Emploi intérieur, durée effective travaillée et productivité horaire - CNA-2010-EMPLOI

Data - INSEE

Author

François Geerolf

TITLE_FR

Code 
`CNA-2010-EMPLOI` %>%
  group_by(IDBANK, TITLE_FR) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}

INDICATEUR

Code 
`CNA-2010-EMPLOI` %>%
  left_join(INDICATEUR,  by = "INDICATEUR") %>%
  group_by(INDICATEUR, Indicateur) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  {if (is_html_output()) print_table(.) else .}
INDICATEUR Indicateur Nobs
CNA_EMPLOI_INTERIEUR Emploi intérieur 26246
CNA_VOLUME_HEURES_TRAV Volume d'heures travaillées 8780
CNA_DUREE_TRAVAILLEE Durée annuelle effective travaillée 4390
CNA_PRODUCTIVITE_HORAIRE Productivité horaire 4320

CNA_ACTIVITE

Code 
`CNA-2010-EMPLOI` %>%
  left_join(CNA_ACTIVITE,  by = "CNA_ACTIVITE") %>%
  group_by(CNA_ACTIVITE, Cna_activite) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}

CNA_TYPE_EMP

Code 
`CNA-2010-EMPLOI` %>%
  left_join(CNA_TYPE_EMP,  by = "CNA_TYPE_EMP") %>%
  group_by(CNA_TYPE_EMP, Cna_type_emp) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  {if (is_html_output()) print_table(.) else .}
CNA_TYPE_EMP Cna_type_emp Nobs
E10 E10 - Emploi intérieur total 17880
E20 E20 - Emploi intérieur salarié 8780
E21 E21 - Emploi intérieur salarié déclaré 8780
E30 E30 - Emploi intérieur non salarié 8296

Emploi Total

1950-

Code 
`CNA-2010-EMPLOI` %>%
  filter(CNA_ACTIVITE %in% c("NNTOTAL"),
         UNIT_MEASURE == "NOMBRE_ACTIFS_OCCUPES_PP",
         `SECT-INST` %in% c("S10"),
         CNA_TYPE_EMP == "E10") %>%
  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/10^6, color = `SECT-INST`, linetype = `SECT-INST`)) +
  scale_color_manual(values = viridis(5)[1:4]) +
  scale_x_date(breaks = seq(1920, 2025, 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, 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-2010-EMPLOI` %>%
  filter(CNA_ACTIVITE %in% c("NNTOTAL"),
         UNIT_MEASURE == "NOMBRE_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/10^6, color = `SECT-INST`, linetype = `SECT-INST`)) +
  scale_color_manual(values = viridis(5)[1:4]) +
  scale_x_date(breaks = seq(1920, 2025, 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-2010-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
NA
:-------:

A10

Code 
`CNA-2010-EMPLOI` %>%
  filter(CNA_TYPE_EMP == "E10",
         TIME_PERIOD == "2016",
         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", "%")) %>%
  arrange(-ETP) %>%
  {if (is_html_output()) print_table(.) else .}
Secteur Heures ETP PP %
A10-OQ - Administration publique, enseignement, santé humaine et action sociale 11386021936 7765239.5 8313409.7 0.8
A10-GI - Commerce de gros et de détail, transports, hébergement et restauration 9428087395 5704528.3 6211586.1 1.8
A10-MN - Activités spécialisées, scientifiques et techniques et activités de services administratifs et de soutien 6275211050 3834017.2 4114653.0 -0.8
A10-BE - Industrie manufacturière, industries extractives et autres 4610381309 2845285.1 2932674.6 2.8
A10-FZ - Construction 3020347378 1754756.3 1743479.8 1.9
A10-RU - Autres activités de services 2151062902 1390690.1 1583419.3 0.7
A10-AZ - Agriculture, sylviculture et pêche 1521695444 807383.7 742572.6 -9.0
A10-JZ - Information et communication 1323236931 804159.1 831623.5 1.5
A10-KZ - Activités financières et d'assurance 1257113073 769395.3 792383.7 -1.7
A10-LZ - Activités immobilières 520182596 328117.6 346157.8 0.7

