Indice des prix à la consommation - Base 1970, 1980
Data - INSEE
François Geerolf
Info
| source | dataset | .html | .RData |
|---|---|---|---|
| insee | IPC-1970-1980 | 2024-04-18 | 2024-05-09 |
Données sur l’inflation en France
| source | dataset | .html | .RData |
|---|---|---|---|
| insee | bdf2017 | 2024-05-09 | 2023-11-21 |
| insee | ILC-ILAT-ICC | 2024-05-09 | 2024-05-09 |
| insee | INDICES_LOYERS | 2024-05-09 | 2024-05-09 |
| insee | IPC-1970-1980 | 2024-04-18 | 2024-05-09 |
| insee | IPC-1990 | 2024-04-18 | 2024-05-09 |
| insee | IPC-2015 | 2024-04-18 | 2024-04-09 |
| insee | IPC-PM-2015 | 2024-04-18 | 2024-05-09 |
| insee | IPCH-2015 | 2024-04-18 | 2024-05-09 |
| insee | IPGD-2015 | 2024-04-18 | 2024-03-20 |
| insee | IPLA-IPLNA-2015 | 2024-04-18 | 2024-05-09 |
| insee | IPPI-2015 | 2024-04-18 | 2024-03-30 |
| insee | IRL | 2024-04-18 | 2024-05-09 |
| insee | SERIES_LOYERS | 2024-04-18 | 2024-05-09 |
| insee | T_CONSO_EFF_FONCTION | 2024-04-18 | 2024-04-01 |
LAST_UPDATE
`IPC-1970-1980` %>%
group_by(LAST_UPDATE) %>%
summarise(Nobs = n()) %>%
arrange(desc(LAST_UPDATE)) %>%
print_table_conditional()| LAST_UPDATE | Nobs |
|---|---|
| 2018-02-12 | 143261 |
Last TIME_PERIOD
`IPC-1970-1980` %>%
group_by(TIME_PERIOD) %>%
summarise(Nobs = n()) %>%
arrange(desc(TIME_PERIOD)) %>%
head(1) %>%
print_table_conditional()| TIME_PERIOD | Nobs |
|---|---|
| 1992-12 | 228 |
Info
- Indice des prix des 295 postes.
PRODUITS_IPC_1970_1980
All
CORRECTION
`IPC-1970-1980` %>%
left_join(CORRECTION, by = "CORRECTION") %>%
group_by(CORRECTION, Correction) %>%
summarise(Nobs = n()) %>%
arrange(-Nobs) %>%
print_table_conditional| CORRECTION | Correction | Nobs |
|---|---|---|
| BRUT | Non corrigé | 141449 |
| CVS | Corrigé des variations saisonnières | 1812 |
FREQ
`IPC-1970-1980` %>%
left_join(FREQ, by = "FREQ") %>%
group_by(FREQ, Freq) %>%
summarise(Nobs = n()) %>%
arrange(-Nobs) %>%
print_table_conditional| FREQ | Freq | Nobs |
|---|---|---|
| M | Monthly | 128968 |
| A | Annual | 14293 |
NATURE
`IPC-1970-1980` %>%
left_join(NATURE, by = "NATURE") %>%
group_by(NATURE, Nature) %>%
summarise(Nobs = n()) %>%
arrange(-Nobs) %>%
print_table_conditional| NATURE | Nature | Nobs |
|---|---|---|
| INDICE | Indice | 137011 |
| POND | Pondérations d’indice | 3743 |
| VARIATIONS_M | Variations mensuelles | 2484 |
| VARIATIONS_A | Variations annuelles | 23 |
BASIND
`IPC-1970-1980` %>%
left_join(BASIND, by = "BASIND") %>%
group_by(BASIND, Basind) %>%
summarise(Nobs = n()) %>%
arrange(-Nobs) %>%
print_table_conditional| BASIND | Basind | Nobs |
|---|---|---|
| 1980 | 1980 | 99788 |
| 1970 | 1970 | 39730 |
| SO | Sans objet | 3743 |
REGROUPEMENTS_IPC_1970_1980
PRODUITS_IPC_1970_1980
TITLE
TITLE_FR
REF_AREA
`IPC-1970-1980` %>%
group_by(REF_AREA) %>%
summarise(Nobs = n()) %>%
arrange(-Nobs) %>%
print_table_conditional| REF_AREA | Nobs |
|---|---|
| FM | 129198 |
| D75 | 14063 |
TIME_PERIOD
Pondération
1979, 1989, 1992
`IPC-1970-1980` %>%
filter(TIME_PERIOD %in% c("1949", "1969", "1992", "1979", "1989"),
CORRECTION == "BRUT",
NATURE == "POND",
REF_AREA == "FM") %>%
select_if(function(col) length(unique(col)) > 1) %>%
select(-IDBANK, -TITLE_FR, -TITLE_EN, -DECIMALS) %>%
left_join(REGROUPEMENTS_IPC_1970_1980, by = "REGROUPEMENTS_IPC_1970_1980") %>%
left_join(PRODUITS_IPC_1970_1980, by = "PRODUITS_IPC_1970_1980") %>%
