Production in industry - monthly data

Data - Eurostat

Info

Last observation: Monthly: 2026M06 (N = 20,865)

First observation: Monthly: 1953M01 (N = 9)

Last data update: 14 aoû 2026, 23:39. Last compile: 15 aoû 2026, 03:32

Structure

freq

indic_bt

nace_r2

s_adj

unit

geo

Last

sts_inpr_m |>
  filter(time == max(time), !is.na(values)) |>
  print_table_conditional()

France VS EU

EU 2027

All

sts_inpr_m |>
  filter(nace_r2 == "C",
         unit == "I21",
         geo %in% c("FR", "EU27_2020"),
         s_adj == "SCA") |>
  select(geo, Geo, time, values) |>
  
  mutate(Geo = ifelse(geo == "DE", "Germany", Geo)) |>
  mutate(Geo = ifelse(geo == "EU27_2020", "Europe", Geo)) |>
  month_to_date() |>
  group_by(geo) |>
  arrange(date) |>
  mutate(values = 100*values/values[1]) |>
  #filter(date >= as.Date("2000-01-01")) %>%
  left_join(colors, by = c("Geo" = "country")) |>
  ggplot() + ylab("Industrial Production") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = values, color = color)) +
  scale_color_identity() +
  scale_x_date(breaks = seq(1920, 2100, 2) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  add_flags +
  scale_y_log10(breaks = seq(-60, 300, 10))

1992-

sts_inpr_m |>
  filter(nace_r2 == "C",
         unit == "I21",
         geo %in% c("FR", "EU27_2020"),
         s_adj == "SCA") |>
  select(geo, Geo, time, values) |>
  group_by(geo) |>
  mutate(values = 100*values/values[time == "1992M01"]) |>
  
  mutate(Geo = ifelse(geo == "DE", "Germany", Geo)) |>
  mutate(Geo = ifelse(geo == "EU27_2020", "Europe", Geo)) |>
  month_to_date() |>
  filter(date >= as.Date("1992-01-01")) |>
  left_join(colors, by = c("Geo" = "country")) |>
  ggplot() + ylab("Industrial Production") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = values, color = color)) +
  scale_color_identity() +
  scale_x_date(breaks = seq(1920, 2100, 2) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  add_flags +
  scale_y_log10(breaks = seq(-60, 300, 10))

2000-

sts_inpr_m |>
  filter(nace_r2 == "C",
         unit == "I21",
         geo %in% c("FR", "EU27_2020"),
         s_adj == "SCA") |>
  select(geo, Geo, time, values) |>
  group_by(geo) |>
  mutate(values = 100*values/values[time == "2000M01"]) |>
  
  mutate(Geo = ifelse(geo == "DE", "Germany", Geo)) |>
  mutate(Geo = ifelse(geo == "EU27_2020", "Europe", Geo)) |>
  month_to_date() |>
  filter(date >= as.Date("2000-01-01")) |>
  left_join(colors, by = c("Geo" = "country")) |>
  ggplot() + ylab("Industrial Production") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = values, color = color)) +
  scale_color_identity() +
  scale_x_date(breaks = seq(1920, 2100, 2) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  add_flags +
  scale_y_log10(breaks = seq(-60, 300, 10))

Eurozone

2000-

sts_inpr_m |>
  filter(nace_r2 == "C",
         unit == "I21",
         geo %in% c("FR", "EA20"),
         s_adj == "SCA") |>
  select(geo, Geo, time, values) |>
  group_by(geo) |>
  mutate(values = 100*values/values[time == "2020M02"]) |>
  
  mutate(Geo = ifelse(geo == "DE", "Germany", Geo)) |>
  mutate(Geo = ifelse(geo == "EA20", "Europe", Geo)) |>
  month_to_date() |>
  filter(date >= as.Date("2000-01-01")) |>
  left_join(colors, by = c("Geo" = "country")) |>
  ggplot() + ylab("Industrial Production") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = values, color = color)) +
  scale_color_identity() +
  scale_x_date(breaks = seq(1920, 2100, 2) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  add_flags +
  scale_y_log10(breaks = seq(-60, 300, 10))

Germany

Index, Change

sts_inpr_m |>
  filter(geo == "DE",
         s_adj == "SCA",
        
         time %in% c("2022M08", "2022M07", "2022M03")) %>%
  select_if(~ n_distinct(.) > 1) |>
  spread(time, values) |>
  
  select(nace_r2, Nace_r2, everything()) |>
  print_table_conditional()

Index

sts_inpr_m |>
  filter(geo == "DE",
         s_adj == "SCA",
         unit == "I21",
         time %in% c("2022M08", "2022M07", "2022M03")) %>%
  select_if(~ n_distinct(.) > 1) |>
  spread(time, values) |>
  
  select(nace_r2, Nace_r2, everything()) |>
  print_table_conditional()