A17

Code 
`CNA-2010-EMPLOI` %>%
  filter(CNA_TYPE_EMP == "E10",
         TIME_PERIOD == "2016",
         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 1521695444 807383.7 742572.6 -9.0
A17-C1 A17-C1 - Fabrication de denrées alimentaires, de boissons et de produits à base de tabac 1007959147 620088.7 647542.1 -1.3
A17-C2 A17-C2 - Cokéfaction et raffinage 12018027 7950.8 8133.0 -20.1
A17-C3 A17-C3 - Fabrication d'équipements électriques, électroniques, informatiques ; fabrication de machines 495506193 301431.0 309088.7 6.7
A17-C4 A17-C4 - Fabrication de matériels de transport 297371314 183912.9 188672.3 8.6
A17-C5 A17-C5 - Fabrication d'autres produits industriels 2322236646 1432148.2 1472589.0 2.6
A17-DE A17-DE - Industries extractives, énergie, eau, gestion des déchets et dépollution 475289982 299753.4 306649.5 2.2
A17-FZ A17-FZ - Construction 3020347378 1754756.3 1743479.8 1.9
A17-GZ A17-GZ - Commerce ; réparation d'automobiles et de motocycles 5505838066 3343618.0 3648366.6 1.2
A17-HZ A17-HZ - Transports et entreposage 2069759241 1305832.3 1367213.9 3.4
A17-IZ A17-IZ - Hébergement et restauration 1852490088 1055077.9 1196005.6 1.8
A17-JZ A17-JZ - Information et communication 1323236931 804159.1 831623.5 1.5
A17-KZ A17-KZ - Activités financières et d'assurance 1257113073 769395.3 792383.7 -1.7
A17-LZ A17-LZ - Activités immobilières 520182596 328117.6 346157.8 0.7
A17-MN A17-MN - Activités scientifiques et techniques ; services administratifs et de soutien 6275211050 3834017.2 4114653.0 -0.8
A17-OQ A17-OQ - Administration publique, enseignement, santé humaine et action sociale 11386021936 7765239.5 8313409.7 0.8
A17-RU A17-RU - Autres activités de services 2151062902 1390690.1 1583419.3 0.7

A38

Code 
`CNA-2010-EMPLOI` %>%
  filter(CNA_TYPE_EMP == "E10",
         TIME_PERIOD == "2016",
         grepl("A38", 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", "%")) %>%
  arrange(-ETP) %>%
  {if (is_html_output()) print_table(.) else .}
Secteur Heures ETP PP %
A38-AZ - Agriculture, sylviculture et pêche NaN NaN NaN NaN
A38-BZ - Industries extractives NaN NaN NaN NaN
A38-CA - Fabrication de denrées alimentaires, de boissons et de produits à base de tabac NaN NaN NaN NaN
A38-CB - Fabrication de textiles, industries de l'habillement, industrie du cuir et de la chaussure NaN NaN NaN NaN
A38-CC - Travail du bois, industries du papier et imprimerie NaN NaN NaN NaN
A38-CD - Cokéfaction et raffinage NaN NaN NaN NaN
A38-CE - Industrie chimique NaN NaN NaN NaN
A38-CF - Industrie pharmaceutique NaN NaN NaN NaN
A38-CG - Fabrication de produits en caoutchouc et en plastique ainsi que d'autres produits minéraux non métalliques NaN NaN NaN NaN
A38-CH - Métallurgie et fabrication de produits métalliques à l'exception des machines et des équipements NaN NaN NaN NaN
A38-CI - Fabrication de produits informatiques, électroniques et optiques NaN NaN NaN NaN
A38-CJ - Fabrication d'équipements électriques NaN NaN NaN NaN
A38-CK - Fabrication de machines et équipements n.c.a. NaN NaN NaN NaN
A38-CL - Fabrication de matériels de transport NaN NaN NaN NaN
A38-CM - Autres industries manufacturières ; réparation et installation de machines et d'équipements NaN NaN NaN NaN
A38-DZ - Production et distribution d'électricité, de gaz, de vapeur et d'air conditionné NaN NaN NaN NaN
A38-EZ - Production et distribution d'eau ; assainissement, gestion des déchets et dépollution NaN NaN NaN NaN
A38-FZ - Construction NaN NaN NaN NaN
A38-GZ - Commerce; réparation d'automobiles et de motocycles NaN NaN NaN NaN
A38-HZ - Transports et entreposage NaN NaN NaN NaN
A38-IZ - Hébergement et restauration NaN NaN NaN NaN
A38-JA - Édition, audiovisuel et diffusion NaN NaN NaN NaN
A38-JB - Télécommunications NaN NaN NaN NaN
A38-JC - Activités informatiques et services d'information NaN NaN NaN NaN
A38-KZ - Activités financières et d'assurance NaN NaN NaN NaN
A38-LZ - Activités immobilières NaN NaN NaN NaN
A38-MA - Activités juridiques, comptables, de gestion, d'architecture, d'ingénierie, de contrôle et d'analyses techniques NaN NaN NaN NaN
A38-MB - Recherche-développement scientifique NaN NaN NaN NaN
A38-MC - Autres activités spécialisées, scientifiques et techniques NaN NaN NaN NaN
A38-NZ - Activités de services administratifs et de soutien NaN NaN NaN NaN
A38-OZ - Administration publique NaN NaN NaN NaN
A38-PZ - Enseignement NaN NaN NaN NaN
A38-QA - Activités pour la santé humaine NaN NaN NaN NaN
A38-QB - Hébergement médico-social et social et action sociale sans hébergement NaN NaN NaN NaN
A38-RZ - Arts, spectacles et activités récréatives NaN NaN NaN NaN
A38-SZ - Autres activités de services NaN NaN NaN NaN
A38-TZ - Activités des ménages en tant qu'employeurs ; activités indifférenciées des ménages en tant que producteurs de biens et services pour usage propre NaN NaN NaN NaN

