Indices de prix et cours des matières premières

Data - INSEE

Info

source dataset Title .html .rData
insee IPPMP-NF Indices de prix et cours des matières premières 2025-12-25 2025-12-27

Informations

Données sur l’énergie

source dataset Title .html .rData
cre TRV_electricite TRV électricité 2024-10-27 2025-06-22
cre TRV_gaz TRV gaz 2024-10-07 2021-09-05
insee IPPMP-NF Indices de prix et cours des matières premières 2025-12-25 2025-12-27
insee econ-gen-solde-ech-ext-2 Solde des échanges extérieurs et principales composantes 2025-12-25 2025-05-24
insee t_5404 5.404 – Importations de biens et de services par produit à prix courants (En milliards d'euros) 2025-12-25 2021-08-01
sdes bilan_energetique Bilan énergétique 2025-06-26 2025-06-26

Data on energy

Code
load_data("energy.RData")
energy %>%
  source_dataset_file_updates()
source dataset Title .html .rData
ec WOB Weekly Oil Bulletin 2025-08-28 2024-08-25
eurostat ei_isen_m Energy - monthly data 2025-12-27 2025-12-27
eurostat nrg_bal_c Complete energy balances 2023-12-31 2025-12-27
eurostat nrg_pc_202 Gas prices for household consumers - bi-annual data (from 2007 onwards) 2025-12-25 2025-12-27
eurostat nrg_pc_203 Gas prices for non-household consumers - bi-annual data (from 2007 onwards) 2023-06-11 2025-12-27
eurostat nrg_pc_203_c Gas prices components for non-household consumers - annual data 2025-12-25 2025-12-27
eurostat nrg_pc_203_h Gas prices for industrial consumers - bi-annual data (until 2007) 2025-12-25 2025-12-27
eurostat nrg_pc_203_v Non-household consumption volumes of gas by consumption bands 2025-12-25 2025-12-27
eurostat nrg_pc_204 Electricity prices for household consumers - bi-annual data (from 2007 onwards) 2025-12-25 2025-12-27
eurostat nrg_pc_205 Electricity prices for non-household consumers - bi-annual data (from 2007 onwards) 2023-06-11 2025-12-27
fred energy Energy 2025-12-25 2025-12-25
iea world_energy_balances_highlights_2022 World Energy Balances Highlights (2022 edition) 2024-06-20 2023-04-24
wb CMO World Bank Commodity Price Data (The Pink Sheet) 2025-12-24 2025-12-24
wdi EG.GDP.PUSE.KO.PP.KD GDP per unit of energy use (constant 2017 PPP $ per kg of oil equivalent) 2025-12-24 2025-12-24
wdi EG.USE.PCAP.KG.OE Energy use (kg of oil equivalent per capita) 2025-12-24 2025-12-24
yahoo energy Energy 2025-12-24 2025-12-24

LAST_DOWNLOAD

Code
tibble(LAST_DOWNLOAD = as.Date(file.info("~/iCloud/website/data/insee/IPPMP-NF.RData")$mtime)) %>%
  print_table_conditional()
LAST_DOWNLOAD
2025-12-27

Last

Code
`IPPMP-NF` %>%
  group_by(TIME_PERIOD) %>%
  summarise(Nobs = n()) %>%
  arrange(desc(TIME_PERIOD)) %>%
  head(1) %>%
  print_table_conditional()
TIME_PERIOD Nobs
2025-11 131

TITLE_FR

Code
`IPPMP-NF` %>%
  group_by(IDBANK, TITLE_FR) %>%
  summarise(Nobs = n(),
            date1 = first(TIME_PERIOD),
            date2 = last(TIME_PERIOD)) %>%
  arrange(-Nobs) %>%
  print_table_conditional()

BASIND

Code
`IPPMP-NF` %>%
  left_join(BASIND, by = "BASIND") %>%
  group_by(BASIND, Basind) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  print_table_conditional()
BASIND Basind Nobs
SO Sans objet 37828
2010 2010 29293
2015 2015 379

DEVISE

Code
`IPPMP-NF` %>%
  left_join(DEVISE, by = "DEVISE") %>%
  group_by(DEVISE, Devise) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  print_table_conditional()
DEVISE Devise Nobs
SO Sans objet 64939
COUR_NORV NA 431
DA Dollar australien 431
LIT Livre sterling 431
USD Dollar US 431
YUAN NA 431
DM Dollar malais 406

MONNAIE

Code
`IPPMP-NF` %>%
  left_join(MONNAIE, by = "MONNAIE") %>%
  group_by(MONNAIE, Monnaie) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  print_table_conditional()
MONNAIE Monnaie Nobs
0048 Dollar US 17771
E Prix en euros 15006
D Prix en devises 12368
SO Sans objet 9625
0151 Cent US 5589
0207 Euro 3356
0201 Euro avec rétropolation en euro converti à taux fixe 1699
0147 Yuan chinois 1259
0014 Couronne norvégienne 431
0121 Ringgit malaisien 396

MATIERES_PREMIERES

Code
`IPPMP-NF` %>%
  left_join(MATIERES_PREMIERES, by = "MATIERES_PREMIERES") %>%
  group_by(MATIERES_PREMIERES, Matieres_premieres) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  print_table_conditional()

NOUVEAU_FOURNISSEUR

Code
`IPPMP-NF` %>%
  left_join(NOUVEAU_FOURNISSEUR, by = "NOUVEAU_FOURNISSEUR") %>%
  group_by(NOUVEAU_FOURNISSEUR, Nouveau_fournisseur) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  print_table_conditional()
NOUVEAU_FOURNISSEUR Nouveau_fournisseur Nobs
NOUVEAU Nouveau 67266
SO Sans objet 234