PCH_PRE - Change

sts_inpr_m |>
  filter(geo == "DE",
         #s_adj == "SCA",
         unit == "PCH_SM",
         time %in% c("2022M12", "2022M11", "2022M08", "2022M05","2022M03")) %>%
  select_if(~ n_distinct(.) > 1) |>
  spread(time, values) |>
  
  select(nace_r2, Nace_r2, everything()) |>
  arrange(`2022M11`) |>
  print_table_conditional()

Fertilizers, Chemical industry

All

sts_inpr_m |>
  filter(geo == "DE",
         s_adj == "SCA",
         unit == "I21",
         nace_r2 %in% c("C2015", "C20_C21", "C20", "C2442")) |>
  month_to_date() |>
  
  mutate(Nace_r2 = gsub("Manufacture", "Manuf.", Nace_r2)) |>
  ggplot() + geom_line(aes(x = date, y = values, color = Nace_r2)) +
  xlab("") + ylab("") + theme_minimal() +
  theme(legend.position = c(0.5, 0.25),
        legend.title = element_blank()) + 
  scale_x_date(breaks = "5 years",
               labels = date_format("%Y")) +
  scale_y_log10(breaks = seq(60, 120, 10))

1995-

sts_inpr_m |>
  filter(geo == "DE",
         s_adj == "SCA",
         unit == "I21",
         nace_r2 %in% c("C2015", "C20_C21", "C20", "C2442")) |>
  month_to_date() |>
  filter(date >= as.Date("1995-01-01")) |>
  
  mutate(Nace_r2 = gsub("Manufacture", "Manuf.", Nace_r2)) |>
  ggplot() + geom_line(aes(x = date, y = values, color = Nace_r2)) +
  xlab("") + ylab("") + theme_minimal() +
  theme(legend.position = c(0.5, 0.25),
        legend.title = element_blank()) + 
  scale_x_date(breaks = "5 years",
               labels = date_format("%Y")) +
  scale_y_log10(breaks = seq(60, 120, 10))

2010-

sts_inpr_m |>
  filter(geo == "DE",
         s_adj == "SCA",
         unit == "I21",
         nace_r2 %in% c("C2015", "C20_C21", "C20", "C2442")) |>
  month_to_date() |>
  filter(date >= as.Date("2010-01-01")) |>
  
  mutate(Nace_r2 = gsub("Manufacture", "Manuf.", Nace_r2)) |>
  ggplot() + geom_line(aes(x = date, y = values, color = Nace_r2)) +
  xlab("") + ylab("") + theme_minimal() +
  theme(legend.position = c(0.5, 0.25),
        legend.title = element_blank()) + 
  scale_x_date(breaks = "1 year",
               labels = date_format("%Y")) +
  scale_y_log10(breaks = seq(60, 120, 10))

2017-

sts_inpr_m |>
  filter(geo == "DE",
         s_adj == "SCA",
         unit == "I21",
         nace_r2 %in% c("C2015", "C20_C21", "C20", "C2442")) |>
  month_to_date() |>
  filter(date >= as.Date("2017-01-01")) |>
  
  mutate(Nace_r2 = gsub("Manufacture", "Manuf.", Nace_r2)) |>
  ggplot() + geom_line(aes(x = date, y = values, color = Nace_r2)) +
  xlab("") + ylab("") + theme_minimal() +
  theme(legend.position = c(0.5, 0.25),
        legend.title = element_blank()) + 
  scale_x_date(breaks = "1 year",
               labels = date_format("%Y")) +
  scale_y_log10(breaks = seq(40, 120, 10))

2020-

sts_inpr_m |>
  filter(geo == "DE",
         s_adj == "SCA",
         unit == "I21",
         nace_r2 %in% c("C2015", "C20_C21", "C20", "C2442")) |>
  month_to_date() |>
  filter(date >= as.Date("2020-01-01")) |>
  
  mutate(Nace_r2 = gsub("Manufacture", "Manuf.", Nace_r2)) |>
  ggplot() + geom_line(aes(x = date, y = values, color = Nace_r2)) +
  xlab("") + ylab("") + theme_minimal() +
  theme(legend.position = c(0.5, 0.25),
        axis.text.x = element_text(angle = 45, vjust = 1, hjust = 1),
        legend.title = element_blank()) + 
  scale_x_date(breaks = "3 months",
               labels = date_format("%b %Y")) +
  scale_y_log10(breaks = seq(40, 120, 5))