Emploi 10 Branches (2010-)

Construction - Manuf - Agriculture

Code 
`CNA-2010-EMPLOI` %>%
  filter(CNA_TYPE_EMP == "E10",
         CNA_ACTIVITE %in% c("A10-FZ", "A10-BE", "A10-AZ"),
         UNIT_MEASURE == "NOMBRE_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/10^6, color = Cna_activite, linetype = Cna_activite)) +
  scale_color_manual(values = viridis(4)[1:3]) +
  scale_x_date(breaks = seq(1920, 2025, 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"))

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

Code 
`CNA-2010-EMPLOI` %>%
  filter(CNA_TYPE_EMP == "E10",
         CNA_ACTIVITE %in% c("A10-OQ", "A10-GI", "A10-MN", "A10-RU"),
         UNIT_MEASURE == "NOMBRE_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)) +
  scale_color_manual(values = viridis(5)[1:4]) +
  theme_minimal() +
  scale_x_date(breaks = seq(1920, 2025, 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("")

Information-Communication - Activités Financières - Immobilières

Code 
`CNA-2010-EMPLOI` %>%
  filter(CNA_TYPE_EMP == "E10",
         CNA_ACTIVITE %in% c("A10-JZ", "A10-KZ", "A10-LZ"),
         UNIT_MEASURE == "NOMBRE_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)) +
  scale_color_manual(values = viridis(4)[1:3]) +
  theme_minimal() +
  scale_x_date(breaks = seq(1920, 2025, 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

Construction - Manuf - Agriculture

Code 
`CNA-2010-EMPLOI` %>%
  filter(CNA_TYPE_EMP == "E10",
         CNA_ACTIVITE %in% c("A10-FZ", "A10-BE", "A10-AZ"),
         UNIT_MEASURE == "NOMBRE_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/10^6, color = Cna_activite, linetype = Cna_activite)) +
  scale_color_manual(values = viridis(4)[1:3]) +
  scale_x_date(breaks = seq(1920, 2025, 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"))

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

Code 
`CNA-2010-EMPLOI` %>%
  filter(CNA_TYPE_EMP == "E10",
         CNA_ACTIVITE %in% c("A10-OQ", "A10-GI", "A10-MN", "A10-RU"),
         UNIT_MEASURE == "NOMBRE_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)) +
  scale_color_manual(values = viridis(5)[1:4]) +
  theme_minimal() +
  scale_x_date(breaks = seq(1920, 2025, 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("")

