Salaire moyen par tête - SMPT (données CVS)

Data - Insee

Author

François Geerolf

Info

source dataset .html .RData

insee

IPC-2015

 2024-06-20 2024-06-19

insee

IPCH-2015

 2024-06-20 2024-06-19

insee

t_salaire_val

 2024-06-20 2024-03-04

Données sur les salaires

source dataset .html .RData

dares

les-indices-de-salaire-de-base

 2024-06-17 2024-03-25

insee

CNA-2014-RDB

 2024-06-20 2024-06-18

insee

CNT-2014-CSI

 2024-06-20 2024-06-18

insee

ECRT2023

 2024-06-20 2023-06-30

insee

if230

 2024-06-20 2021-12-04

insee

INDICE-TRAITEMENT-FP

 2024-06-20 2024-06-18

insee

ir_salaires_SL_csv

 2024-06-20 NA

insee

SALAIRES-ACEMO

 2024-06-20 2024-06-19

insee

SALAIRES-ACEMO-2017

 2024-06-20 2024-06-19

insee

SALAIRES-ANNUELS

 2024-06-20 2024-06-19

insee

t_7401

 2024-06-20 2023-12-23

insee

t_salaire_val

 2024-06-20 2024-03-04

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

variable

Code 
t_salaire_val %>%
  group_by(variable) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  print_table_conditional
variable Nobs
(DE) à (C5) 300
(DE) à (MN), (RU) 300
(GZ) à (MN), (RU) 300
AZ 300
C 300
C1 300
C2 300
C3 300
C4 300
C5 300
DE 300
FZ 300
GZ 300
HZ 300
IZ 300
JZ 300
KZ 300
LZ 300
MN 300
OQ 300
RU 300
TOTAL 300

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 13003.52 16950.00 2.685915
C4 12489.59 16773.04 2.992680
KZ 11223.68 14730.84 2.756481
C2 12837.11 13566.91 0.554467
C3 10350.80 12454.34 1.867273
C5 9420.42 11860.83 2.330355
C 9296.05 11523.62 2.171330
(DE) à (C5) 9365.36 11494.11 2.069288
DE 9971.32 11261.89 1.224552
FZ 8940.00 11092.31 2.180600
MN 8905.25 11023.52 2.156832
(DE) à (MN), (RU) 8541.63 10639.47 2.220482
(GZ) à (MN), (RU) 8295.52 10413.46 2.299885
LZ 8685.89 10177.08 1.597001
TOTAL 8025.29 10081.05 2.306801
GZ 7435.02 9191.13 2.143016
HZ 7874.61 9122.30 1.481652
OQ 7040.34 8990.58 2.475349
C1 7221.01 8874.06 2.082769
IZ 6592.35 8239.40 2.255231
RU 6074.21 7825.97 2.566335
AZ 4811.57 5643.18 1.607019

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 = ""))

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 = ""))

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 = ""))

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 = ""))

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 = ""))

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 = ""))

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 = ""))

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 = ""))

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 = ""))

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 = ""))

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 = ""))

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 = ""))

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 = ""))

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 = ""))

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 = ""))

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 = ""))

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 = ""))

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 = ""))