Indice de la production industrielle

Data - INSEE

Info

source dataset .html .RData

insee

IPI-2021

2024-09-23 2024-09-23

Info

  • La nomenclature agrégée - NA, 2008. html

Données sur l’industrie

Code
industrie %>%
  arrange(-(dataset == "IPI-2021")) %>%
  source_dataset_file_updates()
source dataset .html .RData

eurostat

mar_mg_am_cvh

2024-09-19 2024-09-15

eurostat

namq_10_a10

2024-09-19 2024-09-22

insee

CNA-2014-EMPLOI

2024-06-07 2024-09-22

insee

CNT-2014-CB

2024-09-22 2024-09-22

insee

CNT-2014-OPERATIONS

2024-09-22 2024-09-22

insee

ENQ-CONJ-ACT-IND

2024-09-22 2024-09-22

insee

ICA-2015-IND-CONS

2024-09-22 2024-09-22

insee

IPI-2021

2024-09-23 2024-09-23

insee

IPPI-2015

2024-09-22 2024-09-22

insee

t_5407

2024-09-22 2021-08-01

insee

TCRED-EMPLOI-SALARIE-TRIM

2024-09-22 2024-09-22

oecd

ALFS_EMP

2024-04-16 2024-05-12

oecd

SNA_TABLE3

2024-09-15 2024-04-16

LAST_UPDATE

Code
`IPI-2021` %>%
  group_by(LAST_UPDATE) %>%
  summarise(Nobs = n()) %>%
  arrange(desc(LAST_UPDATE)) %>%
  print_table_conditional()
LAST_UPDATE Nobs
2024-09-06 307117

LAST_COMPILE

LAST_COMPILE
2024-09-23

Last

Code
`IPI-2021` %>%
  group_by(TIME_PERIOD) %>%
  summarise(Nobs = n()) %>%
  arrange(desc(TIME_PERIOD)) %>%
  head(1) %>%
  print_table_conditional()
TIME_PERIOD Nobs
2024-07 728

Exemples

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

  • INSEE Méthodes n°133. pdf / html

CORRECTION

Code
`IPI-2021` %>%
  left_join(CORRECTION, by = "CORRECTION") %>%
  group_by(CORRECTION, Correction) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  print_table_conditional()
CORRECTION Correction Nobs
BRUT Non corrigé 159315
CVS-CJO Corrigé des variations saisonnières et du nombre de jours ouvrables 147802

NAF2

Tous

Code
`IPI-2021` %>%
  left_join(NAF2, by = "NAF2") %>%
  group_by(NAF2, Naf2) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  print_table_conditional()

A10

Code
`IPI-2021` %>%
  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 1682
A10-BE A10-BE - Industrie manufacturière, industries extractives et autres 865
A10-FZ A10-FZ - Construction 35

A17

Code
`IPI-2021` %>%
  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 865
A17-C2 A17-C2 - Cokéfaction et raffinage 865
A17-C3 A17-C3 - Fabrication d'équipements électriques, électroniques, informatiques ; fabrication de machines 865
A17-C4 A17-C4 - Fabrication de matériels de transport 865
A17-C5 A17-C5 - Fabrication d'autres produits industriels 865
A17-DE A17-DE - Industries extractives, énergie, eau, gestion des déchets et dépollution 865

A38

Code
`IPI-2021` %>%
  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 865
A38-CA A38-CA - Fabrication de denrées alimentaires, de boissons et de produits à base de tabac 865
A38-CB A38-CB - Fabrication de textiles, industries de l'habillement, industrie du cuir et de la chaussure 865
A38-CC A38-CC - Travail du bois, industries du papier et imprimerie 865
A38-CD A38-CD - Cokéfaction et raffinage 865
A38-CE A38-CE - Industrie chimique 865
A38-CF A38-CF - Industrie pharmaceutique 865
A38-CG A38-CG - Fabrication de produits en caoutchouc et en plastique ainsi que d'autres produits minéraux non métalliques 865
A38-CH A38-CH - Métallurgie et fabrication de produits métalliques à l'exception des machines et des équipements 865
A38-CI A38-CI - Fabrication de produits informatiques, électroniques et optiques 865
A38-CJ A38-CJ - Fabrication d'équipements électriques 865
A38-CK A38-CK - Fabrication de machines et équipements n.c.a. 865
A38-CL A38-CL - Fabrication de matériels de transport 865
A38-CM A38-CM - Autres industries manufacturières ; réparation et installation de machines et d'équipements 865
A38-DZ A38-DZ - Production et distribution d'électricité, de gaz, de vapeur et d'air conditionné 865
A38-EZ A38-EZ - Production et distribution d'eau ; assainissement, gestion des déchets et dépollution 865

