Indice de la production industrielle

Data - INSEE

Author

François Geerolf

Info

source dataset Title .html .rData
insee IPI-2015 Indice de la production industrielle 2025-10-10 2025-10-09
insee IPI-2021 Indice de la production industrielle 2025-10-10 2025-09-09

Info

  • La nomenclature agrégée - NA, 2008. html

Données sur l’industrie

Code 
industrie %>%
  arrange(-(dataset == "IPI-2015")) %>%
  source_dataset_file_updates()
source dataset Title .html .rData
eurostat mar_mg_am_cvh Country level - volume (in TEUs) of containers handled in main ports, by loading status - mar_mg_am_cvh 2025-10-10 2025-10-10
eurostat namq_10_a10 Gross value added and income A*10 industry breakdowns 2025-10-10 2025-10-09
insee CNA-2014-EMPLOI Emploi intérieur, durée effective travaillée et productivité horaire 2025-10-10 2025-10-09
insee CNT-2014-CB Comptes des branches 2025-10-10 2025-10-09
insee CNT-2014-OPERATIONS Opérations sur biens et services 2025-10-10 2025-10-09
insee ENQ-CONJ-ACT-IND Conjoncture dans l’industrie 2025-10-10 2025-10-09
insee ICA-2015-IND-CONS Indices de chiffre d'affaires dans l'industrie et la construction 2025-10-10 2025-10-09
insee IPI-2021 Indice de la production industrielle 2025-10-10 2025-09-09
insee IPPI-2015 Indices de prix de production et d'importation dans l'industrie 2025-10-10 2025-10-10
insee TCRED-EMPLOI-SALARIE-TRIM Estimations d'emploi salarié par secteur d'activité et par département 2025-10-10 2025-10-10
insee t_5407 5.407 – Solde extérieur de biens et de services par produit à prix courants (En milliards d'euros) - t_5407 2025-10-10 2021-08-01
oecd ALFS_EMP Employment by activities and status (ALFS) 2024-04-16 2025-05-24
oecd SNA_TABLE3 Population and employment by main activity 2024-09-15 2025-05-24

LAST_UPDATE

Code 
`IPI-2015` %>%
  group_by(LAST_UPDATE) %>%
  summarise(Nobs = n()) %>%
  arrange(desc(LAST_UPDATE)) %>%
  print_table_conditional()
LAST_UPDATE Nobs
2024-02-02 305360
2023-02-03 1650

LAST_COMPILE

LAST_COMPILE
2025-10-11

Last

Code 
`IPI-2015` %>%
  group_by(TIME_PERIOD) %>%
  summarise(Nobs = n()) %>%
  arrange(desc(TIME_PERIOD)) %>%
  head(1) %>%
  print_table_conditional()
TIME_PERIOD Nobs
2023-12 734

Exemples

  • En octobre 2022, la production manufacturière baisse de 2,0 %. html / pdf

  • INSEE Méthodes n°133. pdf / html

CORRECTION

Code 
`IPI-2015` %>%
  left_join(CORRECTION, by = "CORRECTION") %>%
  group_by(CORRECTION, Correction) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  print_table_conditional()
CORRECTION Correction Nobs
BRUT Non corrigé 159195
CVS-CJO Corrigé des variations saisonnières et du nombre de jours ouvrables 147815

NAF2

Tous

Code 
`IPI-2015` %>%
  left_join(NAF2, by = "NAF2") %>%
  group_by(NAF2, Naf2) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  print_table_conditional()

A10

Code 
`IPI-2015` %>%
  filter(grepl("A10", NAF2)) %>%
  left_join(NAF2, by = "NAF2") %>%
  group_by(NAF2, Naf2) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  print_table_conditional()
NAF2 Naf2 Nobs
A10-CZ A10-CZ - Industrie manufacturière 1653
A10-BE A10-BE - Industrie manufacturière, industries extractives et autres 850
A10-FZ A10-FZ - Construction 34

A17

Code 
`IPI-2015` %>%
  filter(grepl("A17", NAF2)) %>%
  left_join(NAF2, by = "NAF2") %>%
  group_by(NAF2, Naf2) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  print_table_conditional()
NAF2 Naf2 Nobs
A17-C1 A17-C1 - Fabrication de denrées alimentaires, de boissons et de produits à base de tabac 850
A17-C2 A17-C2 - Cokéfaction et raffinage 850
A17-C3 A17-C3 - Fabrication d'équipements électriques, électroniques, informatiques ; fabrication de machines 850
A17-C4 A17-C4 - Fabrication de matériels de transport 850
A17-C5 A17-C5 - Fabrication d'autres produits industriels 850
A17-DE A17-DE - Industries extractives, énergie, eau, gestion des déchets et dépollution 850