spread(TIME_PERIOD, OBS_VALUE) %>%
print_table_conditional()Services de Santé
`IPC-1970-1980` %>%
filter(NATURE == "POND",
PRODUITS_IPC_1970_1980 == "760") %>%
year_to_date %>%
mutate(OBS_VALUE = OBS_VALUE/10000) %>%
ggplot() + ylab("Poids des services de santé") + xlab("") + theme_minimal() +
geom_line(aes(x = date, y = OBS_VALUE)) +
scale_color_manual(values = viridis(3)[1:2]) +
scale_x_date(breaks = seq(1920, 2025, 2) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%Y")) +
scale_y_continuous(breaks = 0.01*seq(0, 10, 0.1),
labels = percent_format(accuracy = .1))
Produits pharmaceutiques
`IPC-1970-1980` %>%
filter(NATURE == "POND",
PRODUITS_IPC_1970_1980 == "587") %>%
year_to_date %>%
mutate(OBS_VALUE = OBS_VALUE/10000) %>%
ggplot() + ylab("Poids des produits pharmaceutiques") + xlab("") + theme_minimal() +
geom_line(aes(x = date, y = OBS_VALUE)) +
scale_color_manual(values = viridis(3)[1:2]) +
scale_x_date(breaks = seq(1920, 2025, 2) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%Y")) +
scale_y_continuous(breaks = 0.01*seq(0, 10, 0.1),
labels = percent_format(accuracy = .1))
Table
1949, 1969
`IPC-1970-1980` %>%
filter(TIME_PERIOD %in% c("1949", "1969"),
CORRECTION == "BRUT",
NATURE == "INDICE",
REF_AREA == "FM") %>%
mutate(TITLE_FR = gsub("Indice des prix des 295 postes - Base 100 en 1970 - ", "", TITLE_FR),
TITLE_FR = gsub("Indice des prix des 295 postes - Base 100 en 1980 - ", "", TITLE_FR)) %>%
select(TITLE_FR, BASIND, PROD = PRODUITS_IPC_1970_1980, REGR = REGROUPEMENTS_IPC_1970_1980, TIME_PERIOD, OBS_VALUE) %>%
spread(TIME_PERIOD, OBS_VALUE) %>%
print_table_conditionalLoyers
Mensuel - Base 1980
`IPC-1970-1980` %>%
filter(INDICATEUR == "IPC",
REGROUPEMENTS_IPC_1970_1980 == "PARIS11" | PRODUITS_IPC_1970_1980 == "711",
BASIND == "1980",
FREQ == "M") %>%
month_to_date %>%
group_by(REGROUPEMENTS_IPC_1970_1980, PRODUITS_IPC_1970_1980) %>%
mutate(OBS_VALUE = 100*OBS_VALUE/OBS_VALUE[date == as.Date("1990-01-01")]) %>%
ggplot() + ylab("Indice des prix") + xlab("") + theme_minimal() +
geom_line(aes(x = date, y = OBS_VALUE, color = TITLE_FR, linetype = TITLE_FR)) +
scale_color_manual(values = viridis(4)[1:3]) +
scale_x_date(breaks = seq(1920, 2025, 5) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%y")) +
theme(legend.position = c(0.75, 0.3),
legend.title = element_blank()) +
scale_y_log10(breaks = seq(0, 200, 10),
labels = dollar_format(accuracy = 1, prefix = ""))
Mensuel - Base 1970
`IPC-1970-1980` %>%
filter(INDICATEUR == "IPC",
REGROUPEMENTS_IPC_1970_1980 == "PARIS11" | PRODUITS_IPC_1970_1980 == "711",
BASIND == "1970",
FREQ == "M") %>%
month_to_date %>%
group_by(REGROUPEMENTS_IPC_1970_1980, PRODUITS_IPC_1970_1980) %>%
mutate(OBS_VALUE = 100*OBS_VALUE/OBS_VALUE[date == as.Date("1983-01-01")]) %>%
ggplot() + ylab("Indice des prix") + xlab("") + theme_minimal() +
geom_line(aes(x = date, y = OBS_VALUE, color = TITLE_FR, linetype = TITLE_FR)) +
scale_color_manual(values = viridis(4)[1:3]) +
scale_x_date(breaks = seq(1920, 2025, 5) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%y")) +
theme(legend.position = c(0.75, 0.3),
legend.title = element_blank()) +
scale_y_log10(breaks = seq(0, 200, 10),
labels = dollar_format(accuracy = 1, prefix = ""))
Mensuel - Base 1970
All
`IPC-1970-1980` %>%
filter(INDICATEUR == "IPC",
