(x = date, y = OBS_VALUE/10^3, color = Cna_activite, linetype = Cna_activite)) +
  
  scale_x_date(breaks = seq(1920, 2100,5) %>% 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, 6, 0.5), seq(0, 1, 0.1), seq(0, 0.1, 0.01)),
                labels = dollar_format(accuracy = 0.01, prefix = "", suffix = "M"),
                limits = c(0.005, 0.06))