Zone d’emploi, par secteur (NACE88) - Séquoia de l’Acoss et des Urssaf (2008-2019) - ZE_NACE88_2019

Data - INSEE

Author

François Geerolf

Zone d’emploi

  • Atlas des Zones d’Emploi 2010. pdf

Code 
ZE_NACE88_2019 %>%
  left_join(zone_emploi, by = "zone_emploi") %>%
  group_by(zone_emploi, Zone_emploi, region) %>%
  summarise(Nobs = n()) %>%
  print_table_conditional

nace88

Code 
ZE_NACE88_2019 %>%
  left_join(nace88, by = "nace88") %>%
  group_by(nace88, Nace88) %>%
  summarise(Nobs = n()) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}

variable

Code 
ZE_NACE88_2019 %>%
  group_by(variable) %>%
  summarise(Nobs = n()) %>%
  print_table_conditional
variable Nobs
eff 281892
nb_etab 281892

date

Code 
ZE_NACE88_2019 %>%
  group_by(date) %>%
  summarise(Nobs = n()) %>%
  print_table_conditional
date Nobs
2008-01-01 46982
2009-01-01 46982
2010-01-01 46982
2011-01-01 46982
2012-01-01 46982
2013-01-01 46982
2014-01-01 46982
2015-01-01 46982
2016-01-01 46982
2017-01-01 46982
2018-01-01 46982
2019-01-01 46982

Metallurgie - nace88 == 24

Code 
ZE_NACE88_2019 %>%
  filter(nace88 == 24,
         year(date) %in% c(2008, 2019)) %>%
  mutate(variable = paste0(variable, year(date))) %>%
  select(-date) %>%
  spread(variable, value) %>%
  left_join(zone_emploi, by = "zone_emploi") %>%
  select(-nace88) %>%
  arrange(-eff2019) %>%
  select(Zone_emploi, everything()) %>%
  mutate(growth = round(100*(eff2019/eff2008 - 1), 1)) %>%
  print_table_conditional

Saint-Claude

Code 
ZE_NACE88_2019 %>%
  filter(zone_emploi == "4307",
         variable == "eff",
         year(date) %in% c(2008, 2011, 2014, 2019)) %>%
  mutate(year = year(date)) %>%
  select(year, nace88, value) %>%
  spread(year, value) %>%
  left_join(nace88, by = "nace88") %>%
  arrange(-`2019`) %>%
  print_table_conditional