Indice de traitement brut dans la fonction publique de l’État

Data - INSEE

Auteur

François Geerolf

Info

source dataset Title .html .rData
insee INDICE-TRAITEMENT-FP Indice de traitement brut dans la fonction publique de l'État 2025-12-25 2025-12-27
insee IPCH-2015 Indices des prix à la consommation harmonisés 2025-12-25 2025-12-27
insee IPC-2015 Indice des prix à la consommation - Base 2015 2025-12-25 2025-12-27

Données sur les salaires

source dataset Title .html .rData
insee INDICE-TRAITEMENT-FP Indice de traitement brut dans la fonction publique de l'État 2025-12-25 2025-12-27
dares les-indices-de-salaire-de-base Les indices de salaire de base 2025-12-15 2025-12-15
insee CNA-2014-RDB Revenu et pouvoir d’achat des ménages 2025-12-25 2025-12-27
insee CNT-2014-CSI Comptes de secteurs institutionnels 2025-12-25 2025-12-27
insee ECRT2023 Emploi, chômage, revenus du travail - Edition 2023 2025-12-25 2023-06-30
insee SALAIRES-ACEMO Indices trimestriels de salaires dans le secteur privé - Résultats par secteur d’activité 2025-12-25 2025-12-27
insee SALAIRES-ACEMO-2017 Indices trimestriels de salaires dans le secteur privé 2025-12-25 2025-12-27
insee SALAIRES-ANNUELS Salaires annuels 2025-12-25 2025-12-27
insee if230 Séries longues sur les salaires dans le secteur privé 2025-12-25 2021-12-04
insee ir_salaires_SL_23_csv NA NA NA
insee ir_salaires_SL_csv NA NA NA
insee t_7401 NA NA NA
insee t_salaire_val Salaire moyen par tête - SMPT (données CVS) 2025-12-25 2025-12-27

LAST_COMPILE

LAST_COMPILE
2025-12-27

Last

Code 
`INDICE-TRAITEMENT-FP` %>%
  group_by(TIME_PERIOD) %>%
  summarise(Nobs = n()) %>%
  arrange(desc(TIME_PERIOD)) %>%
  head(2) %>%
  print_table_conditional()
TIME_PERIOD Nobs
2025-Q3 8
2025-Q2 8

TITLE_FR

Code 
`INDICE-TRAITEMENT-FP` %>%
  group_by(IDBANK, TITLE_FR) %>%
  summarise(Nobs = n(),
            date1 = first(TIME_PERIOD),
            date2 = last(TIME_PERIOD)) %>%
  arrange(-Nobs) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}

INDICATEUR

Code 
`INDICE-TRAITEMENT-FP` %>%
  left_join(INDICATEUR, by = "INDICATEUR") %>%
  group_by(INDICATEUR, Indicateur) %>%
  summarise(Nobs = n()) %>%
  print_table_conditional()
INDICATEUR Indicateur Nobs
NSALBF Indice de traitement brut 400
NSALNF Indice de traitement net 400

CATEGORIE_FP

Code 
`INDICE-TRAITEMENT-FP` %>%
  left_join(CATEGORIE_FP, by = "CATEGORIE_FP") %>%
  group_by(CATEGORIE_FP, Categorie_fp) %>%
  summarise(Nobs = n()) %>%
  print_table_conditional()
CATEGORIE_FP Categorie_fp Nobs
A Catégorie A 200
B Catégorie B 200
C Catégorie C 200
T Toutes catégories 200

TIME_PERIOD

Code 
`INDICE-TRAITEMENT-FP` %>%
  group_by(TIME_PERIOD) %>%
  summarise(Nobs = n()) %>%
  arrange(desc(TIME_PERIOD)) %>%
  print_table_conditional()

Par type

Net et Brut

Code 
`INDICE-TRAITEMENT-FP` %>%
  #filter(CATEGORIE_FP == "A") %>%
  left_join(INDICATEUR, by = "INDICATEUR") %>%
  left_join(CATEGORIE_FP, by = "CATEGORIE_FP") %>%
  quarter_to_date %>%
  ggplot() + geom_line(aes(x = date, y = OBS_VALUE,  linetype = Indicateur, color = Categorie_fp)) +
  theme_minimal() + ylab("Indice") + xlab("") +
  scale_x_date(breaks = seq(1920, 2100, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = c(0.3, 0.7),
        legend.title = element_blank()) +
  scale_y_log10(breaks = seq(0, 200, 2))