PRODUITS_IPC_1970_1980 %in% c("711", "SO"),
BASIND == "1970",
FREQ == "M") %>%
month_to_date %>%
left_join(PRODUITS_IPC_1970_1980, by = "PRODUITS_IPC_1970_1980") %>%
group_by(PRODUITS_IPC_1970_1980) %>%
mutate(OBS_VALUE = 100*OBS_VALUE/OBS_VALUE[date == as.Date("1983-01-01")]) %>%
ggplot() + ylab("Indice des prix") + xlab("") + theme_minimal() +
geom_line(aes(x = date, y = OBS_VALUE, color = Produits_ipc_1970_1980, linetype = Produits_ipc_1970_1980)) +
scale_color_manual(values = viridis(4)[1:3]) +
scale_x_date(breaks = seq(1920, 2025, 5) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%y")) +
theme(legend.position = c(0.75, 0.3),
legend.title = element_blank()) +
scale_y_log10(breaks = seq(0, 200, 10),
labels = dollar_format(accuracy = 1, prefix = ""))
1960
`IPC-1970-1980` %>%
filter(INDICATEUR == "IPC",
PRODUITS_IPC_1970_1980 %in% c("711", "SO"),
BASIND == "1970",
FREQ == "M") %>%
month_to_date %>%
filter(date >=as.Date("1960-01-01")) %>%
left_join(PRODUITS_IPC_1970_1980, by = "PRODUITS_IPC_1970_1980") %>%
group_by(PRODUITS_IPC_1970_1980) %>%
mutate(OBS_VALUE = 100*OBS_VALUE/OBS_VALUE[date == as.Date("1960-01-01")]) %>%
ggplot() + ylab("Indice des prix") + xlab("") + theme_minimal() +
geom_line(aes(x = date, y = OBS_VALUE, color = Produits_ipc_1970_1980, linetype = Produits_ipc_1970_1980)) +
scale_color_manual(values = viridis(4)[1:3]) +
scale_x_date(breaks = seq(1920, 2025, 5) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%y")) +
theme(legend.position = c(0.75, 0.3),
legend.title = element_blank()) +
scale_y_log10(breaks = seq(0, 1000, 50),
labels = dollar_format(accuracy = 1, prefix = ""))
Mensuel - Base 1970
`IPC-1970-1980` %>%
filter(INDICATEUR == "IPC",
PRODUITS_IPC_1970_1980 %in% c("711", "SO"),
REGROUPEMENTS_IPC_1970_1980 == "SO",
BASIND == "1980",
FREQ == "M") %>%
month_to_date %>%
left_join(PRODUITS_IPC_1970_1980, by = "PRODUITS_IPC_1970_1980") %>%
group_by(PRODUITS_IPC_1970_1980) %>%
mutate(OBS_VALUE = 100*OBS_VALUE/OBS_VALUE[date == as.Date("1983-01-01")]) %>%
ggplot() + ylab("Indice des prix") + xlab("") + theme_minimal() +
geom_line(aes(x = date, y = OBS_VALUE, color = Produits_ipc_1970_1980, linetype = Produits_ipc_1970_1980)) +
scale_color_manual(values = viridis(4)[1:3]) +
scale_x_date(breaks = seq(1920, 2025, 5) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%y")) +
theme(legend.position = c(0.75, 0.3),
legend.title = element_blank()) +
scale_y_log10(breaks = seq(0, 200, 10),
labels = dollar_format(accuracy = 1, prefix = ""))
Annual - Base 1970
`IPC-1970-1980` %>%
filter(INDICATEUR == "IPC",
REGROUPEMENTS_IPC_1970_1980 == "PARIS11" | PRODUITS_IPC_1970_1980 == "711",
BASIND == "1970",
FREQ == "A") %>%
year_to_date %>%
group_by(REGROUPEMENTS_IPC_1970_1980, PRODUITS_IPC_1970_1980) %>%
mutate(OBS_VALUE = 100*OBS_VALUE/OBS_VALUE[date == as.Date("1983-01-01")]) %>%
ggplot() + ylab("Indice des prix") + xlab("") + theme_minimal() +
geom_line(aes(x = date, y = OBS_VALUE, color = TITLE_FR, linetype = TITLE_FR)) +
scale_color_manual(values = viridis(4)[1:3]) +
scale_x_date(breaks = seq(1920, 2025, 5) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%y")) +
theme(legend.position = c(0.75, 0.3),
legend.title = element_blank()) +
scale_y_log10(breaks = seq(0, 200, 10),
labels = dollar_format(accuracy = 1, prefix = ""))