France, Germany, Italy, Greece, Europe

1995-

sts_inpr_m |>
  filter(nace_r2 == "C",
         unit == "I21",
         geo %in% c("FR", "DE", "IT", "EA20", "EL"),
         s_adj == "SCA") |>
  select(geo, Geo, time, values) |>
  group_by(geo) |>
  month_to_date() |>
  filter(date >= as.Date("1995-01-01")) |>
  arrange(date) |>
  mutate(values = 100*values/values[1]) |>
  
  mutate(Geo = ifelse(geo == "DE", "Germany", Geo)) |>
  mutate(Geo = ifelse(geo == "EA20", "Europe", Geo)) |>
  left_join(colors, by = c("Geo" = "country")) |>
  ggplot() + ylab("Industrial Production") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = values, color = color)) +
  scale_color_identity() +
  scale_x_date(breaks = seq(1920, 2100, 2) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  add_flags +
  scale_y_log10(breaks = seq(-60, 300, 10))

2000-

sts_inpr_m |>
  filter(nace_r2 == "C",
         unit == "I21",
         geo %in% c("FR", "DE", "IT", "EA20", "EL"),
         s_adj == "SCA") |>
  select(geo, Geo, time, values) |>
  group_by(geo) |>
  month_to_date() |>
  filter(date >= as.Date("2000-01-01")) |>
  arrange(date) |>
  mutate(values = 100*values/values[1]) |>
  
  mutate(Geo = ifelse(geo == "DE", "Germany", Geo)) |>
  mutate(Geo = ifelse(geo == "EA20", "Europe", Geo)) |>
  left_join(colors, by = c("Geo" = "country")) |>
  ggplot() + ylab("Industrial Production") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = values, color = color)) +
  scale_color_identity() +
  scale_x_date(breaks = seq(1920, 2100, 2) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  add_flags +
  scale_y_log10(breaks = seq(-60, 300, 10))

2008-

sts_inpr_m |>
  filter(nace_r2 == "C",
         unit == "I21",
         geo %in% c("FR", "DE", "IT", "EA20", "EL"),
         s_adj == "SCA") |>
  select(geo, Geo, time, values) |>
  group_by(geo) |>
  month_to_date() |>
  filter(date >= as.Date("2008-01-01")) |>
  arrange(date) |>
  mutate(values = 100*values/values[1]) |>
  
  mutate(Geo = ifelse(geo == "DE", "Germany", Geo)) |>
  mutate(Geo = ifelse(geo == "EA20", "Europe", Geo)) |>
  left_join(colors, by = c("Geo" = "country")) |>
  ggplot() + ylab("Industrial Production") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = values, color = color)) +
  scale_color_identity() +
  scale_x_date(breaks = seq(1920, 2100, 2) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  add_flags +
  scale_y_log10(breaks = seq(-60, 300, 10))

France, Germany, Italy

C20 - Manufacture of chemicals and chemical products

All

sts_inpr_m |>
  filter(nace_r2 == "C20",
         unit == "I21",
         geo %in% c("FR", "DE", "IT", "EA20"),
         s_adj == "SCA") |>
  select(geo, Geo, time, values) |>
  group_by(geo) |>
  mutate(values = 100*values/values[time == "2010M01"]) |>
  
  mutate(Geo = ifelse(geo == "DE", "Germany", Geo)) |>
  mutate(Geo = ifelse(geo == "EA20", "Europe", Geo)) |>
  month_to_date() |>
  left_join(colors, by = c("Geo" = "country")) |>
  ggplot() + ylab("Industrial Production") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = values, color = color)) +
  scale_color_identity() + add_flags +
  scale_x_date(breaks = seq(1920, 2100, 5) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  theme(legend.position = "none") +
  scale_y_log10(breaks = seq(-60, 300, 10))

1992-

sts_inpr_m |>
  filter(nace_r2 == "C20",
         unit == "I21",
         geo %in% c("FR", "DE", "IT", "EA20"),
         s_adj == "SCA") |>
  select(geo, Geo, time, values) |>
  group_by(geo) |>
  mutate(values = 100*values/values[time == "2001M01"]) |>
  
  mutate(Geo = ifelse(geo == "DE", "Germany", Geo)) |>
  mutate(Geo = ifelse(geo == "EA20", "Europe", Geo)) |>
  month_to_date() |>
  filter(date >= as.Date("1992-01-01")) |>
  left_join(colors, by = c("Geo" = "country")) |>
  ggplot() + ylab("Industrial Production") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = values, color = color)) +
  scale_color_identity() + add_flags +
  scale_x_date(breaks = seq(1920, 2100, 2) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  theme(legend.position = "none") +
  scale_y_log10(breaks = seq(-60, 300, 10))

