Emploi salarié en fin d’année en France métropolitaine selon le secteur d’activité (A88) - T102B

Data - INSEE

Author

François Geerolf

A38 VS A88

Code 
A38 %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}

A88

Code 
A88 %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}

Tous

Code 
T102B %>%
  group_by(a88, A88) %>%
  summarise(Nobs = n(),
            value2018 = value[date == as.Date("2019-01-01")]) %>%
  arrange(-value2018) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}

Agriculture

2018

Code 
T102B %>%
  mutate(a88 = as.numeric(a88)) %>%
  filter(a88 < 5) %>%
  group_by(a88, A88) %>%
  summarise(Nobs = n(),
            value2018 = value[date == as.Date("2019-01-01")]) %>%
  arrange(-value2018) %>%
  {if (is_html_output()) print_table(.) else .}
a88 A88 Nobs value2018
1 Culture et production animale, chasse et services annexes 31 231
2 Sylviculture et exploitation forestière 31 21
3 Pêche et aquaculture 31 18

Culture et production animale, Pêche, Sylviculture

Code 
T102B %>%
  filter(a88 %in% c("01", "02", "03")) %>%
  ggplot() + theme_minimal() + ylab("Emploi salarié (en milliers)") + xlab("") +
  geom_line(aes(x = date, y = value, color = A88, linetype = A88)) +
  scale_color_manual(values = viridis(4)[1:3]) +
  scale_x_date(breaks = seq(1920, 2025, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%y")) +
  theme(legend.position = c(0.6, 0.6),
        legend.title = element_blank()) +
  scale_y_log10(breaks = seq(10, 3000, 10),
                labels = dollar_format(accuracy = 1, prefix = "", suffix = " K"))

Industrie

2018

Code 
T102B %>%
  mutate(a88 = as.numeric(a88)) %>%
  filter(a88 >= 5, a88 <= 39) %>%
  group_by(a88, A88) %>%
  summarise(Nobs = n(),
            value2018 = value[date == as.Date("2019-01-01")]) %>%
  arrange(-value2018) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}

Industries alimentaires, Produits métalliques, automobile

Code 
T102B %>%
  filter(a88 %in% c("10", "25", "29")) %>%
  ggplot() + theme_minimal() + ylab("Emploi salarié (en milliers)") + xlab("") +
  geom_line(aes(x = date, y = value, color = A88, linetype = A88)) +
  scale_color_manual(values = viridis(4)[1:3]) +
  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 = seq(100, 3000, 100),
                labels = dollar_format(accuracy = 1, prefix = "", suffix = " K"),
                limits = c(100, 600))

Machines, Production & Distribution électricité, Réparation

Code 
T102B %>%
  filter(a88 %in% c("28", "35", "33")) %>%
  ggplot() + theme_minimal() + ylab("Emploi salarié (en milliers)") + xlab("") +
  geom_line(aes(x = date, y = value, color = A88, linetype = A88)) +
  scale_color_manual(values = viridis(4)[1:3]) +
  scale_x_date(breaks = seq(1920, 2025, 2) %>% 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(100, 3000, 10),
                labels = dollar_format(accuracy = 1, prefix = "", suffix = " K"),
                limits = c(150, 350))

Caoutchouc, Autres matériel de transport, industrie chimique

Code 
T102B %>%
  filter(a88 %in% c("22", "30", "20")) %>%
  ggplot() + theme_minimal() + ylab("Emploi salarié (en milliers)") + xlab("") +
  geom_line(aes(x = date, y = value, color = A88, linetype = A88)) +
  scale_color_manual(values = viridis(4)[1:3]) +
  scale_x_date(breaks = seq(1920, 2025, 2) %>% 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(100, 3000, 10),
                labels = dollar_format(accuracy = 1, prefix = "", suffix = " K"),
                limits = c(130, 300))

Produits informatiques, Collecte déchets, équipements électriques

Code 
T102B %>%
  filter(a88 %in% c("26", "38", "27")) %>%
  ggplot() + theme_minimal() + ylab("Emploi salarié (en milliers)") + xlab("") +
  geom_line(aes(x = date, y = value, color = A88, linetype = A88)) +
  scale_color_manual(values = viridis(4)[1:3]) +
  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 = seq(20, 250, 20),
                labels = dollar_format(accuracy = 1, prefix = "", suffix = " K"),
                limits = c(20, 250))