A38

Code 
`IPI-2015` %>%
  filter(grepl("A38", NAF2)) %>%
  left_join(NAF2, by = "NAF2") %>%
  group_by(NAF2, Naf2) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  print_table_conditional()
NAF2 Naf2 Nobs
A38-BZ A38-BZ - Industries extractives 850
A38-CA A38-CA - Fabrication de denrées alimentaires, de boissons et de produits à base de tabac 850
A38-CB A38-CB - Fabrication de textiles, industries de l'habillement, industrie du cuir et de la chaussure 850
A38-CC A38-CC - Travail du bois, industries du papier et imprimerie 850
A38-CD A38-CD - Cokéfaction et raffinage 850
A38-CE A38-CE - Industrie chimique 850
A38-CF A38-CF - Industrie pharmaceutique 850
A38-CG A38-CG - Fabrication de produits en caoutchouc et en plastique ainsi que d'autres produits minéraux non métalliques 850
A38-CH A38-CH - Métallurgie et fabrication de produits métalliques à l'exception des machines et des équipements 850
A38-CI A38-CI - Fabrication de produits informatiques, électroniques et optiques 850
A38-CJ A38-CJ - Fabrication d'équipements électriques 850
A38-CK A38-CK - Fabrication de machines et équipements n.c.a. 850
A38-CL A38-CL - Fabrication de matériels de transport 850
A38-CM A38-CM - Autres industries manufacturières ; réparation et installation de machines et d'équipements 850
A38-DZ A38-DZ - Production et distribution d'électricité, de gaz, de vapeur et d'air conditionné 850
A38-EZ A38-EZ - Production et distribution d'eau ; assainissement, gestion des déchets et dépollution 850

A88

Code 
`IPI-2015` %>%
  filter(nchar(NAF2) == 2) %>%
  left_join(NAF2, by = "NAF2") %>%
  group_by(NAF2, Naf2) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  print_table_conditional()
NAF2 Naf2 Nobs
SO Sans objet 8141
06 06 - Extraction d'hydrocarbures 850
08 08 - Autres industries extractives 850
10 10 - Industries alimentaires 850
11 11 - Fabrication de boissons 850
12 12 - Fabrication de produits à base de tabac 850
13 13 - Fabrication de textiles 850
14 14 - Industrie de l'habillement 850
15 15 - Industrie du cuir et de la chaussure 850
16 16 - Travail du bois et fabrication d'articles en bois et en liège, à l'exception des meubles ; fabrication d'articles en vannerie et sparterie 850
17 17 - Industrie du papier et du carton 850
18 18 - Imprimerie et reproduction d'enregistrements 850
19 19 - Cokéfaction et raffinage 850
20 20 - Industrie chimique 850
21 21 - Industrie pharmaceutique 850
22 22 - Fabrication de produits en caoutchouc et en plastique 850
23 23 - Fabrication d'autres produits minéraux non métalliques 850
24 24 - Métallurgie 850
25 25 - Fabrication de produits métalliques, à l'exception des machines et des équipements 850
26 26 - Fabrication de produits informatiques, électroniques et optiques 850
27 27 - Fabrication d'équipements électriques 850
28 28 - Fabrication de machines et équipements n.c.a. 850
29 29 - Industrie automobile 850
30 30 - Fabrication d'autres matériels de transport 850
31 31 - Fabrication de meubles 850
32 32 - Autres industries manufacturières 850
33 33 - Réparation et installation de machines et d'équipements 850
35 35 - Production et distribution d'électricité, de gaz, de vapeur et d'air conditionné 850
36 36 - Captage, traitement et distribution d'eau 850

INDICATEUR

Code 
`IPI-2015` %>%
  left_join(INDICATEUR, by = "INDICATEUR") %>%
  group_by(INDICATEUR, Indicateur) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  print_table_conditional()
INDICATEUR Indicateur Nobs
IPI Indice de la production industrielle 294827
IPI_MOYENNE_ANNUELLE Moyenne annuelle de l'indice de la production industrielle 12183

