Turnover and volume of sales in wholesale and retail trade - quarterly data - sts_trtu_q

Data - Eurostat

Author

nace_r2

Code

sts_trtu_q %>%
  left_join(nace_r2, by = "nace_r2") %>%
  group_by(nace_r2, Nace_r2) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}

s_adj

Code

sts_trtu_q %>%
  left_join(s_adj, by = "s_adj") %>%
  group_by(s_adj, S_adj) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  {if (is_html_output()) print_table(.) else .}

s_adj	S_adj	Nobs
SCA	Seasonally and calendar adjusted data	552134
CA	Calendar adjusted data, not seasonally adjusted data	550825
NSA	Unadjusted data (i.e. neither seasonally adjusted nor calendar adjusted data)	341066

unit

Code

sts_trtu_q %>%
  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	452197
I21	Index, 2021=100	387490
I10	Index, 2010=100	275617
PCH_PRE	Percentage change on previous period	167045
PCH_SM	Percentage change compared to same period in previous year	161676

indic_bt

Code

sts_trtu_q %>%
  left_join(indic_bt, by = "indic_bt") %>%
  group_by(indic_bt, Indic_bt) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  {if (is_html_output()) print_table(.) else .}

indic_bt	Indic_bt	Nobs
TOVT	Index of turnover - Total	812569
TOVV	Index of deflated turnover	631456

geo

Code

sts_trtu_q %>%
  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_trtu_q %>%
  group_by(time) %>%
  summarise(Nobs = n()) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}

Turnover and volume of sales in wholesale and retail trade

France, Germany, Italy

All

Code

sts_trtu_q %>%
  filter(nace_r2 == "G47",
         unit == "I15",
         indic_bt == "TOVV",
         geo %in% c("FR", "DE", "IT"),
         s_adj == "SCA") %>%
  select(geo, time, values) %>%
  group_by(geo) %>%
  left_join(geo, by = "geo") %>%
  mutate(Geo = ifelse(geo == "DE", "Germany", Geo)) %>%
  quarter_to_date %>%
  ggplot() + ylab("Retail trade, except of motor vehicles and motorcycles") + 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")) +
  add_3flags + 
  theme(legend.position = "none") +
  scale_y_log10(breaks = seq(-60, 300, 10))

2010-

Code

sts_trtu_q %>%
  filter(nace_r2 == "G47",
         unit == "I15",
         indic_bt == "TOVV",
         geo %in% c("FR", "DE", "IT"),
         s_adj == "SCA") %>%
  select(geo, time, values) %>%
  group_by(geo) %>%
  left_join(geo, by = "geo") %>%
  mutate(Geo = ifelse(geo == "DE", "Germany", Geo)) %>%
  quarter_to_date %>%
  filter(date >= as.Date("2010-01-01")) %>%
  ggplot() + ylab("Retail trade, except of motor vehicles and motorcycles - Since 2010") + 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")) +
  add_3flags + 
  theme(legend.position = "none") +
  scale_y_log10(breaks = seq(-60, 300, 10))