Salaire moyen par tête - SMPT (données CVS)

Data - INSEE

Author

François Geerolf

Info

source dataset Title .html .rData
insee t_salaire_val Salaire moyen par tête - SMPT (données CVS) 2025-10-10 2025-08-29
insee IPC-2015 Indice des prix à la consommation - Base 2015 2025-10-10 2025-10-10
insee IPCH-2015 Indices des prix à la consommation harmonisés 2025-10-10 2025-10-09

Données sur les salaires

source dataset Title .html .rData
insee t_salaire_val Salaire moyen par tête - SMPT (données CVS) 2025-10-10 2025-08-29
dares les-indices-de-salaire-de-base Les indices de salaire de base 2025-10-04 2025-10-04
insee CNA-2014-RDB Revenu et pouvoir d’achat des ménages 2025-10-10 2025-10-09
insee CNT-2014-CSI Comptes de secteurs institutionnels 2025-10-10 2025-10-09
insee ECRT2023 Emploi, chômage, revenus du travail - Edition 2023 2025-10-10 2023-06-30
insee INDICE-TRAITEMENT-FP Indice de traitement brut dans la fonction publique de l'État 2025-10-10 2025-10-09
insee SALAIRES-ACEMO Indices trimestriels de salaires dans le secteur privé - Résultats par secteur d’activité 2025-10-10 2025-10-09
insee SALAIRES-ACEMO-2017 Indices trimestriels de salaires dans le secteur privé 2025-10-10 2025-10-09
insee SALAIRES-ANNUELS Salaires annuels 2025-10-10 2025-10-10
insee if230 Séries longues sur les salaires dans le secteur privé 2025-10-10 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

Structure

  • Comptes nationaux trimestriels au troisième trimestre 2023. html

  • Salaires. xls

  • Comptes de branches. html

  • PIB et ses composantes. html

  • Secteurs et ses composantes. html

Bibliographie

Français

  • “Mesurer”le” pouvoir d’achat”, F. Geerolf, Document de travail, Juillet 2024. [pdf]

  • “Inflation en France: IPC ou IPCH ?”, F. Geerolf, Document de travail, Juillet 2024. [pdf]

  • “La taxe inflationniste, le pouvoir d’achat, le taux d’épargne et le déficit public”, F. Geerolf, Document de travail, Juillet 2024. [pdf]

variable

Code 
t_salaire_val %>%
  group_by(variable) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  print_table_conditional
variable Nobs
(DE) à (C5) 306
(DE) à (MN), (RU) 306
(GZ) à (MN), (RU) 306
AZ 306
C 306
C1 306
C2 306
C3 306
C4 306
C5 306
DE 306
FZ 306
GZ 306
HZ 306
IZ 306
JZ 306
KZ 306
LZ 306
MN 306
OQ 306
RU 306
TOTAL 306

date

Code 
t_salaire_val %>%
  group_by(date) %>%
  summarise(Nobs = n()) %>%
  arrange(desc(date)) %>%
  print_table_conditional()

2021, Trimestre 3

Code 
t_salaire_val %>%
  filter(date %in% c(as.Date("2023-01-01"), as.Date("2011-07-01"))) %>%
  spread(date, value) %>%
  mutate(evolution = 100*((`2023-01-01`/`2011-07-01`)^(1/10)-1)) %>%
  arrange(-`2023-01-01`) %>%
  print_table_conditional()
variable 2011-07-01 2023-01-01 evolution
JZ 12600.62 16504.17 2.7354145
C2 13343.24 15034.28 1.2003778
C4 11463.32 15030.37 2.7462371
KZ 11148.96 14845.66 2.9050091
C3 10571.57 12629.61 1.7946715
DE 10228.78 12156.64 1.7416957
LZ 10001.07 11792.35 1.6612369
C5 9068.12 11264.20 2.1923319
(DE) à (C5) 9034.87 11101.61 2.0813502
MN 8808.78 11048.28 2.2911099
C 8917.24 10987.44 2.1096073
FZ 8486.31 10505.82 2.1576999
(DE) à (MN), (RU) 8410.79 10483.04 2.2268657
(GZ) à (MN), (RU) 8249.88 10351.70 2.2954706
TOTAL 7851.71 9813.32 2.2551455
HZ 8202.73 9445.25 1.4204432
GZ 7305.70 9092.03 2.2115331
OQ 6745.88 8473.93 2.3068295
C1 6522.17 8206.44 2.3237077
RU 6267.23 7699.99 2.0801860
IZ 5848.43 7154.65 2.0363488
AZ 6218.37 5965.74 -0.4138882