Fabrication d’autres produits minéraux, Métallurgie, Pharmacie

Code 
T102B %>%
  filter(a88 %in% c("23", "24", "21")) %>%
  ggplot() + theme_minimal() + ylab("Emploi salarié (en milliers)") + xlab("") +
  geom_line(aes(x = date, y = value, color = A88, linetype = A88)) +
  scale_color_manual(values = viridis(4)[1:3]) +
  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 = seq(20, 250, 20),
                labels = dollar_format(accuracy = 1, prefix = "", suffix = " K"),
                limits = c(40, 200))

Autres idustries manuf, Industrie du papier et du carton, Travail du bois

Code 
T102B %>%
  filter(a88 %in% c("32", "16", "17")) %>%
  ggplot() + theme_minimal() + ylab("Emploi salarié (en milliers)") + xlab("") +
  geom_line(aes(x = date, y = value, color = A88, linetype = A88)) +
  scale_color_manual(values = viridis(4)[1:3]) +
  scale_x_date(breaks = seq(1920, 2025, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%y")) +
  theme(legend.position = c(0.74, 0.2),
        legend.title = element_blank()) +
  scale_y_log10(breaks = seq(20, 250, 10),
                labels = dollar_format(accuracy = 1, prefix = "", suffix = " K"),
                limits = c(50, 120))

Imprimerie, Distribution eau, Fabrication de textiles

Code 
T102B %>%
  filter(a88 %in% c("18", "36", "13")) %>%
  ggplot() + theme_minimal() + ylab("Emploi salarié (en milliers)") + xlab("") +
  geom_line(aes(x = date, y = value, color = A88, linetype = A88)) +
  scale_color_manual(values = viridis(4)[1:3]) +
  scale_x_date(breaks = seq(1920, 2025, 2) %>% 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 = seq(20, 250, 10),
                labels = dollar_format(accuracy = 1, prefix = "", suffix = " K"),
                limits = c(20, 180))

Boissons, Meubles, Chaussure

Code 
T102B %>%
  filter(a88 %in% c("11", "31", "15")) %>%
  ggplot() + theme_minimal() + ylab("Emploi salarié (en milliers)") + xlab("") +
  geom_line(aes(x = date, y = value, color = A88, linetype = A88)) +
  scale_color_manual(values = viridis(4)[1:3]) +
  scale_x_date(breaks = seq(1920, 2025, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%y")) +
  theme(legend.position = c(0.7, 0.85),
        legend.title = element_blank()) +
  scale_y_log10(breaks = seq(20, 250, 10),
                labels = dollar_format(accuracy = 1, prefix = "", suffix = " K"),
                limits = c(20, 140))

Habillement, Eaux, Industries extractives

Code 
T102B %>%
  filter(a88 %in% c("14", "37", "08")) %>%
  ggplot() + theme_minimal() + ylab("Emploi salarié (en milliers)") + xlab("") +
  geom_line(aes(x = date, y = value, color = A88, linetype = A88)) +
  scale_color_manual(values = viridis(4)[1:3]) +
  scale_x_date(breaks = seq(1920, 2025, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%y")) +
  theme(legend.position = c(0.7, 0.85),
        legend.title = element_blank()) +
  scale_y_log10(breaks = seq(10, 250, 10),
                labels = dollar_format(accuracy = 1, prefix = "", suffix = " K"))

Cokéfaction, Dépollution, Tabac

Code 
T102B %>%
  filter(a88 %in% c("19", "39", "12")) %>%
  ggplot() + theme_minimal() + ylab("Emploi salarié (en milliers)") + xlab("") +
  geom_line(aes(x = date, y = value, color = A88, linetype = A88)) +
  scale_color_manual(values = viridis(4)[1:3]) +
  scale_x_date(breaks = seq(1920, 2025, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%y")) +
  theme(legend.position = c(0.6, 0.9),
        legend.title = element_blank()) +
  scale_y_log10(breaks = c(seq(1, 10, 1), seq(10, 250, 10)),
                labels = dollar_format(accuracy = 1, prefix = "", suffix = " K"),
                limits = c(1, 30))