FREQ

Code 
`IPI-2015` %>%
  left_join(FREQ, by = "FREQ") %>%
  group_by(FREQ, Freq) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  print_table_conditional()
FREQ Freq Nobs
M Monthly 294827
A Annual 12183

NATURE

Code 
`IPI-2015` %>%
  left_join(NATURE, by = "NATURE") %>%
  group_by(NATURE, Nature) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  print_table_conditional()
NATURE Nature Nobs
INDICE Indice 294024
MOYENNE_ANNUELLE Moyenne annuelle 12183
VARIATIONS_M Variations mensuelles 407
GLISSEMENT_ANNUEL Glissement annuel 396

TITLE_FR

Code 
`IPI-2015` %>%
  group_by(IDBANK, TITLE_FR) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  print_table_conditional()

TIME_PERIOD: 1990-

Code 
`IPI-2015` %>%
  group_by(TIME_PERIOD) %>%
  summarise(Nobs = n()) %>%
  arrange(desc(TIME_PERIOD)) %>%
  print_table_conditional()

A10, A17

CZ, DE

All

Code 
`IPI-2015` %>%
  filter(NAF2 %in% c("A10-CZ", "A17-DE"),
         CORRECTION == "CVS-CJO",
         NATURE == "INDICE") %>%
  left_join(NAF2, by = "NAF2") %>%
  select_if(function(col) length(unique(col)) > 1) %>%
  month_to_date %>%
  group_by(Naf2) %>%
  mutate(OBS_VALUE = 100*OBS_VALUE/OBS_VALUE[date == as.Date("1990-01-01")]) %>%
  ggplot() + ylab("Indice de Production Industrielle (1990 = 100)") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = OBS_VALUE, color = Naf2)) +
  
  scale_x_date(breaks = seq(1920, 2100, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = c(0.45, 0.2),
        legend.title = element_blank()) +
  scale_y_log10(breaks = seq(-60, 300, 10))

2010-

Code 
`IPI-2015` %>%
  filter(NAF2 %in% c("A10-CZ", "A17-DE"),
         CORRECTION == "CVS-CJO",
         NATURE == "INDICE") %>%
  left_join(NAF2, by = "NAF2") %>%
  select_if(function(col) length(unique(col)) > 1) %>%
  month_to_date %>%
  filter(date >= as.Date("2010-01-01")) %>%
  group_by(Naf2) %>%
  mutate(OBS_VALUE = 100*OBS_VALUE/OBS_VALUE[date == as.Date("2010-01-01")]) %>%
  ggplot() + ylab("Indice de Production Industrielle (2010 = 100)") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = OBS_VALUE, color = Naf2)) +
  
  scale_x_date(breaks = seq(1920, 2100, 1) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = c(0.45, 0.2),
        legend.title = element_blank()) +
  scale_y_log10(breaks = seq(-60, 300, 10))

2017-04-

Code 
`IPI-2015` %>%
  filter(NAF2 %in% c("A17-DE", "A10-CZ", "A10-BE"),
         CORRECTION == "CVS-CJO",
         NATURE == "INDICE") %>%
  left_join(NAF2, by = "NAF2") %>%
  select_if(function(col) length(unique(col)) > 1) %>%
  month_to_date %>%
  filter(date >= as.Date("2017-04-01")) %>%
  group_by(Naf2) %>%
  mutate(OBS_VALUE = 100*OBS_VALUE/OBS_VALUE[date == as.Date("2020-02-01")]) %>%
  ggplot() + ylab("Indice de Production Industrielle (Février 2020 = 100)") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = OBS_VALUE, color = Naf2))  +
  geom_label_repel(data = . %>%
              filter(date == as.Date("2023-12-01")), aes(x = date, y = OBS_VALUE, label = round(OBS_VALUE, 1), color = Naf2)) +
  geom_hline(yintercept = 100, linetype = "dashed") +
  
  scale_x_date(breaks = seq(1920, 2100, 1) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = c(0.45, 0.2),
        legend.title = element_blank()) +
  scale_y_log10(breaks = seq(-60, 300, 5))

