TCRED - Effectifs de la fonction publique hospitalière - TCRED-TRAVAIL-EMPLOI-EFF-FPH

Data - INSEE

Info

LAST_UPDATE

Code
`TCRED-TRAVAIL-EMPLOI-EFF-FPH` %>%
  group_by(LAST_UPDATE) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  print_table_conditional()
LAST_UPDATE Nobs
2025-08-29 4563

LAST_DOWNLOAD

LAST_DOWNLOAD
2025-10-11

LAST_COMPILE

LAST_COMPILE
2025-10-11

Champ

TITLE_FR

Code
`TCRED-TRAVAIL-EMPLOI-EFF-FPH` %>%
  group_by(IDBANK, TITLE_FR) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  print_table_conditional()

TYPE-ETAB

Code
`TCRED-TRAVAIL-EMPLOI-EFF-FPH` %>%
  left_join(`TYPE-ETAB`, by = "TYPE-ETAB") %>%
  group_by(`TYPE-ETAB`, `Type-Etab`) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  print_table_conditional()
TYPE-ETAB Type-Etab Nobs
EFPH Ensemble de la fonction publique hospitalière 1521
ETSMS Établissements médico-sociaux 1521
HOP Hôpitaux 1521

REF_AREA

Code
`TCRED-TRAVAIL-EMPLOI-EFF-FPH` %>%
  group_by(REF_AREA) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  print_table_conditional()

SEXE

Code
`TCRED-TRAVAIL-EMPLOI-EFF-FPH` %>%
  left_join(SEXE, by = "SEXE") %>%
  group_by(SEXE, Sexe) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  print_table_conditional()
SEXE Sexe Nobs
0 Ensemble 3042
2 Femmes 1521

TIME_PERIOD / date

Code
`TCRED-TRAVAIL-EMPLOI-EFF-FPH` %>%
  group_by(TIME_PERIOD) %>%
  summarise(Nobs = n()) %>%
  arrange(desc(TIME_PERIOD)) %>%
  print_table_conditional()
TIME_PERIOD Nobs
2023 351
2022 351
2021 351
2020 351
2019 351
2018 351
2017 351
2016 351
2015 351
2014 351
2013 351
2012 351
2011 351

Sectoriel par département (2011)

Paris, Seine-Saint-Denis, Hauts-de-Seine

Code
`TCRED-TRAVAIL-EMPLOI-EFF-FPH` %>%
  filter(`TYPE-ETAB` == "EFPH",
         REF_AREA %in% c("D92", "D93", "D94")) %>%
  year_to_date %>%
  ggplot + geom_line(aes(x = date, y = OBS_VALUE, color = REF_AREA, linetype = REF_AREA)) +
  xlab("") + ylab("") +  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())