2000-

sts_inpr_m |>
  filter(nace_r2 == "C20",
         unit == "I21",
         geo %in% c("FR", "DE", "IT", "EA20"),
         s_adj == "SCA") |>
  select(geo, Geo, time, values) |>
  group_by(geo) |>
  mutate(values = 100*values/values[time == "2001M01"]) |>
  
  mutate(Geo = ifelse(geo == "DE", "Germany", Geo)) |>
  mutate(Geo = ifelse(geo == "EA20", "Europe", Geo)) |>
  month_to_date() |>
  filter(date >= as.Date("2000-01-01")) |>
  left_join(colors, by = c("Geo" = "country")) |>
  ggplot() + ylab("Industrial Production\nManufacture of fertilisers and nitrogen compounds") + xlab("") +
  geom_line(aes(x = date, y = values, color = color)) +
  scale_color_identity() + add_flags + theme_minimal() +
  scale_x_date(breaks = seq(1920, 2100, 2) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  scale_y_log10(breaks = seq(-60, 300, 10))

2019-

sts_inpr_m |>
  filter(nace_r2 == "C20",
         unit == "I21",
         geo %in% c("FR", "DE", "IT", "EA20"),
         s_adj == "SCA") |>
  select(geo, Geo, time, values) |>
  group_by(geo) |>
  mutate(values = 100*values/values[time == "2019M01"]) |>
  
  mutate(Geo = ifelse(geo == "DE", "Germany", Geo)) |>
  mutate(Geo = ifelse(geo == "EA20", "Europe", Geo)) |>
  month_to_date() |>
  filter(date >= as.Date("2019-01-01")) |>
  left_join(colors, by = c("Geo" = "country")) |>
  ggplot() + ylab("Industrial Production\nManufacture of fertilisers and nitrogen compounds") + xlab("") +
  geom_line(aes(x = date, y = values, color = color)) +
  scale_color_identity() + add_flags + theme_minimal() +
  scale_x_date(breaks = "3 months",
               labels = date_format("%b %Y")) +
  add_flags +
  theme(legend.position = "none",
        axis.text.x = element_text(angle = 45, vjust = 1, hjust = 1)) +
  scale_y_log10(breaks = seq(-60, 300, 5))

2020-

sts_inpr_m |>
  filter(nace_r2 == "C20",
         unit == "I21",
         geo %in% c("FR", "DE", "IT", "EA20"),
         s_adj == "SCA") |>
  select(geo, Geo, time, values) |>
  group_by(geo) |>
  mutate(values = 100*values/values[time == "2020M01"]) |>
  
  mutate(Geo = ifelse(geo == "DE", "Germany", Geo)) |>
  mutate(Geo = ifelse(geo == "EA20", "Europe", Geo)) |>
  month_to_date() |>
  filter(date >= as.Date("2020-01-01")) |>
  left_join(colors, by = c("Geo" = "country")) |>
  ggplot() + ylab("Industrial Production\nManufacture of fertilisers and nitrogen compounds") + xlab("") +
  geom_line(aes(x = date, y = values, color = color)) +
  scale_color_identity() + add_flags + theme_minimal() +
  theme(legend.position = "none",
        axis.text.x = element_text(angle = 45, vjust = 1, hjust = 1)) +
  scale_x_date(breaks = "2 months",
               labels = date_format("%b %Y")) +
  scale_y_log10(breaks = seq(-60, 300, 5))

2021-

sts_inpr_m |>
  filter(nace_r2 == "C20",
         unit == "I21",
         geo %in% c("FR", "DE", "IT", "EA20"),
         s_adj == "SCA") |>
  select(geo, Geo, time, values) |>
  group_by(geo) |>
  mutate(values = 100*values/values[time == "2021M01"]) |>
  
  mutate(Geo = ifelse(geo == "DE", "Germany", Geo)) |>
  mutate(Geo = ifelse(geo == "EA20", "Europe", Geo)) |>
  month_to_date() |>
  filter(date >= as.Date("2021-01-01")) |>
  left_join(colors, by = c("Geo" = "country")) |>
  ggplot() + ylab("Industrial Production\nManufacture of chemicals and chemical products") + xlab("") +
  geom_line(aes(x = date, y = values, color = color)) +
  scale_color_identity() + add_flags + theme_minimal() +
  theme(legend.position = "none",
        axis.text.x = element_text(angle = 45, vjust = 1, hjust = 1)) +
  scale_x_date(breaks = "2 months",
               labels = date_format("%b %Y")) +
  scale_y_log10(breaks = seq(-60, 300, 5))

