Consumption - CONSUMPTION

Data - ec

sector

Code
CONSUMPTION %>%
  group_by(sector, Sector) %>%
  summarise(Nobs = n()) %>%
  print_table_conditional
sector Sector Nobs
TOT TOTAL Consumer 322734

question

Code
CONSUMPTION %>%
  group_by(question, Questions) %>%
  summarise(Nobs = n()) %>%
  print_table_conditional
question Questions Nobs
1 Financial situation over last 12 months 23419
10 Savings at present 22597
11 Savings over next 12 months 23162
12 Statement on financial situation of household 23169
13 Intention to buy a car within the next 12 months 6934
14 Purchase or build a home within the next 12 months 6864
15 Home improvements over the next 12 months 6926
2 Financial situation over next 12 months 23419
3 General economic situation over last 12 months 23419
4 General economic situation over next 12 months 23419
5 Price trends over last 12 months 23172
6 Price trends over next 12 months 23172
7 Unemployment expectations over next 12 months 23374
8 Major purchases at present 23334
9 Major purchases over next 12 months 23177
COF Confidence Indicator (Q1 + Q2 + Q4 + Q9) / 4 23177

answers

Code
CONSUMPTION %>%
  group_by(answers, Answers) %>%
  summarise(Nobs = n()) %>%
  print_table_conditional
answers Answers Nobs
B Balance not seasonally adjusted (n.s.a) 161890
BS Balance seasonally adjusted (s.a) 160844

country

Code
CONSUMPTION %>%
  group_by(country, Country) %>%
  summarise(Nobs = n()) %>%
  mutate(Flag = gsub(" ", "-", str_to_lower(gsub(" ", "-", Country))),
         Flag = paste0('<img src="../../icon/flag/vsmall/', Flag, '.png" alt="Flag">')) %>%
  select(Flag, everything()) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F, escape = F) else .}

freq

Code
CONSUMPTION %>%
  group_by(freq, Frequency) %>%
  summarise(Nobs = n()) %>%
  print_table_conditional
freq Frequency Nobs
M Monthly 302010
Q Quarterly 20724

Germany

Home improvements, Intention to buy a car, Purchase or build a home

Code
CONSUMPTION %>%
  filter(country == "DE",
         question %in% c("13", "14", "15"),
         answers == "B") %>%
  ggplot + theme_minimal() + xlab("") + ylab("Balance not seasonally adjusted (s.a)") +
  geom_line(aes(x = period, y = value, color = Questions)) +
  scale_color_manual(values = viridis(4)[1:3]) +
  scale_x_date(breaks = as.Date(paste0(seq(1960, 2020, 2), "-01-01")),
               labels = date_format("%y")) +
  theme(legend.position = c(0.8, 0.1),
        legend.title = element_blank()) +
  scale_y_continuous(breaks = seq(-200, 60, 10))