Net

Code 
`INDICE-TRAITEMENT-FP` %>%
  filter(INDICATEUR == "NSALNF") %>%
  left_join(INDICATEUR, by = "INDICATEUR") %>%
  left_join(CATEGORIE_FP, by = "CATEGORIE_FP") %>%
  quarter_to_date %>%
  arrange(date) %>%
  ggplot() + geom_line(aes(x = date, y = OBS_VALUE,  color = Categorie_fp)) +
  theme_minimal() + ylab("Indice Net") + xlab("") +
  scale_x_date(breaks = seq(1920, 2100, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = c(0.3, 0.7),
        legend.title = element_blank()) +
  scale_y_log10(breaks = seq(0, 200, 1))

Brut

Code 
`INDICE-TRAITEMENT-FP` %>%
  filter(INDICATEUR == "NSALBF") %>%
  left_join(INDICATEUR, by = "INDICATEUR") %>%
  left_join(CATEGORIE_FP, by = "CATEGORIE_FP") %>%
  quarter_to_date %>%
  ggplot() + geom_line(aes(x = date, y = OBS_VALUE,  color = Categorie_fp)) +
  theme_minimal() + ylab("Indice Brut") + xlab("") +
  scale_x_date(breaks = seq(1920, 2100, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = c(0.3, 0.7),
        legend.title = element_blank()) +
  scale_y_log10(breaks = seq(0, 200, 2))

Indice de traitement brut dans la fonction publique de l’État

Tous

Nominal

Code 
`INDICE-TRAITEMENT-FP` %>%
  filter(CATEGORIE_FP == "T") %>%
  left_join(INDICATEUR, by = "INDICATEUR") %>%
  quarter_to_date %>%
  ggplot() + geom_line(aes(x = date, y = OBS_VALUE,  color = Indicateur)) +
  theme_minimal() + ylab("Indice, Tous") + xlab("") +
  scale_x_date(breaks = seq(1920, 2100, 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(0, 200, 1))

Indice Net

Code 
`INDICE-TRAITEMENT-FP` %>%
  filter(CATEGORIE_FP == "T",
         INDICATEUR == "NSALNF") %>%
  left_join(INDICATEUR, by = "INDICATEUR") %>%
  quarter_to_date %>%
  left_join(inflation, by = "date") %>%
  arrange(date) %>%
  transmute(date, `Indice de traitement net, nominal` = OBS_VALUE,
            `Indice de traitement net, réel` = IPCH[1]*OBS_VALUE/IPCH) %>%
  gather(variable, value, -date) %>%
  ggplot() + geom_line(aes(x = date, y = value,  color = variable)) +
  theme_minimal() + ylab("Indice, Tous") + xlab("") +
  scale_x_date(breaks = seq(1920, 2100, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = c(0.2, 0.2),
        legend.title = element_blank()) +
  scale_y_log10(breaks = seq(0, 200, 5))

Indice Brut

Code 
`INDICE-TRAITEMENT-FP` %>%
  filter(CATEGORIE_FP == "T",
         INDICATEUR == "NSALBF") %>%
  left_join(INDICATEUR, by = "INDICATEUR") %>%
  quarter_to_date %>%
  left_join(inflation, by = "date") %>%
  arrange(date) %>%
  transmute(date, `Indice de traitement brut, nominal` = OBS_VALUE,
            `Indice de traitement brut, réel` = IPCH[1]*OBS_VALUE/IPCH) %>%
  gather(variable, value, -date) %>%
  ggplot() + geom_line(aes(x = date, y = value,  color = variable)) +
  theme_minimal() + ylab("Indice, Tous") + xlab("") +
  scale_x_date(breaks = seq(1920, 2100, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = c(0.2, 0.2),
        legend.title = element_blank()) +
  scale_y_log10(breaks = seq(0, 200, 5))

