source | dataset | .html | .RData |
---|---|---|---|
insee | reve-conso-evo-dep-pa | 2024-11-05 | 2024-09-05 |
Évolution de la dépense et du pouvoir d’achat des ménages - Données annuelles de 1960 à 2023
Data - Insee
Info
Données sur le pouvoir d’achat
source | dataset | .html | .RData |
---|---|---|---|
insee | CNA-2014-RDB | 2024-11-09 | 2024-11-09 |
insee | CNT-2014-CSI | 2024-11-09 | 2024-11-09 |
insee | conso-eff-fonction | 2024-11-09 | 2022-06-14 |
insee | econ-gen-revenu-dispo-pouv-achat-2 | 2024-11-09 | 2024-07-05 |
insee | reve-conso-evo-dep-pa | 2024-11-05 | 2024-09-05 |
insee | reve-niv-vie-individu-activite | 2024-11-05 | NA |
insee | reve-niv-vie-pouv-achat-trim | 2024-11-05 | 2024-09-05 |
insee | T_7401 | 2024-10-18 | 2024-10-18 |
insee | t_men_val | 2024-11-05 | 2024-09-02 |
insee | t_pouvachat_val | 2024-11-05 | 2024-09-04 |
insee | t_recapAgent_val | 2024-11-05 | 2024-09-02 |
insee | t_salaire_val | 2024-11-05 | 2024-09-02 |
oecd | HH_DASH | 2024-09-15 | 2023-09-09 |
LAST_COMPILE
LAST_COMPILE |
---|
2024-11-09 |
Variable
Code
`reve-conso-evo-dep-pa` %>%
group_by(variable) %>%
summarise(Nobs = n()) %>%
arrange(-Nobs) %>%
print_table_conditional
variable | Nobs |
---|---|
Dépense de consommation finale (en volume) | 64 |
Pouvoir d'achat arbitrable | 64 |
Pouvoir d'achat du RDB | 64 |
date
Code
`reve-conso-evo-dep-pa` %>%
%>%
year_to_date2 group_by(date) %>%
summarise(Nobs = n()) %>%
arrange(desc(date)) %>%
print_table_conditional
Pouvoir d’achat
1959-
Code
`reve-conso-evo-dep-pa` %>%
arrange(year) %>%
add_row(year = "1959", variable = "Dépense de consommation finale (en volume)", value = NA) %>%
add_row(year = "1959", variable = "Pouvoir d'achat du RDB", value = NA) %>%
add_row(year = "1959", variable = "Pouvoir d'achat arbitrable", value = NA) %>%
%>%
year_to_date2 filter(date >= as.Date("1959-01-01")) %>%
group_by(variable) %>%
arrange(date) %>%
mutate(index = c(100, 100*cumprod(1 + value[-1]/100))) %>%
ggplot() + geom_line(aes(x = date, y = index, color = variable)) +
xlab("") + ylab("") + theme_minimal() +
scale_x_date(breaks = as.Date(paste0(seq(1959, 2100, 5), "-01-01")),
labels = date_format("%Y")) +
theme(legend.position = c(0.3, 0.85),
legend.title = element_blank()) +
scale_y_log10(breaks = seq(100, 1000, 100)) +
geom_label_repel(data = . %>% filter(date == max(date)),
aes(x = date, y = index, color = variable, label = round(index, 1)))
1990-
Code
`reve-conso-evo-dep-pa` %>%
%>%
year_to_date2 filter(date >= as.Date("1990-01-01")) %>%
group_by(variable) %>%
arrange(date) %>%
mutate(index = c(100, 100*cumprod(1 + value[-1]/100))) %>%
ggplot() + geom_line(aes(x = date, y = index, color = variable)) +
xlab("") + ylab("") + theme_minimal() +
scale_x_date(breaks = as.Date(paste0(seq(1990, 2100, 5), "-01-01")),
labels = date_format("%Y")) +
theme(legend.position = c(0.3, 0.85),
legend.title = element_blank()) +
scale_y_log10(breaks = seq(100, 250, 5)) +
geom_label_repel(data = . %>% filter(date == max(date)),
aes(x = date, y = index, color = variable, label = round(index, 1)))
1999-
Code
`reve-conso-evo-dep-pa` %>%
%>%
year_to_date2 filter(date >= as.Date("1999-01-01")) %>%
group_by(variable) %>%
arrange(date) %>%
mutate(index = c(100, 100*cumprod(1 + value[-1]/100))) %>%
ggplot() + geom_line(aes(x = date, y = index, color = variable)) +
xlab("") + ylab("") + theme_minimal() +
scale_x_date(breaks = as.Date(paste0(seq(1999, 2100, 5), "-01-01")),
labels = date_format("%Y")) +
theme(legend.position = c(0.3, 0.85),
legend.title = element_blank()) +
scale_y_log10(breaks = seq(100, 150, 5)) +
geom_label_repel(data = . %>% filter(date == max(date)),
aes(x = date, y = index, color = variable, label = round(index, 1)))
2007-
Code
`reve-conso-evo-dep-pa` %>%
%>%
year_to_date2 filter(date >= as.Date("2007-01-01")) %>%
group_by(variable) %>%
arrange(date) %>%
mutate(index = c(100, 100*cumprod(1 + value[-1]/100))) %>%
ggplot() + geom_line(aes(x = date, y = index, color = variable)) +
xlab("") + ylab("") + theme_minimal() +
scale_x_date(breaks = as.Date(paste0(seq(1999, 2100, 1), "-01-01")),
labels = date_format("%Y")) +
theme(legend.position = c(0.3, 0.85),
legend.title = element_blank()) +
scale_y_log10(breaks = seq(100, 150, 2)) +
geom_label_repel(data = . %>% filter(date == max(date)),
aes(x = date, y = index, color = variable, label = round(index, 1)))
2017T2-
Code
`reve-conso-evo-dep-pa` %>%
%>%
year_to_date2 filter(date >= as.Date("2017-01-01")) %>%
group_by(variable) %>%
arrange(date) %>%
mutate(index = c(100, 100*cumprod(1 + value[-1]/100))) %>%
ggplot() + geom_line(aes(x = date, y = index, color = variable)) +
xlab("") + ylab("") + theme_minimal() +
scale_x_date(breaks = as.Date(paste0(seq(1999, 2100, 1), "-01-01")),
labels = date_format("%Y")) +
theme(legend.position = c(0.3, 0.85),
legend.title = element_blank()) +
scale_y_log10(breaks = seq(50, 150, 1)) +
geom_label_repel(data = . %>% filter(date == max(date)),
aes(x = date, y = index, color = variable, label = round(index, 1)))