A88

Code
`IPI-2021` %>%
  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 6625
06 06 - Extraction d'hydrocarbures 865
08 08 - Autres industries extractives 865
10 10 - Industries alimentaires 865
11 11 - Fabrication de boissons 865
13 13 - Fabrication de textiles 865
14 14 - Industrie de l'habillement 865
15 15 - Industrie du cuir et de la chaussure 865
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 865
17 17 - Industrie du papier et du carton 865
18 18 - Imprimerie et reproduction d'enregistrements 865
19 19 - Cokéfaction et raffinage 865
20 20 - Industrie chimique 865
21 21 - Industrie pharmaceutique 865
22 22 - Fabrication de produits en caoutchouc et en plastique 865
23 23 - Fabrication d'autres produits minéraux non métalliques 865
24 24 - Métallurgie 865
25 25 - Fabrication de produits métalliques, à l'exception des machines et des équipements 865
26 26 - Fabrication de produits informatiques, électroniques et optiques 865
27 27 - Fabrication d'équipements électriques 865
28 28 - Fabrication de machines et équipements n.c.a. 865
29 29 - Industrie automobile 865
30 30 - Fabrication d'autres matériels de transport 865
31 31 - Fabrication de meubles 865
32 32 - Autres industries manufacturières 865
33 33 - Réparation et installation de machines et d'équipements 865
35 35 - Production et distribution d'électricité, de gaz, de vapeur et d'air conditionné 865
36 36 - Captage, traitement et distribution d'eau 865

INDICATEUR

Code
`IPI-2021` %>%
  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 294787
IPI_MOYENNE_ANNUELLE Moyenne annuelle de l'indice de la production industrielle 12330

FREQ

Code
`IPI-2021` %>%
  left_join(FREQ, by = "FREQ") %>%
  group_by(FREQ, Freq) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  print_table_conditional()
FREQ Freq Nobs
M Monthly 294787
A Annual 12330

NATURE

Code
`IPI-2021` %>%
  left_join(NATURE, by = "NATURE") %>%
  group_by(NATURE, Nature) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  print_table_conditional()
NATURE Nature Nobs
INDICE Indice 293970
MOYENNE_ANNUELLE Moyenne annuelle 12330
VARIATIONS_M Variations mensuelles 414
GLISSEMENT_ANNUEL Glissement annuel 403

TITLE_FR

Code
`IPI-2021` %>%
  group_by(IDBANK, TITLE_FR) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  print_table_conditional()

TIME_PERIOD: 1990-

Code
`IPI-2021` %>%
  group_by(TIME_PERIOD) %>%
  summarise(Nobs = n()) %>%
  arrange(desc(TIME_PERIOD)) %>%
  print_table_conditional()

A10, A17

CZ, BE

Tous

Code
`IPI-2021` %>%
  filter(NAF2 %in% c("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("1995-01-01")) %>%
  mutate(OBS_VALUE = ifelse(year(date) == 2020 & month(date) %in% c(3, 4, 5, 6), NA, OBS_VALUE)) %>%
  group_by(Naf2) %>%
  mutate(OBS_VALUE = 100*OBS_VALUE/OBS_VALUE[date == as.Date("2020-02-01")]) %>%
  ggplot() + ylab("Indice de Production Industrielle vs. Février 2020\nhors Mars-Juin 2020") + 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 = percent(OBS_VALUE/100-1, acc = .1), color = Naf2)) +
  geom_hline(yintercept = 100, linetype = "dashed") +
  
  scale_x_date(breaks = seq(1920, 2100, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = c(0.7, 0.9),
        legend.title = element_blank()) +
  scale_y_log10(breaks = seq(70, 110, 1),
                labels = percent(seq(70, 110, 1)/100 - 1, 1)) +
  geom_rect(data = data_frame(start = as.Date("2020-02-01"), 
                                end = as.Date("2020-07-01")), 
              aes(xmin = start, xmax = end, ymin = 0, ymax = +Inf), fill = viridis(4)[4], alpha = 0.2)

