Salaire moyen par tête - SMPT (données CVS)

Data - INSEE

Auteur

François Geerolf

Info

source dataset Title .html .rData
insee t_salaire_val Salaire moyen par tête - SMPT (données CVS) 2026-03-12 2026-02-27
insee IPC-2015 Indice des prix à la consommation - Base 2015 2026-03-12 2026-03-11
insee IPCH-2015 Indices des prix à la consommation harmonisés 2026-03-12 2026-03-11

Données sur les salaires

source dataset Title .html .rData
insee t_salaire_val Salaire moyen par tête - SMPT (données CVS) 2026-03-12 2026-02-27
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 2026-03-12 2026-03-11
insee CNT-2014-CSI Comptes de secteurs institutionnels 2026-03-12 2026-03-11
insee ECRT2023 Emploi, chômage, revenus du travail - Edition 2023 2026-03-12 2023-06-30
insee INDICE-TRAITEMENT-FP Indice de traitement brut dans la fonction publique de l'État 2026-03-12 2026-03-11
insee SALAIRES-ACEMO Indices trimestriels de salaires dans le secteur privé - Résultats par secteur d’activité 2026-03-12 2026-03-11
insee SALAIRES-ACEMO-2017 Indices trimestriels de salaires dans le secteur privé 2026-03-12 2026-03-11
insee SALAIRES-ANNUELS Salaires annuels 2026-03-12 2026-03-11
insee T_2101 2.101 – Revenu disponible brut des ménages et évolution du pouvoir d'achat par personne, par ménage et par unité de consommation (En milliards euros et %) 2026-03-12 2025-12-14
insee T_7401 7.401 – Compte des ménages (S14) (En milliards d'euros) 2026-03-12 2025-12-14
insee if230 Séries longues sur les salaires dans le secteur privé 2026-03-12 2021-12-04
insee ir_salaires_SL_23_csv NA NA NA
insee ir_salaires_SL_csv 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) 308
(DE) à (MN), (RU) 308
(GZ) à (MN), (RU) 308
AZ 308
C 308
C1 308
C2 308
C3 308
C4 308
C5 308
DE 308
FZ 308
GZ 308
HZ 308
IZ 308
JZ 308
KZ 308
LZ 308
MN 308
OQ 308
RU 308
TOTAL 308

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 12601.01 16504.45 2.7352708
C4 11463.30 15042.06 2.7542434
C2 13343.81 15025.41 1.1939732
KZ 11147.65 14848.03 2.9078610
C3 10570.17 12633.49 1.7991465
DE 10228.44 12160.50 1.7452640
LZ 9999.18 11780.56 1.6529894
C5 9067.98 11268.37 2.1962722
(DE) à (C5) 9034.70 11105.33 2.0849624
MN 8809.12 11048.58 2.2909928
C 8917.09 10991.16 2.1132357
FZ 8486.51 10504.59 2.1562631
(DE) à (MN), (RU) 8410.74 10483.09 2.2269752
(GZ) à (MN), (RU) 8249.82 10351.17 2.2950212
TOTAL 7851.68 9812.49 2.2543197
HZ 8202.63 9445.75 1.4211037
GZ 7305.37 9094.34 2.2145914
OQ 6745.87 8470.71 2.3029565
C1 6522.67 8206.46 2.3229482
RU 6267.56 7689.43 2.0656404
IZ 5848.39 7153.78 2.0351778
AZ 6218.63 5968.86 -0.4090976

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)))

2017T1-

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)))

2017T1-

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)))