Valeurs en Euros

KZ, JZ, C4

All

Code 
t_salaire_val %>%
  filter(variable %in% c("KZ", "JZ", "C4")) %>%
  group_by(variable) %>%
  ggplot() + ylab("Salaire moyen par tête - SMPT") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = value, color = variable)) +
  scale_x_date(breaks = seq(1920, 2100, 5) %>% 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 = 1000*seq(1, 300, 1),
                     labels = dollar_format(accuracy = 1, su = "€", pre = "")) +
  geom_label_repel(data = . %>% filter(date == max(date)),
             aes(x = date, y = value, color = variable, label = round(value, 1)))

1990-

Code 
t_salaire_val %>%
  filter(variable %in% c("KZ", "JZ", "C4"),
         date >= as.Date("1990-01-01")) %>%
  group_by(variable) %>%
  ggplot() + ylab("Salaire moyen par tête - SMPT") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = value, color = variable)) +
  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 = 1000*seq(1, 300, 1),
                     labels = dollar_format(accuracy = 1, su = "€", pre = "")) +
  geom_label_repel(data = . %>% filter(date == max(date)),
             aes(x = date, y = value, color = variable, label = round(value, 1)))

2017T2-

Code 
t_salaire_val %>%
  filter(variable %in% c("KZ", "JZ", "C4"),
         date >= as.Date("2017-04-01")) %>%
  group_by(variable) %>%
  mutate(value = 100*value/value[date == as.Date("2017-04-01")]) %>%
  ggplot() + ylab("") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = value, color = variable)) +
  scale_x_date(breaks = seq(1920, 2100, 1) %>% 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(10, 300, 2),
                     labels = dollar_format(accuracy = 1, prefix = "")) +
  geom_label_repel(data = . %>% filter(date == max(date)),
             aes(x = date, y = value, color = variable, label = round(value, 1)))

C2, C3, C4, C5

All

Code 
t_salaire_val %>%
  filter(variable %in% c("C2", "C3", "C4", "C5")) %>%
  group_by(variable) %>%
  ggplot() + ylab("Salaire moyen par tête - SMPT") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = value, color = variable)) +
  scale_x_date(breaks = seq(1920, 2100, 5) %>% 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 = 1000*seq(1, 300, 1),
                     labels = dollar_format(accuracy = 1, su = "€", pre = "")) +
  geom_label_repel(data = . %>% filter(date == max(date)),
             aes(x = date, y = value, color = variable, label = round(value, 1)))

1990-

Code 
t_salaire_val %>%
  filter(variable %in% c("C2", "C3", "C4", "C5"),
         date >= as.Date("1990-01-01")) %>%
  group_by(variable) %>%
  ggplot() + ylab("Salaire moyen par tête - SMPT") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = value, color = variable)) +
  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 = 1000*seq(1, 300, 1),
                     labels = dollar_format(accuracy = 1, su = "€", pre = "")) +
  geom_label_repel(data = . %>% filter(date == max(date)),
             aes(x = date, y = value, color = variable, label = round(value, 1)))

2017T2-

Code 
t_salaire_val %>%
  filter(variable %in% c("C2", "C3", "C4", "C5"),
         date >= as.Date("2017-04-01")) %>%
  group_by(variable) %>%
  mutate(value = 100*value/value[date == as.Date("2017-04-01")]) %>%
  ggplot() + ylab("") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = value, color = variable)) +
  scale_x_date(breaks = seq(1920, 2100, 1) %>% 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(10, 300, 2),
                     labels = dollar_format(accuracy = 1, prefix = "")) +
  geom_label_repel(data = . %>% filter(date == max(date)),
             aes(x = date, y = value, color = variable, label = round(value, 1)))

Agriculture, Industrie, Total

Value

Code 
t_salaire_val %>%
  filter(variable %in% c("TOTAL", "AZ", "C"),
         date >= as.Date("1990-01-01")) %>%
  group_by(variable) %>%
  ggplot() + ylab("Salaire moyen par tête - SMPT") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = value, color = variable)) +
  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 = 1000*seq(1, 300, 1),
                     labels = dollar_format(accuracy = 1, su = "€", pre = "")) +
  geom_label_repel(data = . %>% filter(date == max(date)),
             aes(x = date, y = value, color = variable, label = round(value, 1)))