Houille, Hydrocarbures, Minerais

Code 
T102B %>%
  filter(a88 %in% c("05", "06", "07")) %>%
  ggplot() + theme_minimal() + ylab("Emploi salarié (en milliers)") + xlab("") +
  geom_line(aes(x = date, y = value, color = A88, linetype = A88)) +
  scale_color_manual(values = viridis(4)[1:3]) +
  scale_x_date(breaks = seq(1920, 2025, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%y")) +
  theme(legend.position = c(0.6, 0.9),
        legend.title = element_blank()) +
  scale_y_log10(breaks = c(seq(1, 10, 1), seq(10, 250, 10)),
                labels = dollar_format(accuracy = 1, prefix = "", suffix = " K"),
                limits = c(1, 30))

Services

2018

Code 
T102B %>%
  mutate(a88 = as.numeric(a88)) %>%
  filter(a88 > 39) %>%
  group_by(a88, A88) %>%
  summarise(Nobs = n(),
            value2018 = value[date == as.Date("2019-01-01")]) %>%
  arrange(-value2018) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}

Administration, commerce de détail, enseignement

Code 
T102B %>%
  filter(a88 %in% c("84", "47", "85")) %>%
  ggplot() + theme_minimal() + ylab("Emploi salarié (en milliers)") + xlab("") +
  geom_line(aes(x = date, y = value, color = A88, linetype = A88)) +
  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(0.6, 0.6),
        legend.title = element_blank()) +
  scale_y_log10(breaks = seq(200, 3000, 100),
                labels = dollar_format(accuracy = 1, prefix = "", suffix = " K"))

Santé, Action sociale, Travaux de construction

Code 
T102B %>%
  filter(a88 %in% c("86", "88", "43")) %>%
  ggplot() + theme_minimal() + ylab("Emploi salarié (en milliers)") + xlab("") +
  geom_line(aes(x = date, y = value, color = A88, linetype = A88)) +
  scale_color_manual(values = viridis(4)[1:3]) +
  scale_x_date(breaks = seq(1920, 2025, 2) %>% 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(200, 3000, 100),
                labels = dollar_format(accuracy = 1, prefix = "", suffix = " K"))

Commerce de gros, Activités liées à l’emploi, Restauration

Code 
T102B %>%
  filter(a88 %in% c("46", "78", "56")) %>%
  ggplot() + theme_minimal() + ylab("Emploi salarié (en milliers)") + xlab("") +
  geom_line(aes(x = date, y = value, color = A88, linetype = A88)) +
  scale_color_manual(values = viridis(4)[1:3]) +
  scale_x_date(breaks = seq(1920, 2025, 2) %>% 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 = seq(200, 3000, 100),
                labels = dollar_format(accuracy = 1, prefix = "", suffix = " K"))

Transports terrestres, Hébergement médico-social

Code 
T102B %>%
  filter(a88 %in% c("49", "87", "64")) %>%
  ggplot() + theme_minimal() + ylab("Emploi salarié (en milliers)") + xlab("") +
  geom_line(aes(x = date, y = value, color = A88, linetype = A88)) +
  scale_color_manual(values = viridis(4)[1:3]) +
  scale_x_date(breaks = seq(1920, 2025, 2) %>% 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 = seq(200, 3000, 100),
                labels = dollar_format(accuracy = 1, prefix = "", suffix = " K"))

Services relatifs aux batiments, Personnel domestique, Architecture & ingénierie

Code 
T102B %>%
  filter(a88 %in% c("81", "97", "71")) %>%
  ggplot() + theme_minimal() + ylab("Emploi salarié (en milliers)") + xlab("") +
  geom_line(aes(x = date, y = value, color = A88, linetype = A88)) +
  scale_color_manual(values = viridis(4)[1:3]) +
  scale_x_date(breaks = seq(1920, 2025, 2) %>% 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 = seq(200, 3000, 100),
                labels = dollar_format(accuracy = 1, prefix = "", suffix = " K"))

Sièges sociaux, Programmation, Commerce

Code 
T102B %>%
  filter(a88 %in% c("70", "62", "45")) %>%
  ggplot() + theme_minimal() + ylab("Emploi salarié (en milliers)") + xlab("") +
  geom_line(aes(x = date, y = value, color = A88, linetype = A88)) +
  scale_color_manual(values = viridis(4)[1:3]) +
  scale_x_date(breaks = seq(1920, 2025, 2) %>% 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 = seq(100, 3000, 100),
                labels = dollar_format(accuracy = 1, prefix = "", suffix = " K"))