Indice Net/brut

Code 
`INDICE-TRAITEMENT-FP` %>%
  filter(CATEGORIE_FP == "A") %>%
  left_join(INDICATEUR, by = "INDICATEUR") %>%
  quarter_to_date %>%
  left_join(inflation, by = "date") %>%
  arrange(date) %>%
  transmute(date, Indicateur, `Nominal` = OBS_VALUE,
            `Réel` = IPCH[1]*OBS_VALUE/IPCH) %>%
  gather(variable, value, -date, -Indicateur) %>%
  ggplot() + geom_line(aes(x = date, y = value,  color = variable, linetype = Indicateur)) +
  theme_minimal() + ylab("Indice, Tous") + xlab("") +
  scale_x_date(breaks = seq(1920, 2100, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = c(0.2, 0.2),
        legend.title = element_blank()) +
  scale_y_log10(breaks = seq(0, 200, 5))

Indice Net/brut, réel IPC IPCH

Code 
`INDICE-TRAITEMENT-FP` %>%
  filter(CATEGORIE_FP == "T") %>%
  left_join(INDICATEUR, by = "INDICATEUR") %>%
  quarter_to_date %>%
  left_join(inflation, by = "date") %>%
  arrange(date) %>%
  transmute(date, Indicateur,
            `Nominal` = OBS_VALUE,
            `Réel (inflation IPCH)` = IPCH[1]*OBS_VALUE/IPCH,
            `Réel (inflation IPC)` = IPC[1]*OBS_VALUE/IPC) %>%
  gather(variable, value, -date, -Indicateur) %>%
  ggplot() + geom_line(aes(x = date, y = value,  color = variable, linetype = Indicateur)) +
  theme_minimal() + ylab("Indice de traitement dans la fonction publique de l'État") + xlab("") +
  scale_color_manual(values = c("darkgrey", "#F8766D", "#619CFF")) +
  scale_x_date(breaks = seq(1920, 2100, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = c(0.18, 0.24),
        legend.title = element_blank()) +
  scale_y_log10(breaks = seq(0, 200, 2))

Ratio Net/brut

Annuel

Code 
net_brut_annuel <- `INDICE-TRAITEMENT-FP` %>%
  filter(CATEGORIE_FP == "T") %>%
  left_join(INDICATEUR, by = "INDICATEUR") %>%
  quarter_to_date %>%
  arrange(date) %>%
  select(date, OBS_VALUE, Indicateur) %>%
  spread(Indicateur, OBS_VALUE) %>%
  transmute(date, net_brut = `Indice de traitement net`/`Indice de traitement brut`) %>%
  filter(month(date) == 1) %>%
  slice(1, 1:n(), n()) %>%
  mutate(date = case_when(row_number() == n() ~ Sys.Date(),
                              row_number() == 1 ~ as.Date("1960-01-01"),
                              TRUE ~ date)) %>%
  complete(date = seq.Date(min(date), max(date), by = "year")) %>%
  fill(net_brut)

save(net_brut_annuel, file = "INDICE-TRAITEMENT-FP-net-brut-annuel.RData")

net_brut_annuel %>%
  ggplot() + geom_line(aes(x = date, y = net_brut-1)) +
  theme_minimal() + ylab("Ratio net/brut") + xlab("") +
  scale_color_manual(values = c("#F8766D", "#619CFF")) +
  scale_x_date(breaks = seq(1920, 2100, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = c(0.18, 0.24),
        legend.title = element_blank()) +
  scale_y_continuous(breaks = seq(-1,1, 0.01),
                     labels = percent_format(a = 1))

Trimestriel

Code 
net_brut_trimestriel <- `INDICE-TRAITEMENT-FP` %>%
  filter(CATEGORIE_FP == "T") %>%
  left_join(INDICATEUR, by = "INDICATEUR") %>%
  quarter_to_date %>%
  arrange(date) %>%
  select(date, OBS_VALUE, Indicateur) %>%
  spread(Indicateur, OBS_VALUE) %>%
  transmute(date, net_brut = `Indice de traitement net`/`Indice de traitement brut`) %>%
  slice(1, 1:n(), n()) %>%
  mutate(date = case_when(row_number() == n() ~ Sys.Date(),
                              row_number() == 1 ~ as.Date("1960-01-01"),
                              TRUE ~ date)) %>%
  complete(date = seq.Date(min(date), max(date), by = "quarter")) %>%
  fill(net_brut)