C2015 - Manufacture of fertilisers and nitrogen compounds

All

sts_inpr_m |>
  filter(nace_r2 == "C2015",
         unit == "I21",
         geo %in% c("FR", "DE", "IT", "EA20"),
         s_adj == "SCA") |>
  select(geo, Geo, time, values) |>
  group_by(geo) |>
  mutate(values = 100*values/values[time == "2010M01"]) |>
  
  mutate(Geo = ifelse(geo == "DE", "Germany", Geo)) |>
  mutate(Geo = ifelse(geo == "EA20", "Europe", Geo)) |>
  month_to_date() |>
  left_join(colors, by = c("Geo" = "country")) |>
  ggplot() + ylab("Industrial Production") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = values, color = color)) +
  scale_color_identity() + add_flags +
  scale_x_date(breaks = seq(1920, 2100, 5) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  theme(legend.position = "none") +
  scale_y_log10(breaks = seq(-60, 300, 10))

1992-

sts_inpr_m |>
  filter(nace_r2 == "C2015",
         unit == "I21",
         geo %in% c("FR", "DE", "IT", "EA20"),
         s_adj == "SCA") |>
  select(geo, Geo, time, values) |>
  
  mutate(Geo = ifelse(geo == "DE", "Germany", Geo)) |>
  mutate(Geo = ifelse(geo == "EA20", "Europe", Geo)) |>
  month_to_date() |>
  group_by(geo) |>
  arrange(date) |>
  mutate(values = 100*values/values[1]) |>
  filter(date >= as.Date("1992-01-01")) |>
  left_join(colors, by = c("Geo" = "country")) |>
  ggplot() + ylab("Industrial Production") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = values, color = color)) +
  scale_color_identity() + add_flags +
  scale_x_date(breaks = seq(1920, 2100, 2) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  theme(legend.position = "none") +
  scale_y_log10(breaks = seq(-60, 300, 10))

2000-

sts_inpr_m |>
  filter(nace_r2 == "C2015",
         unit == "I21",
         geo %in% c("FR", "DE", "IT", "EA20"),
         s_adj == "SCA") |>
  select(geo, Geo, time, values) |>
  
  mutate(Geo = ifelse(geo == "DE", "Germany", Geo)) |>
  mutate(Geo = ifelse(geo == "EA20", "Europe", Geo)) |>
  month_to_date() |>
  group_by(geo) |>
  mutate(values = 100*values/values[1]) |>
  filter(date >= as.Date("2000-01-01")) |>
  left_join(colors, by = c("Geo" = "country")) |>
  ggplot() + ylab("Industrial Production\nManufacture of fertilisers and nitrogen compounds") + xlab("") +
  geom_line(aes(x = date, y = values, color = color)) +
  scale_color_identity() + add_flags + theme_minimal() +
  scale_x_date(breaks = seq(1920, 2100, 2) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  scale_y_log10(breaks = seq(-60, 300, 10))

2019-

sts_inpr_m |>
  filter(nace_r2 == "C2015",
         unit == "I21",
         geo %in% c("FR", "DE", "IT", "EA20"),
         s_adj == "SCA") |>
  select(geo, Geo, time, values) |>
  group_by(geo) |>
  mutate(values = 100*values/values[time == "2019M01"]) |>
  
  mutate(Geo = ifelse(geo == "DE", "Germany", Geo)) |>
  mutate(Geo = ifelse(geo == "EA20", "Europe", Geo)) |>
  month_to_date() |>
  filter(date >= as.Date("2019-01-01")) |>
  left_join(colors, by = c("Geo" = "country")) |>
  ggplot() + ylab("Industrial Production\nManufacture of fertilisers and nitrogen compounds") + xlab("") +
  geom_line(aes(x = date, y = values, color = color)) +
  scale_color_identity() + add_flags + theme_minimal() +
  scale_x_date(breaks = "3 months",
               labels = date_format("%b %Y")) +
  add_flags +
  theme(legend.position = "none",
        axis.text.x = element_text(angle = 45, vjust = 1, hjust = 1)) +
  scale_y_log10(breaks = seq(-60, 300, 10))

2020-

sts_inpr_m |>
  filter(nace_r2 == "C2015",
         unit == "I21",
         geo %in% c("FR", "DE", "IT", "EA20"),
         s_adj == "SCA") |>
  select(geo, Geo, time, values) |>
  group_by(geo) |>
  mutate(values = 100*values/values[time == "2020M01"]) |>
  
  mutate(Geo = ifelse(geo == "DE", "Germany", Geo)) |>
  mutate(Geo = ifelse(geo == "EA20", "Europe", Geo)) |>
  month_to_date() |>
  filter(date >= as.Date("2020-01-01")) |>
  left_join(colors, by = c("Geo" = "country")) |>
  ggplot() + ylab("Industrial Production\nManufacture of fertilisers and nitrogen compounds") + xlab("") +
  geom_line(aes(x = date, y = values, color = color)) +
  scale_color_identity() + add_flags + theme_minimal() +
  theme(legend.position = "none",
        axis.text.x = element_text(angle = 45, vjust = 1, hjust = 1)) +
  scale_x_date(breaks = "2 months",
               labels = date_format("%b %Y")) +
  scale_y_log10(breaks = seq(-60, 300, 10))