Entreposage, Associations, Soutien aux entreprises

Code 
T102B %>%
  filter(a88 %in% c("52", "94", "82")) %>%
  ggplot() + theme_minimal() + ylab("Emploi salarié (en milliers)") + xlab("") +
  geom_line(aes(x = date, y = value, color = A88, linetype = A88)) +
  scale_color_manual(values = viridis(4)[1:3]) +
  scale_x_date(breaks = seq(1920, 2025, 2) %>% 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 = seq(20, 3000, 20),
                labels = dollar_format(accuracy = 1, prefix = "", suffix = " K"),
                limits = c(80, 380))

Activités juridiques, Immobilier, Poste

Code 
T102B %>%
  filter(a88 %in% c("69", "68", "53")) %>%
  ggplot() + theme_minimal() + ylab("Emploi salarié (en milliers)") + xlab("") +
  geom_line(aes(x = date, y = value, color = A88, linetype = A88)) +
  scale_color_manual(values = viridis(4)[1:3]) +
  scale_x_date(breaks = seq(1920, 2025, 2) %>% 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 = seq(20, 3000, 20),
                labels = dollar_format(accuracy = 1, prefix = "", suffix = " K"),
                limits = c(160, 380))

Hébergement, Autres services, Assurance

Code 
T102B %>%
  filter(a88 %in% c("55", "96", "65")) %>%
  ggplot() + theme_minimal() + ylab("Emploi salarié (en milliers)") + xlab("") +
  geom_line(aes(x = date, y = value, color = A88, linetype = A88)) +
  scale_color_manual(values = viridis(4)[1:3]) +
  scale_x_date(breaks = seq(1920, 2025, 2) %>% 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 = seq(20, 3000, 20),
                labels = dollar_format(accuracy = 1, prefix = "", suffix = " K"),
                limits = c(120, 260))

R & D, Génie civil, Enquêtes et sécurité

Code 
T102B %>%
  filter(a88 %in% c("72", "42", "80")) %>%
  ggplot() + theme_minimal() + ylab("Emploi salarié (en milliers)") + xlab("") +
  geom_line(aes(x = date, y = value, color = A88, linetype = A88)) +
  scale_color_manual(values = viridis(4)[1:3]) +
  scale_x_date(breaks = seq(1920, 2025, 2) %>% 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 = seq(20, 3000, 20),
                labels = dollar_format(accuracy = 1, prefix = "", suffix = " K"),
                limits = c(100, 180))

Activités auxiliaires de services financiers, Activités sportives, Construction de bâtiments

Code 
T102B %>%
  filter(a88 %in% c("66", "93", "41")) %>%
  ggplot() + theme_minimal() + ylab("Emploi salarié (en milliers)") + xlab("") +
  geom_line(aes(x = date, y = value, color = A88, linetype = A88)) +
  scale_color_manual(values = viridis(4)[1:3]) +
  scale_x_date(breaks = seq(1920, 2025, 2) %>% 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 = seq(20, 3000, 20),
                labels = dollar_format(accuracy = 1, prefix = "", suffix = " K"),
                limits = c(60, 180))

Publicité et études de marché, Edition, Télécommunications

Code 
T102B %>%
  filter(a88 %in% c("73", "58", "61")) %>%
  ggplot() + theme_minimal() + ylab("Emploi salarié (en milliers)") + xlab("") +
  geom_line(aes(x = date, y = value, color = A88, linetype = A88)) +
  scale_color_manual(values = viridis(4)[1:3]) +
  scale_x_date(breaks = seq(1920, 2025, 2) %>% 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 = seq(20, 3000, 20),
                labels = dollar_format(accuracy = 1, prefix = "", suffix = " K"),
                limits = c(100, 180))

Activités de location, Activités artistiques, Transports aériens

Code 
T102B %>%
  filter(a88 %in% c("77", "90", "51")) %>%
  ggplot() + theme_minimal() + ylab("Emploi salarié (en milliers)") + xlab("") +
  geom_line(aes(x = date, y = value, color = A88, linetype = A88)) +
  scale_color_manual(values = viridis(4)[1:3]) +
  scale_x_date(breaks = seq(1920, 2025, 2) %>% 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 = seq(20, 3000, 20),
                labels = dollar_format(accuracy = 1, prefix = "", suffix = " K"))

