~/data/insee/

Info

source	dataset	.html	.RData
insee	IPI-2015	2024-05-30	2024-06-07

Info

La nomenclature agrégée - NA, 2008. html

Données sur l’industrie

industrie %>%
  arrange(-(dataset == "IPI-2015")) %>%
  source_dataset_title_file_updates()

source	dataset	.html	.RData
eurostat	mar_mg_am_cvh	2024-05-25	2024-05-25
eurostat	namq_10_a10	2024-05-25	2024-06-07
insee	CNA-2014-EMPLOI	2024-06-07	2024-06-07
insee	CNT-2014-CB	2024-06-07	2024-06-07
insee	CNT-2014-OPERATIONS	2024-06-07	2024-06-07
insee	ENQ-CONJ-ACT-IND	2024-06-08	2024-06-07
insee	ICA-2015-IND-CONS	2024-06-08	2024-06-07
insee	IPI-2021	2024-06-06	2024-06-06
insee	IPPI-2015	2024-05-30	2024-03-30
insee	t_5407	2024-05-30	2021-08-01
insee	TCRED-EMPLOI-SALARIE-TRIM	2024-05-30	2024-06-07
oecd	ALFS_EMP	2024-04-16	2024-05-12
oecd	SNA_TABLE3	2024-04-16	2024-04-16

LAST_UPDATE

`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
2024-06-08

Last

`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

`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

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

A10

`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

`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

`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

`IPI-2015` %>%
  filter(nchar(NAF2) == 2) %>%
  left_join(NAF2, by = "NAF2") %>%
  group_by(NAF2, Naf2) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  print_table_conditional()

INDICATEUR

`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

`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

`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

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

TIME_PERIOD: 1990-

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

A10, A17

CZ, DE

All

`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-

`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-

`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

`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

`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

`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

`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

`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

`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-

`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-

`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

`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-

`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

`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

`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

`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

`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

`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

`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

`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

`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

`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

`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

`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

`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

`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

`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-

`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))

Indice de la production industrielle

Data - INSEE

François Geerolf

Info

Info

Données sur l’industrie

LAST_UPDATE

LAST_COMPILE

Last

Exemples

CORRECTION

NAF2

Tous

A10

A17

A38

A88

INDICATEUR

FREQ

NATURE

TITLE_FR

TIME_PERIOD: 1990-

A10, A17

CZ, DE

All

2010-

2017-04-

2019-T1

C1, C2, C3

C4, C5

A38

BZ, DZ, EZ

CA, CB, CC

CD, CE, CF

All

2010-

2017-

CG, CH, CI

All

2017-

CJ, CK, CM

CL, CL1, CL2

A88 (2-digit NAF)

06, 08

10, 11

10, 11, 12

13, 14, 15

16, 17, 18

19, 20, 21

22, 23, 24

25, 26, 27

28, 29, 30

31, 32, 33

35, 36

Electricité

Tous les postes

2017-04-