Information-Communication - Activités Financières - Immobilières

Code 
`CNA-2010-EMPLOI` %>%
  filter(CNA_TYPE_EMP == "E10",
         CNA_ACTIVITE %in% c("A10-JZ", "A10-KZ", "A10-LZ"),
         UNIT_MEASURE == "NOMBRE_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)) +
  scale_color_manual(values = viridis(4)[1:3]) +
  theme_minimal() +
  scale_x_date(breaks = seq(1920, 2025, 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

Fabrication denrées alimentaires, équipements électriques, matériels de transport

Code 
`CNA-2010-EMPLOI` %>%
  filter(CNA_TYPE_EMP == "E10",
         CNA_ACTIVITE %in% c("A17-C1", "A17-C4", "A17-C3"),
         UNIT_MEASURE == "NOMBRE_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/10^6, color = Cna_activite, linetype = Cna_activite)) +
  scale_color_manual(values = viridis(4)[1:3]) +
  scale_x_date(breaks = seq(1920, 2025, 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))

Cokéfaction - Autres produits - Industries extractives

Code 
`CNA-2010-EMPLOI` %>%
  filter(CNA_TYPE_EMP == "E10",
         CNA_ACTIVITE %in% c("A17-C2", "A17-C5", "A17-DE"),
         UNIT_MEASURE == "NOMBRE_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/10^6, color = Cna_activite, linetype = Cna_activite)) +
  scale_color_manual(values = viridis(4)[1:3]) +
  scale_x_date(breaks = seq(1920, 2025, 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

Commerce; réparation; Santé; Hébergement médico-social

Code 
`CNA-2010-EMPLOI` %>%
  filter(CNA_TYPE_EMP == "E10",
         CNA_ACTIVITE %in% c("A38-QA", "A38-QB", "A38-GZ"),
         UNIT_MEASURE == "NOMBRE_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/10^6, color = Cna_activite, linetype = Cna_activite)) +
  scale_color_manual(values = viridis(4)[1:3]) +
  scale_x_date(breaks = seq(1920, 2025, 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))

Administration publique, Activités de service administratifs, Enseignement

Code 
`CNA-2010-EMPLOI` %>%
  filter(CNA_TYPE_EMP == "E10",
         CNA_ACTIVITE %in% c("A38-OZ", "A38-NZ", "A38-PZ"),
         UNIT_MEASURE == "NOMBRE_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/10^6, color = Cna_activite, linetype = Cna_activite)) +
  scale_color_manual(values = viridis(4)[1:3]) +
  scale_x_date(breaks = seq(1920, 2025, 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"))

Construction; Transports et entreposage; Activités juridiques, comptables, de gestion, d’architecture, d’ingénierie, de contrôle et d’analyses techniques

Code 
`CNA-2010-EMPLOI` %>%
  filter(CNA_TYPE_EMP == "E10",
         CNA_ACTIVITE %in% c("A38-FZ", "A38-HZ", "A38-MA"),
         UNIT_MEASURE == "NOMBRE_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/10^6, color = Cna_activite, linetype = Cna_activite)) +
  scale_color_manual(values = viridis(4)[1:3]) +
  scale_x_date(breaks = seq(1920, 2025, 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))

Hébergement et restauration; Agriculture, sylviculture et pêche; Activités financières et d’assurance

Code 
`CNA-2010-EMPLOI` %>%
  filter(CNA_TYPE_EMP == "E10",
         CNA_ACTIVITE %in% c("A38-IZ", "A38-AZ", "A38-KZ"),
         UNIT_MEASURE == "NOMBRE_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/10^6, color = Cna_activite, linetype = Cna_activite)) +
  scale_color_manual(values = viridis(4)[1:3]) +
  scale_x_date(breaks = seq(1920, 2025, 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))

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-2010-EMPLOI` %>%
  filter(CNA_TYPE_EMP == "E10",
         CNA_ACTIVITE %in% c("A38-SZ", "A38-CA", "A38-JC"),
         UNIT_MEASURE == "NOMBRE_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/10^6, color = Cna_activite, linetype = Cna_activite)) +
  scale_color_manual(values = viridis(4)[1:3]) +
  scale_x_date(breaks = seq(1920, 2025, 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))