Services d’information, Arts, Films

Code 
T102B %>%
  filter(a88 %in% c("63", "74", "59")) %>%
  ggplot() + theme_minimal() + ylab("Emploi salarié (en milliers)") + xlab("") +
  geom_line(aes(x = date, y = value, color = A88, linetype = A88)) +
  scale_color_manual(values = viridis(4)[1:3]) +
  scale_x_date(breaks = seq(1920, 2025, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%y")) +
  theme(legend.position = c(0.7, 0.85),
        legend.title = element_blank()) +
  scale_y_log10(breaks = seq(10, 3000, 10),
                labels = dollar_format(accuracy = 1, prefix = "", suffix = " K"))

Agences de voyage, Bibliothèques, Programmation et diffusion

Code 
T102B %>%
  filter(a88 %in% c("79", "91", "60")) %>%
  ggplot() + theme_minimal() + ylab("Emploi salarié (en milliers)") + xlab("") +
  geom_line(aes(x = date, y = value, color = A88, linetype = A88)) +
  scale_color_manual(values = viridis(4)[1:3]) +
  scale_x_date(breaks = seq(1920, 2025, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%y")) +
  theme(legend.position = c(0.5, 0.85),
        legend.title = element_blank()) +
  scale_y_log10(breaks = seq(20, 3000, 5),
                labels = dollar_format(accuracy = 1, prefix = "", suffix = " K"))

Ordinateurs, Jeux hasard, Vétérinaires

Code 
T102B %>%
  filter(a88 %in% c("95", "92", "75")) %>%
  ggplot() + theme_minimal() + ylab("Emploi salarié (en milliers)") + xlab("") +
  geom_line(aes(x = date, y = value, color = A88, linetype = A88)) +
  scale_color_manual(values = viridis(4)[1:3]) +
  scale_x_date(breaks = seq(1920, 2025, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%y")) +
  theme(legend.position = c(0.4, 0.7),
        legend.title = element_blank()) +
  scale_y_log10(breaks = seq(5, 3000, 5),
                labels = dollar_format(accuracy = 1, prefix = "", suffix = " K"))

Organisations, Transports par eau, Activités indifférenciées des ménages

Code 
T102B %>%
  filter(a88 %in% c("99", "50", "98")) %>%
  ggplot() + theme_minimal() + ylab("Emploi salarié (en milliers)") + xlab("") +
  geom_line(aes(x = date, y = value, color = A88, linetype = A88)) +
  scale_color_manual(values = viridis(4)[1:3]) +
  scale_x_date(breaks = seq(1920, 2025, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%y")) +
  theme(legend.position = c(0.6, 0.7),
        legend.title = element_blank()) +
  scale_y_log10(breaks = seq(5, 3000, 1),
                labels = dollar_format(accuracy = 1, prefix = "", suffix = " K"))

Construction

2018

Code 
T102B %>%
  mutate(a88 = as.numeric(a88)) %>%
  filter(a88 >= 41, a88 <= 43) %>%
  group_by(a88, A88) %>%
  summarise(Nobs = n(),
            value2018 = value[date == as.Date("2019-01-01")]) %>%
  arrange(-value2018) %>%
  {if (is_html_output()) print_table(.) else .}
a88 A88 Nobs value2018
43 Travaux de construction spécialisés 31 1095
42 Génie civil 31 175
41 Construction de bâtiments 31 152

Travaux de construction sépcialisés, Génie civil, Constructio de batiments

Code 
T102B %>%
  filter(a88 %in% c("41", "42", "43")) %>%
  ggplot() + theme_minimal() + ylab("Emploi salarié (en milliers)") + xlab("") +
  geom_line(aes(x = date, y = value, color = A88, linetype = A88)) +
  scale_color_manual(values = viridis(4)[1:3]) +
  scale_x_date(breaks = seq(1920, 2025, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%y")) +
  theme(legend.position = c(0.6, 0.6),
        legend.title = element_blank()) +
  scale_y_log10(breaks = seq(100, 3000, 100),
                labels = dollar_format(accuracy = 1, prefix = "", suffix = " K"))