1990-

Code 
t_salaire_val %>%
  filter(variable %in% c("TOTAL", "AZ", "C"),
         date >= as.Date("1990-01-01")) %>%
  group_by(variable) %>%
  mutate(value = 100*value/value[date == as.Date("1990-01-01")]) %>%
  ggplot() + ylab("") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = value, color = variable)) +
  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(10, 300, 10),
                     labels = dollar_format(accuracy = 1, prefix = "")) +
  geom_label_repel(data = . %>% filter(date == max(date)),
             aes(x = date, y = value, color = variable, label = round(value, 1)))

1996-

Code 
t_salaire_val %>%
  filter(variable %in% c("TOTAL", "AZ", "C"),
         date >= as.Date("1996-01-01")) %>%
  group_by(variable) %>%
  mutate(value = 100*value/value[date == as.Date("1996-01-01")]) %>%
  ggplot() + ylab("") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = value, color = variable)) +
  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(10, 300, 10),
                     labels = dollar_format(accuracy = 1, prefix = "")) +
  geom_label_repel(data = . %>% filter(date == max(date)),
             aes(x = date, y = value, color = variable, label = round(value, 1)))

2012-

Code 
t_salaire_val %>%
  filter(variable %in% c("TOTAL", "AZ", "C"),
         date >= as.Date("2012-01-01")) %>%
  group_by(variable) %>%
  mutate(value = 100*value/value[date == as.Date("2012-01-01")]) %>%
  ggplot() + ylab("") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = value, color = variable)) +
  scale_x_date(breaks = seq(1920, 2100, 1) %>% 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(10, 300, 2),
                     labels = dollar_format(accuracy = 1, prefix = "")) +
  geom_label_repel(data = . %>% filter(date == max(date)),
             aes(x = date, y = value, color = variable, label = round(value, 1)))

2017-

Code 
t_salaire_val %>%
  filter(variable %in% c("TOTAL", "AZ", "C"),
         date >= as.Date("2017-01-01")) %>%
  group_by(variable) %>%
  mutate(value = 100*value/value[date == as.Date("2017-01-01")]) %>%
  ggplot() + ylab("") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = value, color = variable)) +
  scale_x_date(breaks = seq(1920, 2100, 1) %>% 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(10, 300, 2),
                     labels = dollar_format(accuracy = 1, prefix = "")) +
  geom_label_repel(data = . %>% filter(date == max(date)),
             aes(x = date, y = value, color = variable, label = round(value, 1)))

2017T2-

Code 
t_salaire_val %>%
  filter(variable %in% c("TOTAL", "AZ", "C"),
         date >= as.Date("2017-04-01")) %>%
  group_by(variable) %>%
  mutate(value = 100*value/value[date == as.Date("2017-04-01")]) %>%
  ggplot() + ylab("") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = value, color = variable)) +
  scale_x_date(breaks = seq(1920, 2100, 1) %>% 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(10, 300, 2),
                     labels = dollar_format(accuracy = 1, prefix = "")) +
  geom_label_repel(data = . %>% filter(date == max(date)),
             aes(x = date, y = value, color = variable, label = round(value, 1)))

2019T4-

Code 
t_salaire_val %>%
  filter(variable %in% c("TOTAL", "AZ", "C"),
         date >= as.Date("2019-10-01")) %>%
  group_by(variable) %>%
  mutate(value = 100*value/value[date == as.Date("2019-10-01")]) %>%
  ggplot() + ylab("") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = value, color = variable)) +
  scale_x_date(breaks = seq(1920, 2100, 1) %>% 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(10, 300, 2),
                     labels = dollar_format(accuracy = 1, prefix = "")) +
  geom_label_repel(data = . %>% filter(date == max(date)),
             aes(x = date, y = value, color = variable, label = round(value, 1)))

2021T3-

Code 
df <- t_salaire_val %>%
  filter(variable %in% c("TOTAL", "AZ", "C"),
         date >= as.Date("2021-07-01")) %>%
  group_by(variable) %>%
  arrange(date) %>%
  mutate(value = 100*value/value[1]) %>%
  date_to_yearqtr()

ggplot(data = df) + ylab("") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = value, color = variable)) +
  scale_x_yearqtr(labels = date_format("%Y T%q"),
                  breaks = seq(from = min(df$date), to = max(df$date), by = 0.25)) +
  theme(legend.position = c(0.7, 0.2),
        legend.title = element_blank(),
        axis.text.x = element_text(angle = 45, vjust = 1, hjust = 1)) +
  scale_y_log10(breaks = seq(10, 300, 1),
                     labels = dollar_format(accuracy = 1, prefix = "")) +
  geom_label_repel(data = . %>% filter(date == max(date)),
             aes(x = date, y = value, color = variable, label = round(value, 1)))