1995

Code
`IPI-2021` %>%
  filter(NAF2 %in% c("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("1995-01-01")) %>%
  mutate(OBS_VALUE = ifelse(year(date) == 2020 & month(date) %in% c(3, 4, 5, 6), NA, OBS_VALUE)) %>%
  group_by(Naf2) %>%
  mutate(OBS_VALUE = 100*OBS_VALUE/OBS_VALUE[date == as.Date("2020-02-01")]) %>%
  ggplot() + ylab("Indice de Production Industrielle vs. Février 2020\nhors Mars-Juin 2020") + 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 = percent(OBS_VALUE/100-1, acc = .1), color = Naf2)) +
  geom_hline(yintercept = 100, linetype = "dashed") +
  
  scale_x_date(breaks = seq(1920, 2100, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = c(0.7, 0.9),
        legend.title = element_blank()) +
  scale_y_log10(breaks = seq(70, 110, 1),
                labels = percent(seq(70, 110, 1)/100 - 1, 1)) +
  geom_rect(data = data_frame(start = as.Date("2020-02-01"), 
                                end = as.Date("2020-07-01")), 
              aes(xmin = start, xmax = end, ymin = 0, ymax = +Inf), fill = viridis(4)[4], alpha = 0.2)

1999

Code
`IPI-2021` %>%
  filter(NAF2 %in% c("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("1999-01-01")) %>%
  mutate(OBS_VALUE = ifelse(year(date) == 2020 & month(date) %in% c(3, 4, 5, 6), NA, OBS_VALUE)) %>%
  group_by(Naf2) %>%
  mutate(OBS_VALUE = 100*OBS_VALUE/OBS_VALUE[date == as.Date("2020-02-01")]) %>%
  ggplot() + ylab("Indice de Production Industrielle vs. Février 2020\nhors Mars-Juin 2020") + 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 = percent(OBS_VALUE/100-1, acc = .1), color = Naf2)) +
  geom_hline(yintercept = 100, linetype = "dashed") +
  
  scale_x_date(breaks = c(seq(1997, 2100, 5), seq(1999, 2100, 5)) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = c(0.7, 0.9),
        legend.title = element_blank()) +
  scale_y_log10(breaks = seq(70, 110, 1),
                labels = percent(seq(70, 110, 1)/100 - 1, 1)) +
  geom_rect(data = data_frame(start = as.Date("2020-02-01"), 
                                end = as.Date("2020-07-01")), 
              aes(xmin = start, xmax = end, ymin = 0, ymax = +Inf), fill = viridis(4)[4], alpha = 0.2)

2000

Code
`IPI-2021` %>%
  filter(NAF2 %in% c("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("2000-01-01")) %>%
  mutate(OBS_VALUE = ifelse(year(date) == 2020 & month(date) %in% c(3, 4, 5, 6), NA, OBS_VALUE)) %>%
  group_by(Naf2) %>%
  mutate(OBS_VALUE = 100*OBS_VALUE/OBS_VALUE[date == as.Date("2017-05-01")]) %>%
  ggplot() + ylab("Indice de Production Industrielle vs. Mai 2017\n(hors Mars-Juin 2020)") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = OBS_VALUE, color = Naf2))  +
  geom_text_repel(data = . %>%
              filter(date == max(date)), aes(x = date, y = OBS_VALUE, label = percent(OBS_VALUE/100-1, acc = .1), color = Naf2)) +
  geom_hline(yintercept = 100, linetype = "dashed") +
  
  scale_x_date(breaks = seq(1920, 2100, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = c(0.68, 0.9),
        legend.title = element_blank()) +
  scale_y_log10(breaks = seq(70, 120, 1),
                labels = percent(seq(70, 120, 1)/100 - 1, 1)) +
  geom_rect(data = data_frame(start = as.Date("2020-02-01"), 
                                end = as.Date("2020-07-01")), 
              aes(xmin = start, xmax = end, ymin = 0, ymax = +Inf), fill = viridis(4)[4], alpha = 0.2)

