Turnover in industry, total - monthly data - sts_intv_m

Data - Eurostat

Author

François Geerolf

indic_bt

Code 
sts_intv_m %>%
  left_join(indic_bt, by = "indic_bt") %>%
  group_by(indic_bt, Indic_bt) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  print_table_conditional()
indic_bt Indic_bt Nobs
TOVT Index of turnover - Total 4179782

nace_r2

Code 
sts_intv_m %>%
  left_join(nace_r2, by = "nace_r2") %>%
  group_by(nace_r2, Nace_r2) %>%
  summarise(Nobs = n()) %>%
  print_table_conditional()

s_adj

Code 
sts_intv_m %>%
  left_join(s_adj, by = "s_adj") %>%
  group_by(s_adj, S_adj) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  print_table_conditional()
s_adj S_adj Nobs
SCA Seasonally and calendar adjusted data 1593300
CA Calendar adjusted data, not seasonally adjusted data 1578233
NSA Unadjusted data (i.e. neither seasonally adjusted nor calendar adjusted data) 1008249

unit

Code 
sts_intv_m %>%
  left_join(unit, by = "unit") %>%
  group_by(unit, Unit) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  {if (is_html_output()) print_table(.) else .}
unit Unit Nobs
I15 Index, 2015=100 1288306
I21 Index, 2021=100 1086311
I10 Index, 2010=100 910585
PCH_PRE Percentage change on previous period 455843
PCH_SM Percentage change compared to same period in previous year 438737

geo

Code 
sts_intv_m %>%
  left_join(geo, by = "geo") %>%
  group_by(geo, Geo) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  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()) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F, escape = F) else .}

time

Code 
sts_intv_m %>%
  group_by(time) %>%
  summarise(Nobs = n()) %>%
  arrange(desc(time)) %>%
  print_table_conditional()

Germany - Different Industries

C10 - Manufacture of food products

Code 
sts_intv_m %>%
  filter(nace_r2 == "C10",
         unit == "I15",
         s_adj == "SCA",
         geo %in% c("DE")) %>%
  group_by(indic_bt) %>%
  mutate(values = 100*values/values[time == "2004M01"]) %>%
  left_join(indic_bt, by = "indic_bt") %>%
  month_to_date %>%
  filter(date <= as.Date("2020-07-01"),
         date >= as.Date("2000-01-01")) %>%
  ggplot() + ylab("Index of turnover - Non domestic market") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = values, color = Indic_bt)) +
  scale_color_manual(values = viridis(4)[1:3]) +
  scale_x_date(breaks = seq(1920, 2025, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%y")) +
  theme(legend.position = c(0.3, 0.85),
        legend.title = element_blank()) +
  scale_y_log10(breaks = seq(-60, 300, 10))

C13-C15 - Manufacture of textiles, wearing apparel, leather and related products

Code 
sts_intv_m %>%
  filter(nace_r2 == "C13-C15",
         unit == "I15",
         s_adj == "SCA",
         geo %in% c("DE")) %>%
  group_by(indic_bt) %>%
  left_join(indic_bt, by = "indic_bt") %>%
  month_to_date %>%
  filter(date <= as.Date("2020-07-01"),
         date >= as.Date("2000-01-01")) %>%
  ggplot() + ylab("Index of turnover - Non domestic market") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = values, color = Indic_bt)) +
  scale_color_manual(values = viridis(4)[1:3]) +
  scale_x_date(breaks = seq(1920, 2025, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%y")) +
  theme(legend.position = c(0.3, 0.25),
        legend.title = element_blank()) +
  scale_y_log10(breaks = seq(-60, 300, 10))

C20 - Manufacture of chemicals and chemical products

Code 
sts_intv_m %>%
  filter(nace_r2 == "C20",
         unit == "I15",
         s_adj == "SCA",
         geo %in% c("DE")) %>%
  group_by(indic_bt) %>%
  mutate(values = 100*values/values[time == "2004M01"]) %>%
  left_join(indic_bt, by = "indic_bt") %>%
  month_to_date %>%
  filter(date <= as.Date("2020-07-01"),
         date >= as.Date("2000-01-01")) %>%
  ggplot() + ylab("Index of turnover - Non domestic market") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = values, color = Indic_bt)) +
  scale_color_manual(values = viridis(4)[1:3]) +
  scale_x_date(breaks = seq(1920, 2025, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%y")) +
  theme(legend.position = c(0.3, 0.85),
        legend.title = element_blank()) +
  scale_y_log10(breaks = seq(-60, 300, 10))

C30 - Manufacture of other transport equipment

Code 
sts_intv_m %>%
  filter(nace_r2 == "C30",
         unit == "I15",
         s_adj == "SCA",
         geo %in% c("DE")) %>%
  group_by(indic_bt) %>%
  mutate(values = 100*values/values[time == "2004M01"]) %>%
  left_join(indic_bt, by = "indic_bt") %>%
  month_to_date %>%
  filter(date <= as.Date("2020-07-01"),
         date >= as.Date("2000-01-01")) %>%
  ggplot() + ylab("Index of turnover - Non domestic market") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = values, color = Indic_bt)) +
  scale_color_manual(values = viridis(4)[1:3]) +
  scale_x_date(breaks = seq(1920, 2025, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%y")) +
  theme(legend.position = c(0.3, 0.85),
        legend.title = element_blank()) +
  scale_y_log10(breaks = seq(-60, 300, 10))

