Emploi salarié en fin d’année par département et région de France (hors Mayotte), selon le secteur d’activité (A38) et le sexe (1990-2019) - T202

Data - INSEE

Auteur

François Geerolf 

Warning: le package 'rgdal' n'est pas disponible for this version of R

Une version de ce package pour votre version de R est peut-être disponible ailleurs,
Voyez des idées à
https://cran.r-project.org/doc/manuals/r-patched/R-admin.html#Installing-packages
Warning in library(package, lib.loc = lib.loc, character.only = TRUE,
logical.return = TRUE, : aucun package nommé 'rgdal' n'est trouvé

Geo

Code 
`insee-T202` %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}

sex

Code 
T202 %>%
  group_by(sex) %>%
  summarise(Nobs = n()) %>%
  {if (is_html_output()) print_table(.) else .}
sex Nobs
E 167040
F 158400
H 158400

sector

Code 
T202 %>%
  left_join(sector, by = "sector") %>%
  group_by(sector, Sector) %>%
  summarise(Nobs = n()) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}

date

Code 
T202 %>%
  group_by(date) %>%
  summarise(Nobs = n()) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}

Saint-Claude - Departement = 39

Industrie

Code 
T202 %>%
  filter(geo == "D39",
         sex == "E", 
         sector %in% c("T", "TBE", "TBEC1", "TBEC2", "TBEC3", "TBEC4", "TBEC5")) %>%
  group_by(date) %>%
  mutate(value = value / value[sector == "T"]) %>%
  filter(sector != "T") %>%
  left_join(sector, by = "sector") %>%
  ggplot + geom_line(aes(x = date, y = value, color = Sector)) +
  xlab("") + ylab("Part emploi") +  theme_minimal() +
  scale_x_date(breaks = seq(1960, 2020, 1) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%y")) +
  scale_y_continuous(breaks = 0.01*seq(0, 120, 1),
                labels = percent_format(accuracy = 1)) +
  scale_color_manual(values = viridis(7)[1:6]) +
  theme(legend.position = c(0.5, 0.4),
        legend.title = element_blank())

Industrie

Code 
T202 %>%
  filter(geo == "D39",
         sex == "E", 
         sector %in% c("T", "TBE", "TBEC5")) %>%
  group_by(date) %>%
  mutate(value = value / value[sector == "T"]) %>%
  filter(sector != "T") %>%
  left_join(sector, by = "sector") %>%
  ggplot + geom_line(aes(x = date, y = value, color = Sector)) +
  xlab("") + ylab("Part emploi") +  theme_minimal() +
  scale_x_date(breaks = seq(1960, 2020, 1) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%y")) +
  scale_y_continuous(breaks = 0.01*seq(0, 120, 1),
                labels = percent_format(accuracy = 1)) +
  scale_color_manual(values = viridis(3)[1:2]) +
  theme(legend.position = c(0.75, 0.9),
        legend.title = element_blank())

Industrie

Code 
T202 %>%
  filter(geo == "D39",
         sex == "E", 
         sector %in% c("T", "TBEC1", "TBEC2", "TBEC3", "TBEC4")) %>%
  group_by(date) %>%
  mutate(value = value / value[sector == "T"]) %>%
  filter(sector != "T") %>%
  left_join(sector, by = "sector") %>%
  ggplot + geom_line(aes(x = date, y = value, color = Sector)) +
  xlab("") + ylab("Part emploi") +  theme_minimal() +
  scale_x_date(breaks = seq(1960, 2020, 1) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%y")) +
  scale_y_continuous(breaks = 0.01*seq(0, 120, 1),
                labels = percent_format(accuracy = 1)) +
  scale_color_manual(values = viridis(5)[1:4]) +
  theme(legend.position = c(0.5, 0.4),
        legend.title = element_blank())

Industrie (BE) Par Département

Hauts de Seine, Seine-Saint-Denis, Paris

Code 
T202 %>%
  filter(sex == "E",
         sector %in% c("TBE", "T"),
         geo == c("D92", "D93", "D75")) %>%
  mutate(CODE_DEPT = gsub("D", "", geo)) %>%
  select(CODE_DEPT, sector, date, value) %>%
  spread(sector, value) %>%
  ggplot + geom_line(aes(x = date, y = TBE / T, color = CODE_DEPT, linetype = CODE_DEPT)) +
  xlab("") + ylab("Part emploi industriel (% BE-FZ-GU)") +  theme_minimal() +
  scale_x_date(breaks = seq(1960, 2020, 1) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%y")) +
  scale_y_continuous(breaks = 0.01*seq(0, 120, 1),
                labels = percent_format(accuracy = 1)) +
  scale_color_manual(values = viridis(5)[1:4]) +
  theme(legend.position = c(0.8, 0.9),
        legend.title = element_blank())

Ain, Allier

Code 
T202 %>%
  filter(sex == "E",
         sector %in% c("TBE", "T"),
         geo == c("D01", "D02", "D03")) %>%
  mutate(CODE_DEPT = gsub("D", "", geo)) %>%
  select(CODE_DEPT, sector, date, value) %>%
  spread(sector, value) %>%
  ggplot + geom_line(aes(x = date, y = TBE / T, color = CODE_DEPT, linetype = CODE_DEPT)) +
  xlab("") + ylab("Part emploi industriel (% BE-FZ-GU)") +  theme_minimal() +
  scale_x_date(breaks = seq(1960, 2020, 1) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%y")) +
  scale_y_continuous(breaks = 0.01*seq(0, 120, 1),
                labels = percent_format(accuracy = 1)) +
  scale_color_manual(values = viridis(5)[1:4]) +
  theme(legend.position = c(0.8, 0.9),
        legend.title = element_blank())