2005

Code
`IPI-2021` %>%
  filter(NAF2 %in% c("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("2005-01-01")) %>%
  mutate(OBS_VALUE = ifelse(year(date) == 2020 & month(date) %in% c(3, 4, 5, 6), NA, OBS_VALUE)) %>%
  group_by(Naf2) %>%
  mutate(OBS_VALUE = 100*OBS_VALUE/OBS_VALUE[date == as.Date("2020-02-01")]) %>%
  ggplot() + ylab("Indice de Production Industrielle vs. Février 2020\nhors Mars-Juin 2020 (fermeture Covid-19)") + 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 = percent(OBS_VALUE/100-1, acc = .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(0.6, 0.9),
        legend.title = element_blank(),
        axis.text.x = element_text(angle = 45, vjust = 1, hjust=1)) +
  scale_y_log10(breaks = seq(80, 110, 1),
                labels = percent(seq(80, 110, 1)/100 - 1, 1)) +
  geom_rect(data = data_frame(start = as.Date("2020-02-01"), 
                                end = as.Date("2020-07-01")), 
              aes(xmin = start, xmax = end, ymin = 0, ymax = +Inf), fill = viridis(4)[4], alpha = 0.2)

vs. 2008

Code
`IPI-2021` %>%
  filter(NAF2 %in% c("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("2005-01-01")) %>%
  mutate(OBS_VALUE = ifelse(year(date) == 2020 & month(date) %in% c(3, 4, 5, 6), NA, OBS_VALUE)) %>%
  group_by(Naf2) %>%
  mutate(OBS_VALUE = 100*OBS_VALUE/OBS_VALUE[date == as.Date("2008-01-01")]) %>%
  ggplot() + ylab("Indice de Production Industrielle vs. Janvier 2008\nhors Mars-Juin 2020 (fermeture Covid-19)") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = OBS_VALUE, color = Naf2))  +
  geom_text_repel(data = . %>%
              filter(date == max(date)), aes(x = date, y = OBS_VALUE, label = percent(OBS_VALUE/100-1, acc = .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(0.6, 0.8),
        legend.title = element_blank(),
        axis.text.x = element_text(angle = 45, vjust = 1, hjust=1)) +
  scale_y_log10(breaks = seq(80, 110, 1),
                labels = percent(seq(80, 110, 1)/100 - 1, 1)) +
  geom_rect(data = data_frame(start = as.Date("2020-02-01"), 
                                end = as.Date("2020-07-01")), 
              aes(xmin = start, xmax = end, ymin = 0, ymax = +Inf), fill = viridis(4)[4], alpha = 0.2)

2010

Code
`IPI-2021` %>%
  filter(NAF2 %in% c("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("2010-01-01")) %>%
  mutate(OBS_VALUE = ifelse(year(date) == 2020 & month(date) %in% c(3, 4, 5, 6), NA, OBS_VALUE)) %>%
  group_by(Naf2) %>%
  mutate(OBS_VALUE = 100*OBS_VALUE/OBS_VALUE[date == as.Date("2020-02-01")]) %>%
  ggplot() + ylab("Indice de Production Industrielle vs. Février 2020\nhors Mars-Juin 2020") + 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 = percent(OBS_VALUE/100-1, acc = .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(0.3, 0.9),
        legend.title = element_blank()) +
  scale_y_log10(breaks = seq(90, 110, 1),
                labels = percent(seq(90, 110, 1)/100 - 1, 1)) +
  geom_rect(data = data_frame(start = as.Date("2020-02-01"), 
                                end = as.Date("2020-07-01")), 
              aes(xmin = start, xmax = end, ymin = 0, ymax = +Inf), fill = viridis(4)[4], alpha = 0.2)