2019-T1

Code 
`IPI-2015` %>%
  filter(NAF2 %in% c("A17-DE", "A10-CZ", "A10-BE"),
         CORRECTION == "CVS-CJO",
         NATURE == "INDICE") %>%
  left_join(NAF2, by = "NAF2") %>%
  select_if(function(col) length(unique(col)) > 1) %>%
  month_to_date %>%
  filter(date >= as.Date("2019-01-01")) %>%
  group_by(Naf2) %>%
  mutate(OBS_VALUE = 100*OBS_VALUE/OBS_VALUE[date == as.Date("2019-01-01")]) %>%
  ggplot() + ylab("Indice de Production Industrielle (Janvier 2019 = 100)") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = OBS_VALUE, color = Naf2))  +
  geom_label_repel(data = . %>%
              filter(date == max(date)), aes(x = date, y = OBS_VALUE, label = round(OBS_VALUE, 1), color = Naf2)) +
  geom_hline(yintercept = 100, linetype = "dashed") +
  
  scale_x_date(breaks = seq(1920, 2100, 1) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = c(0.45, 0.2),
        legend.title = element_blank()) +
  scale_y_log10(breaks = seq(-60, 300, 5))

C1, C2, C3

Code 
`IPI-2015` %>%
  filter(NAF2 %in% c("A17-C1", "A17-C2", "A17-C3"),
         CORRECTION == "CVS-CJO",
         NATURE == "INDICE") %>%
  left_join(NAF2, by = "NAF2") %>%
  select_if(function(col) length(unique(col)) > 1) %>%
  month_to_date %>%
  group_by(Naf2) %>%
  mutate(OBS_VALUE = 100*OBS_VALUE/OBS_VALUE[date == as.Date("1990-01-01")]) %>%
  ggplot() + ylab("Indice de Production Industrielle") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = OBS_VALUE, color = Naf2)) +
  
  scale_x_date(breaks = seq(1920, 2100, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = c(0.45, 0.2),
        legend.title = element_blank()) +
  scale_y_log10(breaks = seq(-60, 300, 10))

C4, C5

Code 
`IPI-2015` %>%
  filter(NAF2 %in% c("A17-C4", "A17-C5"),
         CORRECTION == "CVS-CJO",
         NATURE == "INDICE") %>%
  left_join(NAF2, by = "NAF2") %>%
  select_if(function(col) length(unique(col)) > 1) %>%
  month_to_date %>%
  group_by(Naf2) %>%
  mutate(OBS_VALUE = 100*OBS_VALUE/OBS_VALUE[date == as.Date("1990-01-01")]) %>%
  ggplot() + ylab("Indice de Production Industrielle") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = OBS_VALUE, color = Naf2)) +
  
  scale_x_date(breaks = seq(1920, 2100, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = c(0.45, 0.2),
        legend.title = element_blank()) +
  scale_y_log10(breaks = seq(-60, 300, 10))

A38

BZ, DZ, EZ

Code 
`IPI-2015` %>%
  filter(NAF2 %in% c("A38-BZ", "A38-DZ", "A38-EZ"),
         CORRECTION == "CVS-CJO",
         NATURE == "INDICE") %>%
  left_join(NAF2, by = "NAF2") %>%
  select_if(function(col) length(unique(col)) > 1) %>%
  month_to_date %>%
  group_by(Naf2) %>%
  mutate(OBS_VALUE = 100*OBS_VALUE/OBS_VALUE[date == as.Date("1990-01-01")]) %>%
  ggplot() + ylab("Indice de Production Industrielle") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = OBS_VALUE, color = Naf2)) +
  
  scale_x_date(breaks = seq(1920, 2100, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = c(0.45, 0.2),
        legend.title = element_blank()) +
  scale_y_log10(breaks = seq(-60, 300, 10))

CA, CB, CC

Code 
`IPI-2015` %>%
  filter(NAF2 %in% c("A38-CA", "A38-CB", "A38-CC"),
         CORRECTION == "CVS-CJO",
         NATURE == "INDICE") %>%
  left_join(NAF2, by = "NAF2") %>%
  select_if(function(col) length(unique(col)) > 1) %>%
  month_to_date %>%
  group_by(Naf2) %>%
  mutate(OBS_VALUE = 100*OBS_VALUE/OBS_VALUE[date == as.Date("1990-01-01")]) %>%
  ggplot() + ylab("Indice de Production Industrielle") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = OBS_VALUE, color = Naf2)) +
  
  scale_x_date(breaks = seq(1920, 2100, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = c(0.45, 0.2),
        legend.title = element_blank()) +
  scale_y_log10(breaks = seq(-60, 300, 10))