2021T4-

Code 
df <- t_salaire_val %>%
  filter(variable %in% c("TOTAL", "AZ", "C"),
         date >= as.Date("2021-10-01")) %>%
  group_by(variable) %>%
  arrange(date) %>%
  mutate(value = 100*value/value[1]) %>%
  date_to_yearqtr()

ggplot(data = df) + ylab("") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = value, color = variable)) +
  scale_x_yearqtr(labels = date_format("%Y T%q"),
                  breaks = seq(from = min(df$date), to = max(df$date), by = 0.25)) +
  theme(legend.position = c(0.7, 0.2),
        legend.title = element_blank(),
        axis.text.x = element_text(angle = 45, vjust = 1, hjust = 1)) +
  scale_y_log10(breaks = seq(10, 300, 1),
                     labels = dollar_format(accuracy = 1, prefix = "")) +
  geom_label_repel(data = . %>% filter(date == max(date)),
             aes(x = date, y = value, color = variable, label = round(value, 1)))

Services Marchands, Total, Non Marchands

1990-

Code 
t_salaire_val %>%
  filter(variable %in% c("TOTAL", "OQ", "(GZ) à (MN), (RU)"),
         date >= as.Date("1990-01-01")) %>%
  group_by(variable) %>%
  mutate(value = 100*value/value[date == as.Date("1990-01-01")]) %>%
  ggplot() + ylab("") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = value, color = variable)) +
  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(10, 300, 5),
                     labels = dollar_format(accuracy = 1, prefix = "")) +
  geom_label_repel(data = . %>% filter(date == max(date)),
             aes(x = date, y = value, color = variable, label = round(value, 1)))

1996-

Code 
t_salaire_val %>%
  filter(variable %in% c("TOTAL", "OQ", "(GZ) à (MN), (RU)"),
         date >= as.Date("1996-01-01")) %>%
  group_by(variable) %>%
  mutate(value = 100*value/value[date == as.Date("1996-01-01")]) %>%
  ggplot() + ylab("") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = value, color = variable)) +
  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(10, 300, 5),
                     labels = dollar_format(accuracy = 1, prefix = "")) +
  geom_label_repel(data = . %>% filter(date == max(date)),
             aes(x = date, y = value, color = variable, label = round(value, 1)))

2012-

Code 
t_salaire_val %>%
  filter(variable %in% c("TOTAL", "OQ", "(GZ) à (MN), (RU)"),
         date >= as.Date("2012-01-01")) %>%
  group_by(variable) %>%
  mutate(value = 100*value/value[date == as.Date("2012-01-01")]) %>%
  ggplot() + ylab("") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = value, color = variable)) +
  scale_x_date(breaks = seq(1920, 2100, 1) %>% 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(10, 300, 2),
                     labels = dollar_format(accuracy = 1, prefix = "")) +
  geom_label_repel(data = . %>% filter(date == max(date)),
             aes(x = date, y = value, color = variable, label = round(value, 1)))

2017-

Code 
df <- t_salaire_val %>%
  filter(variable %in% c("TOTAL", "OQ", "(GZ) à (MN), (RU)"),
         date >= as.Date("2017-01-01")) %>%
  group_by(variable) %>%
  arrange(date) %>%
  mutate(value = 100*value/value[1]) %>%
  date_to_yearqtr %>%
  ungroup

ggplot(data = df) + ylab("") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = value, color = variable)) +
  scale_x_yearqtr(labels = date_format("%Y T%q"),
                  breaks = seq(from = min(df$date), to = max(df$date), by = 0.5)) +
  theme(legend.position = c(0.7, 0.2),
        legend.title = element_blank(),
        axis.text.x = element_text(angle = 45, vjust = 1, hjust = 1)) +
  scale_y_log10(breaks = seq(10, 300, 2),
                     labels = dollar_format(accuracy = 1, prefix = "")) +
  geom_label_repel(data = . %>% filter(date == max(date)),
             aes(x = date, y = value, color = variable, label = round(value, 1)))

2017T2-

Code 
df <- t_salaire_val %>%
  filter(variable %in% c("TOTAL", "OQ", "(GZ) à (MN), (RU)"),
         date >= as.Date("2017-04-01")) %>%
  group_by(variable) %>%
  arrange(date) %>%
  mutate(value = 100*value/value[1]) %>%
  date_to_yearqtr %>%
  ungroup

ggplot(data = df) + ylab("") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = value, color = variable)) +
  scale_x_yearqtr(labels = date_format("%Y T%q"),
                  breaks = seq(from = min(df$date), to = max(df$date), by = 0.5)) +
  theme(legend.position = c(0.7, 0.2),
        legend.title = element_blank(),
        axis.text.x = element_text(angle = 45, vjust = 1, hjust = 1)) +
  scale_y_log10(breaks = seq(10, 300, 2),
                     labels = dollar_format(accuracy = 1, prefix = "")) +
  geom_label_repel(data = . %>% filter(date == max(date)),
             aes(x = date, y = value, color = variable, label = round(value, 1)))