2021-

nace_r2 <- read_parquet("nace_r2_fr.parquet")
sts_inpr_m |>
  filter(nace_r2 == "C2015",
         unit == "I21",
         geo %in% c("FR", "DE", "IT", "EA20"),
         s_adj == "SCA") |>
  group_by(geo) |>
  mutate(values = 100*values/values[time == "2021M01"]) |>
  
  
  mutate(Geo = ifelse(geo == "DE", "Germany", Geo)) |>
  mutate(Geo = ifelse(geo == "EA20", "Europe", Geo)) |>
  month_to_date() |>
  filter(date >= as.Date("2021-01-01")) |>
  left_join(colors, by = c("Geo" = "country")) |>
  ggplot() + ylab("Production industrielle\nFabrication de produits azotés et d'engrais") + xlab("") +
  geom_line(aes(x = date, y = values, color = color)) +
  scale_color_identity() + add_flags + theme_minimal() +
  theme(legend.position = "none",
        axis.text.x = element_text(angle = 45, vjust = 1, hjust = 1)) +
  scale_x_date(breaks = "2 months",
               labels = date_format("%b %Y")) +
  scale_y_log10(breaks = seq(-60, 300, 10))

Manufacturing

All

sts_inpr_m |>
  filter(nace_r2 == "C",
         unit == "I21",
         geo %in% c("FR", "DE", "IT", "EA20"),
         s_adj == "SCA") |>
  select(geo, Geo, time, values) |>
  group_by(geo) |>
  mutate(values = 100*values/values[time == "1997M01"]) |>
  
  mutate(Geo = ifelse(geo == "DE", "Germany", Geo)) |>
  mutate(Geo = ifelse(geo == "EA20", "Europe", Geo)) |>
  month_to_date() |>
  left_join(colors, by = c("Geo" = "country")) |>
  ggplot() + ylab("Industrial Production") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = values, color = color)) +
  scale_color_identity() + add_flags +
  scale_x_date(breaks = seq(1920, 2100, 5) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  theme(legend.position = "none") +
  scale_y_log10(breaks = seq(-60, 300, 10))

1992-

sts_inpr_m |>
  filter(nace_r2 == "C",
         unit == "I21",
         geo %in% c("FR", "DE", "IT", "EA20"),
         s_adj == "SCA") |>
  select(geo, Geo, time, values) |>
  group_by(geo) |>
  month_to_date() |>
  arrange(date) |>
  mutate(values = 100*values/values[1]) |>
  
  mutate(Geo = ifelse(geo == "DE", "Germany", Geo)) |>
  mutate(Geo = ifelse(geo == "EA20", "Europe", Geo)) |>
  filter(date >= as.Date("1992-01-01")) |>
  left_join(colors, by = c("Geo" = "country")) |>
  ggplot() + ylab("Industrial Production") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = values, color = color)) +
  scale_color_identity() + add_flags +
  scale_x_date(breaks = seq(1920, 2100, 2) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  theme(legend.position = "none") +
  scale_y_log10(breaks = seq(-60, 300, 10))

1995-

sts_inpr_m |>
  filter(nace_r2 == "C",
         unit == "I21",
         geo %in% c("FR", "DE", "IT", "EA20"),
         s_adj == "SCA") |>
  select(geo, Geo, time, values) |>
  group_by(geo) |>
  month_to_date() |>
  filter(date >= as.Date("1995-01-01")) |>
  arrange(date) |>
  mutate(values = 100*values/values[1]) |>
  
  mutate(Geo = ifelse(geo == "DE", "Germany", Geo)) |>
  mutate(Geo = ifelse(geo == "EA20", "Europe", Geo)) |>
  left_join(colors, by = c("Geo" = "country")) |>
  ggplot() + ylab("Industrial Production") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = values, color = color)) +
  scale_color_identity() +
  scale_x_date(breaks = seq(1920, 2100, 2) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  add_flags +
  scale_y_log10(breaks = seq(-60, 300, 10))