save(net_brut_trimestriel, file = "INDICE-TRAITEMENT-FP-net-brut-trimestriel.RData")

net_brut_trimestriel %>%
  ggplot() + geom_line(aes(x = date, y = net_brut-1)) +
  theme_minimal() + ylab("Ratio net/brut") + xlab("") +
  scale_color_manual(values = c("#F8766D", "#619CFF")) +
  scale_x_date(breaks = seq(1920, 2100, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = c(0.18, 0.24),
        legend.title = element_blank()) +
  scale_y_continuous(breaks = seq(-1,1, 0.01),
                     labels = percent_format(a = 1))

Mensuel

Code 
net_brut_mensuel <- `INDICE-TRAITEMENT-FP` %>%
  filter(CATEGORIE_FP == "T") %>%
  left_join(INDICATEUR, by = "INDICATEUR") %>%
  quarter_to_date %>%
  arrange(date) %>%
  select(date, OBS_VALUE, Indicateur) %>%
  spread(Indicateur, OBS_VALUE) %>%
  transmute(date, net_brut = `Indice de traitement net`/`Indice de traitement brut`) %>%
  slice(1, 1:n(), n()) %>%
  mutate(date = case_when(row_number() == n() ~ Sys.Date(),
                              row_number() == 1 ~ as.Date("1960-01-01"),
                              TRUE ~ date)) %>%
  complete(date = seq.Date(min(date), max(date), by = "month")) %>%
  fill(net_brut)

save(net_brut_mensuel, file = "INDICE-TRAITEMENT-FP-net-brut-mensuel.RData")

net_brut_mensuel %>%
  ggplot() + geom_line(aes(x = date, y = net_brut-1)) +
  theme_minimal() + ylab("Ratio net/brut") + xlab("") +
  scale_color_manual(values = c("#F8766D", "#619CFF")) +
  scale_x_date(breaks = seq(1920, 2100, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = c(0.18, 0.24),
        legend.title = element_blank()) +
  scale_y_continuous(breaks = seq(-1,1, 0.01),
                     labels = percent_format(a = 1))

Indice Net/brut, réel IPC IPCH

Code 
`INDICE-TRAITEMENT-FP` %>%
  filter(CATEGORIE_FP == "T") %>%
  left_join(INDICATEUR, by = "INDICATEUR") %>%
  quarter_to_date %>%
  left_join(inflation, by = "date") %>%
  arrange(date) %>%
  transmute(date, Indicateur,
            `Réel (inflation IPCH)` = IPCH[1]*OBS_VALUE/IPCH,
            `Réel (inflation IPC)` = IPC[1]*OBS_VALUE/IPC) %>%
  gather(variable, value, -date, -Indicateur) %>%
  ggplot() + geom_line(aes(x = date, y = value,  color = variable, linetype = Indicateur)) +
  theme_minimal() + ylab("Indice de traitement dans la FP de l'État") + xlab("") +
  scale_color_manual(values = c("#F8766D", "#619CFF")) +
  scale_x_date(breaks = seq(1921, 2100, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = c(0.18, 0.24),
        legend.title = element_blank()) +
  scale_y_log10(breaks = seq(0, 200, 2))

Catégorie A

Nominal

Code 
`INDICE-TRAITEMENT-FP` %>%
  filter(CATEGORIE_FP == "A") %>%
  left_join(INDICATEUR, by = "INDICATEUR") %>%
  quarter_to_date %>%
  ggplot() + geom_line(aes(x = date, y = OBS_VALUE,  color = Indicateur)) +
  theme_minimal() + ylab("Indice, Catégorie A") + xlab("") +
  scale_x_date(breaks = seq(1920, 2100, 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(0, 200, 1))