2019T4-

Code 
df <- t_salaire_val %>%
  filter(variable %in% c("TOTAL", "OQ", "(GZ) à (MN), (RU)"),
         date >= as.Date("2019-10-01")) %>%
  group_by(variable) %>%
  arrange(date) %>%
  mutate(value = 100*value/value[1]) %>%
  date_to_yearqtr %>%
  ungroup

ggplot(data = df) + ylab("") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = value, color = variable)) +
  scale_x_yearqtr(labels = date_format("%Y T%q"),
                  breaks = seq(from = min(df$date), to = max(df$date), by = 0.25)) +
  theme(legend.position = c(0.7, 0.2),
        legend.title = element_blank(),
        axis.text.x = element_text(angle = 45, vjust = 1, hjust = 1)) +
  scale_y_log10(breaks = seq(10, 300, 2),
                     labels = dollar_format(accuracy = 1, prefix = "")) +
  geom_label_repel(data = . %>% filter(date == max(date)),
             aes(x = date, y = value, color = variable, label = round(value, 1)))

2021T2-

Code 
df <- t_salaire_val %>%
  filter(variable %in% c("TOTAL", "OQ", "(GZ) à (MN), (RU)"),
         date >= as.Date("2021-04-01")) %>%
  group_by(variable) %>%
  arrange(date) %>%
  mutate(value = 100*value/value[1]) %>%
  date_to_yearqtr %>%
  ungroup

ggplot(data = df) + ylab("") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = value, color = variable)) +
  scale_x_yearqtr(labels = date_format("%Y T%q"),
                  breaks = seq(from = min(df$date), to = max(df$date), by = 0.25)) +
  theme(legend.position = c(0.7, 0.2),
        legend.title = element_blank(),
        axis.text.x = element_text(angle = 45, vjust = 1, hjust = 1)) +
  scale_y_log10(breaks = seq(10, 300, 2),
                     labels = dollar_format(accuracy = 1, prefix = "")) +
  geom_label_repel(data = . %>% filter(date == max(date)),
             aes(x = date, y = value, color = variable, label = round(value, 1)))

2021T3-

Code 
df <- t_salaire_val %>%
  filter(variable %in% c("TOTAL", "OQ", "(GZ) à (MN), (RU)"),
         date >= as.Date("2021-07-01")) %>%
  group_by(variable) %>%
  arrange(date) %>%
  mutate(value = 100*value/value[1]) %>%
  date_to_yearqtr %>%
  ungroup

ggplot(data = df) + ylab("") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = value, color = variable)) +
  scale_x_yearqtr(labels = date_format("%Y T%q"),
                  breaks = seq(from = min(df$date), to = max(df$date), by = 0.25)) +
  theme(legend.position = c(0.7, 0.2),
        legend.title = element_blank(),
        axis.text.x = element_text(angle = 45, vjust = 1, hjust = 1)) +
  scale_y_log10(breaks = seq(10, 300, 2),
                     labels = dollar_format(accuracy = 1, prefix = "")) +
  geom_label_repel(data = . %>% filter(date == max(date)),
             aes(x = date, y = value, color = variable, label = round(value, 1)))

2021T4-

Nominal

Code 
df <- t_salaire_val %>%
  filter(variable %in% c("TOTAL", "OQ", "(GZ) à (MN), (RU)"),
         date >= as.Date("2021-10-01")) %>%
  group_by(variable) %>%
  arrange(date) %>%
  mutate(value = 100*value/value[1]) %>%
  date_to_yearqtr %>%
  ungroup

ggplot(data = df) + ylab("") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = value, color = variable)) +
  scale_x_yearqtr(labels = date_format("%Y T%q"),
                  breaks = seq(from = min(df$date), to = max(df$date), by = 0.25)) +
  theme(legend.position = c(0.7, 0.2),
        legend.title = element_blank(),
        axis.text.x = element_text(angle = 45, vjust = 1, hjust = 1)) +
  scale_y_log10(breaks = seq(10, 300, 2),
                     labels = dollar_format(accuracy = 1, prefix = "")) +
  geom_label_repel(data = . %>% filter(date == max(date)),
             aes(x = date, y = value, color = variable, label = round(value, 1)))