INDICATEUR

Code
`IPPMP-NF` %>%
  left_join(INDICATEUR, by = "INDICATEUR") %>%
  group_by(INDICATEUR, Indicateur) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  print_table_conditional()
INDICATEUR Indicateur Nobs
CIMP Cours internationaux des matières premières 35646
IPIMPI Indices des prix internationaux des matières importées 19668
IIEMP Indices internationaux en euros des matières premières 9625
CDECMPI Cours des devises étrangères 2561

NATURE

Code
`IPPMP-NF` %>%
  left_join(NATURE, by = "NATURE") %>%
  group_by(NATURE, Nature) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  print_table_conditional()
NATURE Nature Nobs
VALEUR_ABSOLUE Valeur absolue 37828
INDICE Indice 29672

TIME_PERIOD

Code
`IPPMP-NF` %>%
  group_by(TIME_PERIOD) %>%
  summarise(Nobs = n()) %>%
  arrange(desc(TIME_PERIOD)) %>%
  print_table_conditional()

Prix du pétrole

Valeur

All

Code
`IPPMP-NF` %>%
  filter(INDICATEUR == "CIMP",
         MATIERES_PREMIERES == "41") %>%
  left_join(MATIERES_PREMIERES, by = "MATIERES_PREMIERES") %>%
  left_join(MONNAIE, by = "MONNAIE") %>%
  month_to_date %>%
  ggplot + theme_minimal() + xlab("") + ylab("Pétrole brut  Brent (Londres) – par baril") +
  geom_line(aes(x = date, y = OBS_VALUE, color = Monnaie)) +
  scale_x_date(breaks = seq(1990, 2100, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = seq(0, 200, 10)) +
  theme(legend.position = c(0.3, 0.9),
        legend.title = element_blank())

Log

Tous

Code
`IPPMP-NF` %>%
  filter(INDICATEUR == "CIMP",
         MATIERES_PREMIERES == "41") %>%
  left_join(MATIERES_PREMIERES, by = "MATIERES_PREMIERES") %>%
  left_join(MONNAIE, by = "MONNAIE") %>%
  month_to_date %>%
  ggplot + theme_minimal() + xlab("") + ylab("Pétrole brut  Brent (Londres) – par baril") +
  geom_line(aes(x = date, y = OBS_VALUE, color = Monnaie)) +
  scale_x_date(breaks = seq(1990, 2100, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_log10(breaks = seq(0, 200, 10)) +
  theme(legend.position = c(0.3, 0.9),
        legend.title = element_blank())

2004-

Code
`IPPMP-NF` %>%
  filter(INDICATEUR == "CIMP",
         MATIERES_PREMIERES == "41") %>%
  left_join(MATIERES_PREMIERES, by = "MATIERES_PREMIERES") %>%
  left_join(MONNAIE, by = "MONNAIE") %>%
  month_to_date %>%
  filter(date >= as.Date("2004-01-01")) %>%
  ggplot + theme_minimal() + xlab("") + ylab("Pétrole brut  Brent (Londres) – par baril") +
  geom_line(aes(x = date, y = OBS_VALUE, color = Monnaie)) +
  scale_x_date(breaks = seq(1990, 2100, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_log10(breaks = seq(0, 200, 10)) +
  theme(legend.position = c(0.3, 0.2),
        legend.title = element_blank())

2010-

Code
`IPPMP-NF` %>%
  filter(INDICATEUR == "CIMP",
         MATIERES_PREMIERES == "41") %>%
  left_join(MATIERES_PREMIERES, by = "MATIERES_PREMIERES") %>%
  left_join(MONNAIE, by = "MONNAIE") %>%
  month_to_date %>%
  filter(date >= as.Date("2004-01-01")) %>%
  ggplot + theme_minimal() + xlab("") + ylab("Pétrole brut  Brent (Londres) – par baril") +
  geom_line(aes(x = date, y = OBS_VALUE, color = Monnaie)) +
  scale_x_date(breaks = seq(1990, 2100, 1) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_log10(breaks = seq(0, 200, 10)) +
  theme(legend.position = c(0.3, 0.2),
        legend.title = element_blank(),
        axis.text.x = element_text(angle = 45, vjust = 1, hjust = 1))

2 years

Code
`IPPMP-NF` %>%
  filter(INDICATEUR == "CIMP",
         MATIERES_PREMIERES == "41") %>%
  left_join(MATIERES_PREMIERES, by = "MATIERES_PREMIERES") %>%
  left_join(MONNAIE, by = "MONNAIE") %>%
  month_to_date %>%
  filter(date >= Sys.Date() - years(2)) %>%
  ggplot + theme_minimal() + xlab("") + ylab("Pétrole brut  Brent (Londres) – par baril") +
  geom_line(aes(x = date, y = OBS_VALUE, color = Monnaie)) +
  scale_x_date(breaks = "2 months",
               labels = date_format("%b %Y")) +
  scale_y_log10(breaks = seq(0, 200, 10)) +
  theme(legend.position = c(0.3, 0.2),
        legend.title = element_blank(),
        axis.text.x = element_text(angle = 45, vjust = 1, hjust = 1)) +
  geom_text(aes(x = date, y = OBS_VALUE, label = round(OBS_VALUE, 1), color = Monnaie), 
                  fontface ="plain", size = 3)