CD, CE, CF

All

Code 
`IPI-2015` %>%
  filter(NAF2 %in% c("A38-CD", "A38-CE", "A38-CF"),
         CORRECTION == "CVS-CJO",
         NATURE == "INDICE") %>%
  left_join(NAF2, by = "NAF2") %>%
  select_if(function(col) length(unique(col)) > 1) %>%
  month_to_date %>%
  group_by(Naf2) %>%
  mutate(OBS_VALUE = 100*OBS_VALUE/OBS_VALUE[date == as.Date("1990-01-01")]) %>%
  ggplot() + ylab("Indice de Production Industrielle") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = OBS_VALUE, color = Naf2)) +
  
  scale_x_date(breaks = seq(1920, 2100, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = c(0.25, 0.2),
        legend.title = element_blank()) +
  scale_y_log10(breaks = seq(-60, 600, 10))

2010-

Code 
`IPI-2015` %>%
  filter(NAF2 %in% c("A38-CD", "A38-CE", "A38-CF"),
         CORRECTION == "CVS-CJO",
         NATURE == "INDICE") %>%
  left_join(NAF2, by = "NAF2") %>%
  select_if(function(col) length(unique(col)) > 1) %>%
  month_to_date %>%
  filter(date >= as.Date("2010-01-01")) %>%
  group_by(Naf2) %>%
  mutate(OBS_VALUE = 100*OBS_VALUE/OBS_VALUE[date == as.Date("2010-01-01")]) %>%
  ggplot() + ylab("Indice de Production Industrielle") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = OBS_VALUE, color = Naf2)) +
  
  scale_x_date(breaks = seq(1920, 2100, 1) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = c(0.25, 0.2),
        legend.title = element_blank()) +
  scale_y_log10(breaks = seq(-60, 600, 10))

2017-

Code 
`IPI-2015` %>%
  filter(NAF2 %in% c("A38-CD", "A38-CE", "A38-CF"),
         CORRECTION == "CVS-CJO",
         NATURE == "INDICE") %>%
  left_join(NAF2, by = "NAF2") %>%
  select_if(function(col) length(unique(col)) > 1) %>%
  month_to_date %>%
  filter(date >= as.Date("2017-01-01")) %>%
  group_by(Naf2) %>%
  mutate(OBS_VALUE = 100*OBS_VALUE/OBS_VALUE[date == as.Date("2017-01-01")]) %>%
  ggplot() + ylab("Indice de Production Industrielle") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = OBS_VALUE, color = Naf2)) +
  
  scale_x_date(breaks = seq(1920, 2100, 1) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = c(0.25, 0.2),
        legend.title = element_blank()) +
  scale_y_log10(breaks = seq(-60, 600, 10))

CG, CH, CI

All

Code 
`IPI-2015` %>%
  filter(NAF2 %in% c("A38-CG", "A38-CH", "A38-CI"),
         CORRECTION == "CVS-CJO",
         NATURE == "INDICE") %>%
  left_join(NAF2, by = "NAF2") %>%
  select_if(function(col) length(unique(col)) > 1) %>%
  month_to_date %>%
  group_by(Naf2) %>%
  mutate(OBS_VALUE = 100*OBS_VALUE/OBS_VALUE[date == as.Date("1990-01-01")]) %>%
  ggplot() + ylab("Indice de Production Industrielle") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = OBS_VALUE, color = Naf2)) +
  
  scale_x_date(breaks = seq(1920, 2100, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = c(0.5, 0.2),
        legend.title = element_blank()) +
  scale_y_log10(breaks = seq(-60, 300, 10))

2017-

Code 
`IPI-2015` %>%
  filter(NAF2 %in% c("A38-CG", "A38-CH", "A38-CI"),
         CORRECTION == "CVS-CJO",
         NATURE == "INDICE") %>%
  left_join(NAF2, by = "NAF2") %>%
  select_if(function(col) length(unique(col)) > 1) %>%
  month_to_date %>%
  filter(date >= as.Date("2017-01-01")) %>%
  group_by(Naf2) %>%
  mutate(OBS_VALUE = 100*OBS_VALUE/OBS_VALUE[date == as.Date("2017-01-01")]) %>%
  ggplot() + ylab("Indice de Production Industrielle") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = OBS_VALUE, color = Naf2)) +
  
  scale_x_date(breaks = seq(1920, 2100, 1) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = c(0.5, 0.2),
        legend.title = element_blank()) +
  scale_y_log10(breaks = seq(-60, 300, 10))