Indice Net

Code 
`INDICE-TRAITEMENT-FP` %>%
  filter(CATEGORIE_FP == "A",
         INDICATEUR == "NSALNF") %>%
  left_join(INDICATEUR, by = "INDICATEUR") %>%
  quarter_to_date %>%
  left_join(inflation, by = "date") %>%
  arrange(date) %>%
  transmute(date, `Indice de traitement net, nominal` = OBS_VALUE,
            `Indice de traitement net, réel` = IPCH[1]*OBS_VALUE/IPCH) %>%
  gather(variable, value, -date) %>%
  ggplot() + geom_line(aes(x = date, y = value,  color = variable)) +
  theme_minimal() + ylab("Indice, Catégorie A") + xlab("") +
  scale_x_date(breaks = seq(1920, 2100, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = c(0.2, 0.2),
        legend.title = element_blank()) +
  scale_y_log10(breaks = seq(0, 200, 5))

Indice Brut

Code 
`INDICE-TRAITEMENT-FP` %>%
  filter(CATEGORIE_FP == "A",
         INDICATEUR == "NSALBF") %>%
  left_join(INDICATEUR, by = "INDICATEUR") %>%
  quarter_to_date %>%
  left_join(inflation, by = "date") %>%
  arrange(date) %>%
  transmute(date, `Indice de traitement brut, nominal` = OBS_VALUE,
            `Indice de traitement brut, réel` = IPCH[1]*OBS_VALUE/IPCH) %>%
  gather(variable, value, -date) %>%
  ggplot() + geom_line(aes(x = date, y = value,  color = variable)) +
  theme_minimal() + ylab("Indice, Catégorie A") + xlab("") +
  scale_x_date(breaks = seq(1920, 2100, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = c(0.2, 0.2),
        legend.title = element_blank()) +
  scale_y_log10(breaks = seq(0, 200, 5))

Indice Net/brut

Code 
`INDICE-TRAITEMENT-FP` %>%
  filter(CATEGORIE_FP == "A") %>%
  left_join(INDICATEUR, by = "INDICATEUR") %>%
  quarter_to_date %>%
  left_join(inflation, by = "date") %>%
  arrange(date) %>%
  transmute(date, Indicateur, `Nominal` = OBS_VALUE,
            `Réel` = IPCH[1]*OBS_VALUE/IPCH) %>%
  gather(variable, value, -date, -Indicateur) %>%
  ggplot() + geom_line(aes(x = date, y = value,  color = variable, linetype = Indicateur)) +
  theme_minimal() + ylab("Indice, Catégorie A") + xlab("") +
  scale_x_date(breaks = seq(1920, 2100, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = c(0.2, 0.2),
        legend.title = element_blank()) +
  scale_y_log10(breaks = seq(0, 200, 5))

Indice Net/brut, réel IPC IPCH

Code 
`INDICE-TRAITEMENT-FP` %>%
  filter(CATEGORIE_FP == "A") %>%
  left_join(INDICATEUR, by = "INDICATEUR") %>%
  quarter_to_date %>%
  left_join(inflation, by = "date") %>%
  arrange(date) %>%
  transmute(date, Indicateur,
            `Nominal` = OBS_VALUE,
            `Réel (inflation IPCH)` = IPCH[1]*OBS_VALUE/IPCH,
            `Réel (inflation IPC)` = IPC[1]*OBS_VALUE/IPC) %>%
  gather(variable, value, -date, -Indicateur) %>%
  ggplot() + geom_line(aes(x = date, y = value,  color = variable, linetype = Indicateur)) +
  theme_minimal() + ylab("Indice de traitement dans la fonction publique de l'État, Cat. A") + xlab("") +
  scale_color_manual(values = c("darkgrey", "#F8766D", "#619CFF")) +
  scale_x_date(breaks = seq(1920, 2100, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = c(0.18, 0.24),
        legend.title = element_blank()) +
  scale_y_log10(breaks = seq(0, 200, 2))

Catégorie B

Nominal

Code 
`INDICE-TRAITEMENT-FP` %>%
  filter(CATEGORIE_FP == "B") %>%
  left_join(INDICATEUR, by = "INDICATEUR") %>%
  quarter_to_date %>%
  ggplot() + geom_line(aes(x = date, y = OBS_VALUE,  color = Indicateur)) +
  theme_minimal() + ylab("Indice, Catégorie B") + xlab("") +
  scale_x_date(breaks = seq(1920, 2100, 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(0, 200, 1))