Individual Countries

France

Code 
sts_intv_m %>%
  filter(nace_r2 == "C",
         unit == "I15",
         s_adj == "SCA",
         geo %in% c("FR")) %>%
  group_by(indic_bt) %>%
  mutate(values = 100*values/values[time == "2000M01"]) %>%
  left_join(indic_bt, by = "indic_bt") %>%
  month_to_date %>%
  filter(date <= as.Date("2020-07-01")) %>%
  ggplot() + ylab("Index of turnover - Non domestic market") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = values, color = Indic_bt)) +
  scale_color_manual(values = c("#0055a4", "#000000", "#008c45")) +
  scale_x_date(breaks = seq(1920, 2025, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%y")) +
  theme(legend.position = c(0.3, 0.85),
        legend.title = element_blank()) +
  scale_y_log10(breaks = seq(-60, 300, 10))

Germany

All

Code 
sts_intv_m %>%
  filter(nace_r2 == "C",
         unit == "I15",
         s_adj == "SCA",
         geo %in% c("DE")) %>%
  group_by(indic_bt) %>%
  mutate(values = 100*values/values[time == "2004M01"]) %>%
  left_join(indic_bt, by = "indic_bt") %>%
  month_to_date %>%
  filter(date <= as.Date("2020-07-01")) %>%
  ggplot() + ylab("Index of turnover - Non domestic market") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = values, color = Indic_bt)) +
  scale_color_manual(values = c("#0055a4", "#000000", "#008c45")) +
  scale_x_date(breaks = seq(1920, 2025, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%y")) +
  theme(legend.position = c(0.3, 0.85),
        legend.title = element_blank()) +
  scale_y_log10(breaks = seq(-60, 300, 10))

2000-

Code 
sts_intv_m %>%
  filter(nace_r2 == "C",
         unit == "I15",
         s_adj == "SCA",
         geo %in% c("DE")) %>%
  group_by(indic_bt) %>%
  mutate(values = 100*values/values[time == "2004M01"]) %>%
  left_join(indic_bt, by = "indic_bt") %>%
  month_to_date %>%
  filter(date <= as.Date("2020-07-01"),
         date >= as.Date("2000-01-01")) %>%
  ggplot() + ylab("Index of turnover - Non domestic market") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = values, color = Indic_bt)) +
  scale_color_manual(values = viridis(4)[1:3]) +
  scale_x_date(breaks = seq(1920, 2025, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%y")) +
  theme(legend.position = c(0.3, 0.85),
        legend.title = element_blank()) +
  scale_y_log10(breaks = seq(-60, 300, 10))

France, Germany, Italy

All

Code 
sts_intv_m %>%
  filter(nace_r2 == "C",
         unit == "I15",
         s_adj == "SCA",
         indic_bt == "TOVT",
         geo %in% c("FR", "DE", "IT")) %>%
  select(geo, time, values) %>%
  group_by(geo) %>%
  mutate(values = 100*values/values[time == "2000M01"]) %>%
  left_join(geo, by = "geo") %>%
  mutate(Geo = ifelse(geo == "DE", "Germany", Geo)) %>%
  month_to_date %>%
  ggplot() + ylab("Index of turnover - Non domestic market") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = values, color = Geo)) +
  scale_color_manual(values = c("#0055a4", "#000000", "#008c45")) +
  scale_x_date(breaks = seq(1920, 2025, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%y")) +
  geom_image(data = . %>%
               filter(date == as.Date("2014-01-01")) %>%
               mutate(image = paste0("../../icon/flag/", str_to_lower(Geo), ".png")),
             aes(x = date, y = values, image = image), asp = 1.5) +
  theme(legend.position = "none") +
  scale_y_log10(breaks = seq(-60, 300, 10))

1995-

Code 
sts_intv_m %>%
  filter(nace_r2 == "C",
         unit == "I15",
         s_adj == "SCA",
         indic_bt == "TOVT",
         geo %in% c("FR", "DE", "IT")) %>%
  select(geo, time, values) %>%
  group_by(geo) %>%
  mutate(values = 100*values/values[time == "2000M01"]) %>%
  left_join(geo, by = "geo") %>%
  mutate(Geo = ifelse(geo == "DE", "Germany", Geo)) %>%
  month_to_date %>%
  filter(date >= as.Date("1995-01-01")) %>%
  ggplot() + ylab("Index of turnover - Non domestic market") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = values, color = Geo)) +
  scale_color_manual(values = c("#0055a4", "#000000", "#008c45")) +
  scale_x_date(breaks = seq(1920, 2025, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%y")) +
  geom_image(data = . %>%
               filter(date == as.Date("2014-01-01")) %>%
               mutate(image = paste0("../../icon/flag/", str_to_lower(Geo), ".png")),
             aes(x = date, y = values, image = image), asp = 1.5) +
  theme(legend.position = "none") +
  scale_y_log10(breaks = seq(-60, 300, 5))

2000-

Code 
sts_intv_m %>%
  filter(nace_r2 == "C",
         unit == "I15",
         s_adj == "SCA",
         indic_bt == "TOVT",
         geo %in% c("FR", "DE", "IT")) %>%
  select(geo, time, values) %>%
  group_by(geo) %>%
  mutate(values = 100*values/values[time == "2000M01"]) %>%
  left_join(geo, by = "geo") %>%
  mutate(Geo = ifelse(geo == "DE", "Germany", Geo)) %>%
  month_to_date %>%
  filter(date >= as.Date("2000-01-01")) %>%
  ggplot() + ylab("Index of turnover - Non domestic market") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = values, color = Geo)) +
  scale_color_manual(values = c("#0055a4", "#000000", "#008c45")) +
  scale_x_date(breaks = seq(1920, 2025, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%y")) +
  geom_image(data = . %>%
               filter(date == as.Date("2014-01-01")) %>%
               mutate(image = paste0("../../icon/flag/", str_to_lower(Geo), ".png")),
             aes(x = date, y = values, image = image), asp = 1.5) +
  theme(legend.position = "none") +
  scale_y_log10(breaks = seq(-60, 300, 5))