CJ, CK, CM

Code 
`IPI-2015` %>%
  filter(NAF2 %in% c("A38-CJ", "A38-CK", "A38-CM"),
         CORRECTION == "CVS-CJO",
         NATURE == "INDICE") %>%
  left_join(NAF2, by = "NAF2") %>%
  select_if(function(col) length(unique(col)) > 1) %>%
  month_to_date %>%
  group_by(Naf2) %>%
  mutate(OBS_VALUE = 100*OBS_VALUE/OBS_VALUE[date == as.Date("1990-01-01")]) %>%
  ggplot() + ylab("Indice de Production Industrielle") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = OBS_VALUE, color = Naf2)) +
  
  scale_x_date(breaks = seq(1920, 2100, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = c(0.5, 0.2),
        legend.title = element_blank()) +
  scale_y_log10(breaks = seq(-60, 300, 10))

CL, CL1, CL2

Code 
`IPI-2015` %>%
  filter(NAF2 %in% c("A38-CL", "CL1", "CL2"),
         CORRECTION == "CVS-CJO",
         NATURE == "INDICE") %>%
  left_join(NAF2, by = "NAF2") %>%
  select_if(function(col) length(unique(col)) > 1) %>%
  month_to_date %>%
  group_by(Naf2) %>%
  mutate(OBS_VALUE = 100*OBS_VALUE/OBS_VALUE[date == as.Date("1990-01-01")]) %>%
  ggplot() + ylab("Indice de Production Industrielle") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = OBS_VALUE, color = Naf2)) +
  
  scale_x_date(breaks = seq(1920, 2100, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = c(0.5, 0.2),
        legend.title = element_blank()) +
  scale_y_log10(breaks = seq(-60, 300, 10))

A88 (2-digit NAF)

06, 08

Code 
`IPI-2015` %>%
  filter(NAF2 %in% c("06", "08"),
         CORRECTION == "CVS-CJO",
         NATURE == "INDICE") %>%
  left_join(NAF2, by = "NAF2") %>%
  select_if(function(col) length(unique(col)) > 1) %>%
  month_to_date %>%
  group_by(Naf2) %>%
  mutate(OBS_VALUE = 100*OBS_VALUE/OBS_VALUE[date == as.Date("1990-01-01")]) %>%
  ggplot() + ylab("Indice de Production Industrielle") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = OBS_VALUE, color = Naf2)) +
  
  scale_x_date(breaks = seq(1920, 2100, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = c(0.5, 0.2),
        legend.title = element_blank()) +
  scale_y_log10(breaks = seq(-60, 300, 10))

10, 11

Code 
`IPI-2015` %>%
  filter(NAF2 %in% c("10", "11"),
         CORRECTION == "CVS-CJO",
         NATURE == "INDICE") %>%
  left_join(NAF2, by = "NAF2") %>%
  select_if(function(col) length(unique(col)) > 1) %>%
  month_to_date %>%
  group_by(Naf2) %>%
  mutate(OBS_VALUE = 100*OBS_VALUE/OBS_VALUE[date == as.Date("1990-01-01")]) %>%
  ggplot() + ylab("Indice de Production Industrielle") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = OBS_VALUE, color = Naf2)) +
  
  scale_x_date(breaks = seq(1920, 2100, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = c(0.5, 0.2),
        legend.title = element_blank()) +
  scale_y_log10(breaks = seq(-60, 300, 10))

10, 11, 12

Code 
`IPI-2015` %>%
  filter(NAF2 %in% c("10", "11", "12"),
         CORRECTION == "CVS-CJO",
         NATURE == "INDICE") %>%
  left_join(NAF2, by = "NAF2") %>%
  select_if(function(col) length(unique(col)) > 1) %>%
  month_to_date %>%
  group_by(Naf2) %>%
  mutate(OBS_VALUE = 100*OBS_VALUE/OBS_VALUE[date == as.Date("1990-01-01")]) %>%
  ggplot() + ylab("Indice de Production Industrielle") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = OBS_VALUE, color = Naf2)) +
  
  scale_x_date(breaks = seq(1920, 2100, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = c(0.5, 0.2),
        legend.title = element_blank()) +
  scale_y_log10(breaks = seq(-60, 300, 10))