Indice Net

Code 
`INDICE-TRAITEMENT-FP` %>%
  filter(CATEGORIE_FP == "B",
         INDICATEUR == "NSALNF") %>%
  left_join(INDICATEUR, by = "INDICATEUR") %>%
  quarter_to_date %>%
  left_join(inflation, by = "date") %>%
  arrange(date) %>%
  transmute(date, `Indice de traitement net, nominal` = OBS_VALUE,
            `Indice de traitement net, réel` = IPCH[1]*OBS_VALUE/IPCH) %>%
  gather(variable, value, -date) %>%
  ggplot() + geom_line(aes(x = date, y = value,  color = variable)) +
  theme_minimal() + ylab("Indice, Catégorie B") + xlab("") +
  scale_x_date(breaks = seq(1920, 2100, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = c(0.2, 0.2),
        legend.title = element_blank()) +
  scale_y_log10(breaks = seq(0, 200, 5))

Indice Brut

Code 
`INDICE-TRAITEMENT-FP` %>%
  filter(CATEGORIE_FP == "B",
         INDICATEUR == "NSALBF") %>%
  left_join(INDICATEUR, by = "INDICATEUR") %>%
  quarter_to_date %>%
  left_join(inflation, by = "date") %>%
  arrange(date) %>%
  transmute(date, `Indice de traitement brut, nominal` = OBS_VALUE,
            `Indice de traitement brut, réel` = IPCH[1]*OBS_VALUE/IPCH) %>%
  gather(variable, value, -date) %>%
  ggplot() + geom_line(aes(x = date, y = value,  color = variable)) +
  theme_minimal() + ylab("Indice, Catégorie B") + xlab("") +
  scale_x_date(breaks = seq(1920, 2100, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = c(0.2, 0.2),
        legend.title = element_blank()) +
  scale_y_log10(breaks = seq(0, 200, 5))

Indice Net/brut

Code 
`INDICE-TRAITEMENT-FP` %>%
  filter(CATEGORIE_FP == "B") %>%
  left_join(INDICATEUR, by = "INDICATEUR") %>%
  quarter_to_date %>%
  left_join(inflation, by = "date") %>%
  arrange(date) %>%
  transmute(date, Indicateur, `Nominal` = OBS_VALUE,
            `Réel` = IPCH[1]*OBS_VALUE/IPCH) %>%
  gather(variable, value, -date, -Indicateur) %>%
  ggplot() + geom_line(aes(x = date, y = value,  color = variable, linetype = Indicateur)) +
  theme_minimal() + ylab("Indice, Catégorie B") + xlab("") +
  scale_x_date(breaks = seq(1920, 2100, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = c(0.2, 0.2),
        legend.title = element_blank()) +
  scale_y_log10(breaks = seq(0, 200, 5))

Indice Net/brut, réel IPC IPCH

Code 
`INDICE-TRAITEMENT-FP` %>%
  filter(CATEGORIE_FP == "B") %>%
  left_join(INDICATEUR, by = "INDICATEUR") %>%
  quarter_to_date %>%
  left_join(inflation, by = "date") %>%
  arrange(date) %>%
  transmute(date, Indicateur,
            `Nominal` = OBS_VALUE,
            `Réel (inflation IPCH)` = IPCH[1]*OBS_VALUE/IPCH,
            `Réel (inflation IPC)` = IPC[1]*OBS_VALUE/IPC) %>%
  gather(variable, value, -date, -Indicateur) %>%
  ggplot() + geom_line(aes(x = date, y = value,  color = variable, linetype = Indicateur)) +
  theme_minimal() + ylab("Indice de traitement dans la fonction publique de l'État, Cat. B") + xlab("") +
  scale_color_manual(values = c("darkgrey", "#F8766D", "#619CFF")) +
  scale_x_date(breaks = seq(1920, 2100, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = c(0.18, 0.24),
        legend.title = element_blank()) +
  scale_y_log10(breaks = seq(0, 200, 2))

Catégorie C

Nominal

Code 
`INDICE-TRAITEMENT-FP` %>%
  filter(CATEGORIE_FP == "B") %>%
  left_join(INDICATEUR, by = "INDICATEUR") %>%
  quarter_to_date %>%
  ggplot() + geom_line(aes(x = date, y = OBS_VALUE,  color = Indicateur)) +
  theme_minimal() + ylab("Indice, Catégorie C") + xlab("") +
  scale_x_date(breaks = seq(1920, 2100, 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(0, 200, 1))