2019

Agriculture (AZ)

Code 
T202 %>%
  filter(sex == "E",
         sector %in% c("TAZ", "T"),
         grepl("D", geo),
         date == as.Date("2018-12-31")) %>%
  mutate(CODE_DEPT = gsub("D", "", geo)) %>%
  select(CODE_DEPT, sector, date, value) %>%
  spread(sector, value) %>%
  mutate(value = TAZ / T) %>%
  left_join(departements_details, by = "CODE_DEPT") %>%
  left_join(departements, by = "CODE_DEPT") %>%
  ggplot(.) + aes(long, lat, group = group, fill = value) + 
  coord_equal() + theme_void() + geom_polygon() +
  scale_fill_viridis_c(na.value = "white",
                       direction = -1,
                       name = "Agriculture (AZ)",
                       breaks = 0.01*seq(0, 90, 1),
                       labels = percent_format(accuracy = 1)) +
  labs(x = "", y = "", title = "") +
  theme(axis.text.x = element_blank(),
        axis.text.y = element_blank())

Industrie (BE)

Code 
T202 %>%
  filter(sex == "E",
         sector %in% c("TBE", "T"),
         grepl("D", geo),
         date == as.Date("2018-12-31")) %>%
  mutate(CODE_DEPT = gsub("D", "", geo)) %>%
  select(CODE_DEPT, sector, date, value) %>%
  spread(sector, value) %>%
  mutate(value = TBE / T) %>%
  left_join(departements_details, by = "CODE_DEPT") %>%
  left_join(departements, by = "CODE_DEPT") %>%
  ggplot(.) + aes(long, lat, group = group, fill = value) + 
  coord_equal() + theme_void() + geom_polygon() +
  scale_fill_viridis_c(na.value = "white",
                       direction = -1,
                       name = "Industrie (BE)",
                       breaks = 0.01*seq(0, 50, 4),
                       labels = percent_format(accuracy = 1)) +
  labs(x = "", y = "", title = "") +
  theme(axis.text.x = element_blank(),
        axis.text.y = element_blank())

Construction (FZ)

Code 
T202 %>%
  filter(sex == "E",
         sector %in% c("TFZ", "T"),
         grepl("D", geo),
         date == as.Date("2018-12-31")) %>%
  mutate(CODE_DEPT = gsub("D", "", geo)) %>%
  select(CODE_DEPT, sector, date, value) %>%
  spread(sector, value) %>%
  mutate(value = TFZ / T) %>%
  left_join(departements_details, by = "CODE_DEPT") %>%
  left_join(departements, by = "CODE_DEPT") %>%
  ggplot(.) + aes(long, lat, group = group, fill = value) + 
  coord_equal() + theme_void() + geom_polygon() +
  scale_fill_viridis_c(na.value = "white",
                       direction = -1,
                       name = "Construction (FZ)",
                       breaks = 0.01*seq(0, 90, 2),
                       labels = percent_format(accuracy = 1)) +
  labs(x = "", y = "", title = "") +
  theme(axis.text.x = element_blank(),
        axis.text.y = element_blank())

Tertiaire Marchand (GU)

Code 
T202 %>%
  filter(sex == "E",
         sector %in% c("TGU", "T"),
         grepl("D", geo),
         date == as.Date("2018-12-31")) %>%
  mutate(CODE_DEPT = gsub("D", "", geo)) %>%
  select(CODE_DEPT, sector, date, value) %>%
  spread(sector, value) %>%
  mutate(value = TGU / T) %>%
  left_join(departements_details, by = "CODE_DEPT") %>%
  left_join(departements, by = "CODE_DEPT") %>%
  ggplot(.) + aes(long, lat, group = group, fill = value) + 
  coord_equal() + theme_void() + geom_polygon() +
  scale_fill_viridis_c(na.value = "white",
                       direction = -1,
                       name = "Tert. Marchand (GU)",
                       breaks = 0.01*seq(0, 90, 10),
                       labels = percent_format(accuracy = 1)) +
  labs(x = "", y = "", title = "") +
  theme(axis.text.x = element_blank(),
        axis.text.y = element_blank())

Tertiaire Non Marchand (OQ)

Code 
knitr::opts_chunk$set(dev.args = list(bg = 'white'))
T202 %>%
  filter(sex == "E",
         sector %in% c("TOQ", "T"),
         grepl("D", geo),
         date == as.Date("2018-12-31")) %>%
  mutate(CODE_DEPT = gsub("D", "", geo)) %>%
  select(CODE_DEPT, sector, date, value) %>%
  spread(sector, value) %>%
  mutate(value = TOQ / T) %>%
  left_join(departements_details, by = "CODE_DEPT") %>%
  left_join(departements, by = "CODE_DEPT") %>%
  ggplot(.) + aes(long, lat, group = group, fill = value) + 
  coord_equal() + theme_void() + geom_polygon() +
  scale_fill_viridis_c(na.value = "white",
                       direction = -1,
                       name = "Tert. Non Marchand (OQ)",
                       breaks = 0.01*seq(0, 90, 10),
                       labels = percent_format(accuracy = 1)) +
  labs(x = "", y = "", title = "") +
  theme(axis.text.x = element_blank(),
        axis.text.y = element_blank())