13, 14, 15

Code 
`IPI-2015` %>%
  filter(NAF2 %in% c("13", "14", "15"),
         CORRECTION == "CVS-CJO",
         NATURE == "INDICE") %>%
  left_join(NAF2, by = "NAF2") %>%
  select_if(function(col) length(unique(col)) > 1) %>%
  month_to_date %>%
  group_by(Naf2) %>%
  mutate(OBS_VALUE = 100*OBS_VALUE/OBS_VALUE[date == as.Date("1990-01-01")]) %>%
  ggplot() + ylab("Indice de Production Industrielle") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = OBS_VALUE, color = Naf2)) +
  
  scale_x_date(breaks = seq(1920, 2100, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = c(0.3, 0.2),
        legend.title = element_blank()) +
  scale_y_log10(breaks = seq(-60, 300, 10))

16, 17, 18

Code 
`IPI-2015` %>%
  filter(NAF2 %in% c("16", "17", "18"),
         CORRECTION == "CVS-CJO",
         NATURE == "INDICE") %>%
  left_join(NAF2, by = "NAF2") %>%
  select_if(function(col) length(unique(col)) > 1) %>%
  month_to_date %>%
  group_by(Naf2) %>%
  mutate(OBS_VALUE = 100*OBS_VALUE/OBS_VALUE[date == as.Date("1990-01-01")]) %>%
  ggplot() + ylab("Indice de Production Industrielle") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = OBS_VALUE, color = Naf2)) +
  
  scale_x_date(breaks = seq(1920, 2100, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = c(0.6, 0.2),
        legend.title = element_blank()) +
  scale_y_log10(breaks = seq(-60, 300, 10))

19, 20, 21

Code 
`IPI-2015` %>%
  filter(NAF2 %in% c("19", "20", "21"),
         CORRECTION == "CVS-CJO",
         NATURE == "INDICE") %>%
  left_join(NAF2, by = "NAF2") %>%
  select_if(function(col) length(unique(col)) > 1) %>%
  month_to_date %>%
  group_by(Naf2) %>%
  mutate(OBS_VALUE = 100*OBS_VALUE/OBS_VALUE[date == as.Date("1990-01-01")]) %>%
  ggplot() + ylab("Indice de Production Industrielle") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = OBS_VALUE, color = Naf2)) +
  
  scale_x_date(breaks = seq(1920, 2100, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = c(0.3, 0.2),
        legend.title = element_blank()) +
  scale_y_log10(breaks = seq(0, 600, 50))

22, 23, 24

Code 
`IPI-2015` %>%
  filter(NAF2 %in% c("22", "23", "24"),
         CORRECTION == "CVS-CJO",
         NATURE == "INDICE") %>%
  left_join(NAF2, by = "NAF2") %>%
  select_if(function(col) length(unique(col)) > 1) %>%
  month_to_date %>%
  group_by(Naf2) %>%
  mutate(OBS_VALUE = 100*OBS_VALUE/OBS_VALUE[date == as.Date("1990-01-01")]) %>%
  ggplot() + ylab("Indice de Production Industrielle") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = OBS_VALUE, color = Naf2)) +
  
  scale_x_date(breaks = seq(1920, 2100, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = c(0.3, 0.2),
        legend.title = element_blank()) +
  scale_y_log10(breaks = seq(0, 600, 10))

25, 26, 27

Code 
`IPI-2015` %>%
  filter(NAF2 %in% c("22", "26", "27"),
         CORRECTION == "CVS-CJO",
         NATURE == "INDICE") %>%
  left_join(NAF2, by = "NAF2") %>%
  select_if(function(col) length(unique(col)) > 1) %>%
  month_to_date %>%
  group_by(Naf2) %>%
  mutate(OBS_VALUE = 100*OBS_VALUE/OBS_VALUE[date == as.Date("1990-01-01")]) %>%
  ggplot() + ylab("Indice de Production Industrielle") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = OBS_VALUE, color = Naf2)) +
  
  scale_x_date(breaks = seq(1920, 2100, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = c(0.4, 0.2),
        legend.title = element_blank()) +
  scale_y_log10(breaks = seq(0, 600, 10))