Indice Net

Code 
`INDICE-TRAITEMENT-FP` %>%
  filter(CATEGORIE_FP == "C",
         INDICATEUR == "NSALNF") %>%
  left_join(INDICATEUR, by = "INDICATEUR") %>%
  quarter_to_date %>%
  left_join(inflation, by = "date") %>%
  arrange(date) %>%
  transmute(date, `Indice de traitement net, nominal` = OBS_VALUE,
            `Indice de traitement net, réel` = IPCH[1]*OBS_VALUE/IPCH) %>%
  gather(variable, value, -date) %>%
  ggplot() + geom_line(aes(x = date, y = value,  color = variable)) +
  theme_minimal() + ylab("Indice, Catégorie C") + xlab("") +
  scale_x_date(breaks = seq(1920, 2100, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = c(0.2, 0.2),
        legend.title = element_blank()) +
  scale_y_log10(breaks = seq(0, 200, 5))

Indice Brut

Code 
`INDICE-TRAITEMENT-FP` %>%
  filter(CATEGORIE_FP == "C",
         INDICATEUR == "NSALBF") %>%
  left_join(INDICATEUR, by = "INDICATEUR") %>%
  quarter_to_date %>%
  left_join(inflation, by = "date") %>%
  arrange(date) %>%
  transmute(date, `Indice de traitement brut, nominal` = OBS_VALUE,
            `Indice de traitement brut, réel` = IPCH[1]*OBS_VALUE/IPCH) %>%
  gather(variable, value, -date) %>%
  ggplot() + geom_line(aes(x = date, y = value,  color = variable)) +
  theme_minimal() + ylab("Indice, Catégorie C") + xlab("") +
  scale_x_date(breaks = seq(1920, 2100, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = c(0.2, 0.2),
        legend.title = element_blank()) +
  scale_y_log10(breaks = seq(0, 200, 5))

Indice Net/brut, réel IPC IPCH

Code 
`INDICE-TRAITEMENT-FP` %>%
  filter(CATEGORIE_FP == "C") %>%
  left_join(INDICATEUR, by = "INDICATEUR") %>%
  quarter_to_date %>%
  left_join(inflation, by = "date") %>%
  arrange(date) %>%
  transmute(date, Indicateur,
            `Nominal` = OBS_VALUE,
            `Réel (inflation IPCH)` = IPCH[1]*OBS_VALUE/IPCH,
            `Réel (inflation IPC)` = IPC[1]*OBS_VALUE/IPC) %>%
  gather(variable, value, -date, -Indicateur) %>%
  ggplot() + geom_line(aes(x = date, y = value,  color = variable, linetype = Indicateur)) +
  theme_minimal() + ylab("Indice de traitement dans la fonction publique de l'État, Cat. C") + xlab("") +
  scale_color_manual(values = c("darkgrey", "#F8766D", "#619CFF")) +
  scale_x_date(breaks = seq(1920, 2100, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = c(0.18, 0.24),
        legend.title = element_blank()) +
  scale_y_log10(breaks = seq(0, 200, 2))

Indice Net/brut

Code 
`INDICE-TRAITEMENT-FP` %>%
  filter(CATEGORIE_FP == "C") %>%
  left_join(INDICATEUR, by = "INDICATEUR") %>%
  quarter_to_date %>%
  left_join(inflation, by = "date") %>%
  arrange(date) %>%
  transmute(date, Indicateur, `Nominal` = OBS_VALUE,
            `Réel` = IPCH[1]*OBS_VALUE/IPCH) %>%
  gather(variable, value, -date, -Indicateur) %>%
  ggplot() + geom_line(aes(x = date, y = value,  color = variable, linetype = Indicateur)) +
  theme_minimal() + ylab("Indice, Catégorie C") + xlab("") +
  scale_x_date(breaks = seq(1920, 2100, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = c(0.2, 0.2),
        legend.title = element_blank()) +
  scale_y_log10(breaks = seq(0, 200, 5))