2015-

Code
`IPI-2021` %>%
  filter(NAF2 %in% c("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("2015-01-01")) %>%
  mutate(OBS_VALUE = ifelse(year(date) == 2020 & month(date) %in% c(3, 4, 5, 6), NA, OBS_VALUE)) %>%
  group_by(Naf2) %>%
  mutate(OBS_VALUE = 100*OBS_VALUE/OBS_VALUE[date == as.Date("2020-02-01")]) %>%
  ggplot() + ylab("Indice de Production Industrielle vs. Février 2020\nhors Mars-Juin 2020") + 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 = percent(OBS_VALUE/100-1, acc = .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(0.7, 0.9),
        legend.title = element_blank()) +
  scale_y_log10(breaks = seq(90, 110, 1),
                labels = percent(seq(90, 110, 1)/100 - 1, 1)) +
  geom_rect(data = data_frame(start = as.Date("2020-02-01"), 
                                end = as.Date("2020-07-01")), 
              aes(xmin = start, xmax = end, ymin = 0, ymax = +Inf), fill = viridis(4)[4], alpha = 0.2)

Mai 2017-

Code
`IPI-2021` %>%
  filter(NAF2 %in% c("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 %>%
  arrange(desc(date)) %>%
  filter(date >= as.Date("2017-05-01")) %>%
  mutate(OBS_VALUE = ifelse(year(date) == 2020 & month(date) %in% c(3, 4, 5, 6), NA, OBS_VALUE)) %>%
  group_by(Naf2) %>%
  mutate(OBS_VALUE = 100*OBS_VALUE/OBS_VALUE[date == as.Date("2017-05-01")]) %>%
  ggplot() + ylab("Indice de Production Industrielle vs. Mai 2017\nhors Mars-Juin 2020") + 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 = percent(OBS_VALUE/100-1, acc = .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(0.7, 0.9),
        legend.title = element_blank()) +
  scale_y_log10(breaks = seq(90, 110, 1),
                labels = percent(seq(90, 110, 1)/100 - 1, 1)) +
  geom_rect(data = data_frame(start = as.Date("2020-02-01"), 
                                end = as.Date("2020-07-01")), 
              aes(xmin = start, xmax = end, ymin = 0, ymax = +Inf), fill = viridis(4)[4], alpha = 0.2)

2018

Code
`IPI-2021` %>%
  filter(NAF2 %in% c("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("2018-01-01")) %>%
  mutate(OBS_VALUE = ifelse(year(date) == 2020 & month(date) %in% c(3, 4, 5, 6), NA, OBS_VALUE)) %>%
  group_by(Naf2) %>%
  mutate(OBS_VALUE = 100*OBS_VALUE/OBS_VALUE[date == as.Date("2020-02-01")]) %>%
  ggplot() + ylab("Indice de Production Industrielle vs. Février 2020\nhors Mars-Juin 2020") + 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 = percent(OBS_VALUE/100-1, acc = .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(0.7, 0.9),
        legend.title = element_blank()) +
  scale_y_log10(breaks = seq(90, 110, 1),
                labels = percent(seq(90, 110, 1)/100 - 1, 1)) +
  geom_rect(data = data_frame(start = as.Date("2020-02-01"), 
                                end = as.Date("2020-07-01")), 
              aes(xmin = start, xmax = end, ymin = 0, ymax = +Inf), fill = viridis(4)[4], alpha = 0.2)

CZ, DE

All

Code
`IPI-2021` %>%
  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-2021` %>%
  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-2021` %>%
  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-2021` %>%
  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-2021` %>%
  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-2021` %>%
  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-2021` %>%
  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-2021` %>%
  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-2021` %>%
  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-2021` %>%
  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-2021` %>%
  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-2021` %>%
  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-2021` %>%
  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-2021` %>%
  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-2021` %>%
  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-2021` %>%
  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-2021` %>%
  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-2021` %>%
  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-2021` %>%
  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-2021` %>%
  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-2021` %>%
  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-2021` %>%
  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-2021` %>%
  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-2021` %>%
  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-2021` %>%
  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-2021` %>%
  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-2021` %>%
  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-2021` %>%
  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))