28, 29, 30

Code 
`IPI-2015` %>%
  filter(NAF2 %in% c("28", "29", "30"),
         CORRECTION == "CVS-CJO",
         NATURE == "INDICE") %>%
  left_join(NAF2, by = "NAF2") %>%
  select_if(function(col) length(unique(col)) > 1) %>%
  month_to_date %>%
  group_by(Naf2) %>%
  mutate(OBS_VALUE = 100*OBS_VALUE/OBS_VALUE[date == as.Date("1990-01-01")]) %>%
  ggplot() + ylab("Indice de Production Industrielle") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = OBS_VALUE, color = Naf2)) +
  
  scale_x_date(breaks = seq(1920, 2100, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = c(0.4, 0.2),
        legend.title = element_blank()) +
  scale_y_log10(breaks = seq(0, 600, 10))

31, 32, 33

Code 
`IPI-2015` %>%
  filter(NAF2 %in% c("31", "32", "33"),
         CORRECTION == "CVS-CJO",
         NATURE == "INDICE") %>%
  left_join(NAF2, by = "NAF2") %>%
  select_if(function(col) length(unique(col)) > 1) %>%
  month_to_date %>%
  group_by(Naf2) %>%
  mutate(OBS_VALUE = 100*OBS_VALUE/OBS_VALUE[date == as.Date("1990-01-01")]) %>%
  ggplot() + ylab("Indice de Production Industrielle") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = OBS_VALUE, color = Naf2)) +
  
  scale_x_date(breaks = seq(1920, 2100, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = c(0.4, 0.2),
        legend.title = element_blank()) +
  scale_y_log10(breaks = seq(0, 600, 10))

35, 36

Code 
`IPI-2015` %>%
  filter(NAF2 %in% c("35", "36"),
         CORRECTION == "CVS-CJO",
         NATURE == "INDICE") %>%
  left_join(NAF2, by = "NAF2") %>%
  select_if(function(col) length(unique(col)) > 1) %>%
  month_to_date %>%
  group_by(Naf2) %>%
  mutate(OBS_VALUE = 100*OBS_VALUE/OBS_VALUE[date == as.Date("1990-01-01")]) %>%
  ggplot() + ylab("Indice de Production Industrielle") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = OBS_VALUE, color = Naf2)) +
  
  scale_x_date(breaks = seq(1920, 2100, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = c(0.6, 0.2),
        legend.title = element_blank()) +
  scale_y_log10(breaks = seq(0, 600, 10))

Electricité

Tous les postes

Code 
`IPI-2015` %>%
  filter(NAF2 %in% c("35", "35-11", "A10-BE", "A17-DE", "A38-DZ"),
         CORRECTION == "CVS-CJO",
         NATURE == "INDICE") %>%
  left_join(NAF2, by = "NAF2") %>%
  select_if(function(col) length(unique(col)) > 1) %>%
  month_to_date %>%
  group_by(Naf2) %>%
  mutate(OBS_VALUE = 100*OBS_VALUE/OBS_VALUE[date == as.Date("1990-01-01")]) %>%
  ggplot() + ylab("Indice de Production Industrielle") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = OBS_VALUE, color = Naf2)) +
  
  scale_x_date(breaks = seq(1920, 2100, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = c(0.6, 0.2),
        legend.title = element_blank()) +
  scale_y_log10(breaks = seq(0, 600, 10))

2017-04-

Code 
`IPI-2015` %>%
  filter(NAF2 %in% c("35-11", "A10-BE", "A17-DE", "A38-DZ"),
         CORRECTION == "CVS-CJO",
         NATURE == "INDICE") %>%
  left_join(NAF2, by = "NAF2") %>%
  select_if(function(col) length(unique(col)) > 1) %>%
  month_to_date %>%
  filter(date >= as.Date("2017-04-01")) %>%
  group_by(Naf2) %>%
  mutate(OBS_VALUE = 100*OBS_VALUE/OBS_VALUE[date == as.Date("2020-02-01")]) %>%
  ggplot() + ylab("Indice de Production Industrielle (Février 2020 = 100)") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = OBS_VALUE, color = Naf2))  +
  geom_text_repel(data = . %>%
              filter(date == as.Date("2023-12-01")), aes(x = date, y = OBS_VALUE, label = round(OBS_VALUE, 1))) +
  geom_hline(yintercept = 100, linetype = "dashed") +
  
  scale_x_date(breaks = seq(1920, 2100, 1) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = c(0.45, 0.2),
        legend.title = element_blank()) +
  scale_y_log10(breaks = seq(-60, 300, 5))