2000-

sts_inpr_m |>
  filter(nace_r2 == "C",
         unit == "I21",
         geo %in% c("FR", "DE", "IT", "EA20"),
         s_adj == "SCA") |>
  select(geo, Geo, time, values) |>
  group_by(geo) |>
  month_to_date() |>
  filter(date >= as.Date("2000-01-01")) |>
  arrange(date) |>
  mutate(values = 100*values/values[1]) |>
  
  mutate(Geo = ifelse(geo == "DE", "Germany", Geo)) |>
  mutate(Geo = ifelse(geo == "EA20", "Europe", Geo)) |>
  left_join(colors, by = c("Geo" = "country")) |>
  ggplot() + ylab("Industrial Production") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = values, color = color)) +
  scale_color_identity() +
  scale_x_date(breaks = seq(1920, 2100, 2) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  add_flags +
  scale_y_log10(breaks = seq(-60, 300, 10))

2019-

sts_inpr_m |>
  filter(nace_r2 == "C",
         unit == "I21",
         geo %in% c("FR", "DE", "IT", "EA20"),
         s_adj == "SCA") |>
  select(geo, Geo, time, values) |>
  group_by(geo) |>
  mutate(values = 100*values/values[time == "2019M01"]) |>
  
  mutate(Geo = ifelse(geo == "DE", "Germany", Geo)) |>
  mutate(Geo = ifelse(geo == "EA20", "Europe", Geo)) |>
  month_to_date() |>
  filter(date >= as.Date("2019-01-01")) |>
  left_join(colors, by = c("Geo" = "country")) |>
  ggplot() + ylab("Industrial Production") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = values, color = color)) +
  scale_color_identity() +
  scale_x_date(breaks = "3 months",
               labels = date_format("%b %Y")) +
  theme(legend.position = "none",
        axis.text.x = element_text(angle = 45, vjust = 1, hjust = 1)) +
  add_flags +
  theme(legend.position = "none") +
  scale_y_log10(breaks = seq(-60, 300, 10))

2020-

sts_inpr_m |>
  filter(nace_r2 == "C",
         unit == "I21",
         geo %in% c("FR", "DE", "IT", "EA20", "ES"),
         s_adj == "SCA") |>
  select(geo, Geo, time, values) |>
  group_by(geo) |>
  mutate(values = 100*values/values[time == "2020M02"]) |>
  
  mutate(Geo = ifelse(geo == "DE", "Germany", Geo)) |>
  mutate(Geo = ifelse(geo == "EA20", "Europe", Geo)) |>
  month_to_date() |>
  filter(date >= as.Date("2020-02-01")) |>
  left_join(colors, by = c("Geo" = "country")) |>
  ggplot() + ylab("Industrial Production, Manufacturing") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = values, color = color)) +
  scale_color_identity() + add_flags +
  theme(legend.position = "none",
        axis.text.x = element_text(angle = 45, vjust = 1, hjust = 1)) +
  scale_x_date(breaks = "2 months",
               labels = date_format("%b %Y")) +
  scale_y_log10(breaks = seq(-60, 300, 10))

Covid-19

Table

sts_inpr_m |>
  filter(nace_r2 == "C",
         unit == "I21",
         s_adj == "SCA",
         time %in% c("2019M11", "2020M02", "2020M03", "2020M04", "2020M05", "2020M08", "2020M11"),
         !(geo %in% c("IE", "EU28"))) |>
  select(geo, Geo, time, values) |>
  group_by(geo) |>
  mutate(values = 100*values/values[time == "2019M11"]) |>
  
  spread(time, values) |>
  mutate(Geo = ifelse(geo == "DE", "Germany", Geo)) |>
  mutate(Flag = gsub(" ", "-", str_to_lower(Geo)),
         Flag = paste0('<img src="../../bib/flags/vsmall/', Flag, '.png" alt="Flag">')) |>
  select(Flag, everything()) |>
  arrange(`2020M04`) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F, escape = F) else .}

2018

sts_inpr_m |>
  filter(nace_r2 == "C",
         unit == "I21",
         geo %in% c("FR", "DE", "IT"),
         s_adj == "SCA") |>
  select(geo, Geo, time, values) |>
  group_by(geo) |>
  mutate(values = 100*values/values[time == "2018M01"]) |>
  
  mutate(Geo = ifelse(geo == "DE", "Germany", Geo)) |>
  month_to_date() |>
  filter(date >= as.Date("2018-01-01")) |>
  ggplot() + ylab("Industrial Production") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = values, color = Geo)) +
  scale_color_manual(values = c("#0055a4", "#000000", "#008c45")) +
  scale_x_date(breaks = "3 months",
               labels = date_format("%b %Y")) +
  geom_image(data = . %>%
               filter(date == as.Date("2021-01-01")) %>%
               mutate(image = paste0("../../icon/flag/", str_to_lower(Geo), ".png")),
             aes(x = date, y = values, image = image), asp = 1.5) +
  theme(legend.position = "none",
        axis.text.x = element_text(angle = 45, vjust = 1, hjust = 1)) +
  scale_y_log10(breaks = seq(-60, 300, 10))