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

Code 
`CNA-2010-EMPLOI` %>%
  filter(CNA_TYPE_EMP == "E10",
         CNA_ACTIVITE %in% c("A38-RZ", "A38-MB", "A38-CH"),
         UNIT_MEASURE == "NOMBRE_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/10^6, color = Cna_activite, linetype = Cna_activite)) +
  scale_color_manual(values = viridis(4)[1:3]) +
  scale_x_date(breaks = seq(1920, 2025, 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))

Autres industries manufacturières ; réparation et installation de machines et d’équipements ; Activités immobilières; Autres activités spécialisées, scientifiques et techniques

Code 
`CNA-2010-EMPLOI` %>%
  filter(CNA_TYPE_EMP == "E10",
         CNA_ACTIVITE %in% c("A38-CM", "A38-LZ", "A38-MC"),
         UNIT_MEASURE == "NOMBRE_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/10^6, color = Cna_activite, linetype = Cna_activite)) +
  scale_color_manual(values = viridis(4)[1:3]) +
  scale_x_date(breaks = seq(1920, 2025, 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))

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-2010-EMPLOI` %>%
  filter(CNA_TYPE_EMP == "E10",
         CNA_ACTIVITE %in% c("A38-CG", "A38-TZ", "A38-JA"),
         UNIT_MEASURE == "NOMBRE_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/10^6, color = Cna_activite, linetype = Cna_activite)) +
  scale_color_manual(values = viridis(4)[1:3]) +
  scale_x_date(breaks = seq(1920, 2025, 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))

A38-CL - Fabrication de matériels de transport
A38-CC - Travail du bois, industries du papier et imprimerie
A38-EZ - Production et distribution d’eau ; assainissement, gestion des déchets et dépollution

Code 
`CNA-2010-EMPLOI` %>%
  filter(CNA_TYPE_EMP == "E10",
         CNA_ACTIVITE %in% c("A38-CL", "A38-CC", "A38-EZ"),
         UNIT_MEASURE == "NOMBRE_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/10^6, color = Cna_activite, linetype = Cna_activite)) +
  scale_color_manual(values = viridis(4)[1:3]) +
  scale_x_date(breaks = seq(1920, 2025, 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-2010-EMPLOI` %>%
  filter(CNA_TYPE_EMP == "E10",
         CNA_ACTIVITE %in% c("A38-CK", "A38-DZ", "A38-CE"),
         UNIT_MEASURE == "NOMBRE_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/10^6, color = Cna_activite, linetype = Cna_activite)) +
  scale_color_manual(values = viridis(4)[1:3]) +
  scale_x_date(breaks = seq(1920, 2025, 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-2010-EMPLOI` %>%
  filter(CNA_TYPE_EMP == "E10",
         CNA_ACTIVITE %in% c("A38-JB", "A38-CB", "A38-CI"),
         UNIT_MEASURE == "NOMBRE_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/10^6, color = Cna_activite, linetype = Cna_activite)) +
  scale_color_manual(values = viridis(4)[1:3]) +
  scale_x_date(breaks = seq(1920, 2025, 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-2010-EMPLOI` %>%
  filter(CNA_TYPE_EMP == "E10",
         CNA_ACTIVITE %in% c("A38-CJ", "A38-CF", "A38-BZ"),
         UNIT_MEASURE == "NOMBRE_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/10^6, color = Cna_activite, linetype = Cna_activite)) +
  scale_color_manual(values = viridis(4)[1:3]) +
  scale_x_date(breaks = seq(1920, 2025, 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))

Cokéfaction et raffinage

Code 
`CNA-2010-EMPLOI` %>%
  filter(CNA_TYPE_EMP == "E10",
         CNA_ACTIVITE %in% c("A38-CD"),
         UNIT_MEASURE == "NOMBRE_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/10^6, color = Cna_activite, linetype = Cna_activite)) +
  scale_color_manual(values = viridis(4)[1:3]) +
  scale_x_date(breaks = seq(1920, 2025, 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))