2019M09

sts_inpr_m |>
  filter(nace_r2 == "C",
         unit == "I21",
         geo %in% c("FR", "DE", "IT"),
         s_adj == "SCA") |>
  select(geo, Geo, time, values) |>
  group_by(geo) |>
  mutate(values = 100*values/values[time == "2019M09"]) |>
  
  mutate(Geo = ifelse(geo == "DE", "Germany", Geo)) |>
  month_to_date() |>
  filter(date >= as.Date("2019-09-01")) |>
  ggplot() + ylab("Industrial Production") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = values, color = Geo)) +
  scale_color_manual(values = c("#0055a4", "#000000", "#008c45")) +
  scale_x_date(breaks = "2 months",
               labels = date_format("%b %Y")) +
  geom_image(data = . %>%
               filter(date == as.Date("2021-05-01")) %>%
               mutate(image = paste0("../../icon/flag/", str_to_lower(Geo), ".png")),
             aes(x = date, y = values, image = image), asp = 1.5) +
  theme(legend.position = "none",
        axis.text.x = element_text(angle = 45, vjust = 1, hjust = 1)) +
  scale_y_log10(breaks = seq(-60, 300, 10))

2020M02

sts_inpr_m |>
  filter(nace_r2 == "C",
         unit == "I21",
         geo %in% c("FR", "DE", "IT", "ES"),
         s_adj == "SCA") |>
  select(geo, Geo, time, values) |>
  group_by(geo) |>
  mutate(values = 100*values/values[time == "2020M02"]) |>
  
  mutate(Geo = ifelse(geo == "DE", "Germany", Geo)) |>
  month_to_date() |>
  filter(date >= as.Date("2020-02-01")) |>
  ggplot() + ylab("Industrial Production") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = values, color = Geo)) +
  scale_color_manual(values = c("#0055a4", "#000000", "#008c45", "#C60B1E")) +
  scale_x_date(breaks = "3 months",
               labels = date_format("%b %Y")) +
  geom_image(data = . %>%
               filter(date == as.Date("2020-08-01")) %>%
               mutate(image = paste0("../../icon/flag/", str_to_lower(Geo), ".png")),
             aes(x = date, y = values, image = image), asp = 1.5) +
  theme(legend.position = "none",
        axis.text.x = element_text(angle = 45, vjust = 1, hjust = 1)) +
  scale_y_log10(breaks = seq(-60, 300, 10))

Cumulative loss in production

sts_inpr_m |>
  filter(nace_r2 == "C",
         unit == "I21",
         geo %in% c("FR", "DE", "IT", "ES", "UK"),
         s_adj == "SCA") |>
  select(geo, Geo, time, values) |>
  group_by(geo) |>
  mutate(values = 100*values/values[time == "2020M02"]) |>
  
  month_to_date() |>
  filter(date >= as.Date("2020-02-01")) |>
  group_by(Geo) |>
  arrange(date) |>
  mutate(values = values-100,
         values = cumsum(values)) |>
  left_join(colors, by = c("Geo" = "country")) |>
  ggplot() + ylab("Industrial Production (Cumulative loss)") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = values, color = color)) +
  scale_color_identity() +
  scale_x_date(breaks = "2 months",
               labels = date_format("%b %Y")) +
  add_flags +
  theme(legend.position = "none",
        axis.text.x = element_text(angle = 45, vjust = 1, hjust = 1)) +
  scale_y_continuous(breaks = seq(-300, 300, 10))

Cumulative loss in production

sts_inpr_m |>
  filter(nace_r2 == "C",
         unit == "I21",
         geo %in% c("FR", "DE", "IT", "ES"),
         s_adj == "SCA") |>
  select(geo, Geo, time, values) |>
  group_by(geo) |>
  mutate(values = 100*values/values[time == "2020M02"]) |>
  
  month_to_date() |>
  filter(date >= as.Date("2020-02-01")) |>
  group_by(Geo) |>
  arrange(date) |>
  mutate(values = values-100,
         values = cumsum(values)) |>
  ggplot() + ylab("Industrial Production (Cumulative loss)") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = values, color = Geo)) +
  scale_color_manual(values = c("#0055a4", "#000000", "#008c45", "#C60B1E")) +
  scale_x_date(breaks = "2 months",
               labels = date_format("%b %Y")) +
  add_flags +
  theme(legend.position = "none",
        axis.text.x = element_text(angle = 45, vjust = 1, hjust = 1)) +
  scale_y_continuous(breaks = seq(-300, 300, 10))