Prices, Consumer Price Index, All items, Percentage change, Corresponding period previous year, Percent

Data - IMF - IFS

Author

François Geerolf

FREQ

Code 
PCPI_PC_CP_A_PT %>%
  group_by(FREQ) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  print_table_conditional()
FREQ Nobs
M 100658
Q 36292
A 9453

REF_AREA

All

Code 
PCPI_PC_CP_A_PT %>%
  left_join(REF_AREA, by = "REF_AREA") %>%
  group_by(REF_AREA, Ref_area) %>%
  summarise(Nobs = n(),
            min = first(TIME_PERIOD),
            max = last(TIME_PERIOD)) %>%
  arrange(-Nobs) %>%
  mutate(Flag = gsub(" ", "-", str_to_lower(gsub(" ", "-", Ref_area))),
         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 .}

Monthly

Code 
PCPI_PC_CP_A_PT %>%
  filter(FREQ == "M") %>%
  left_join(REF_AREA, by = "REF_AREA") %>%
  group_by(REF_AREA, Ref_area) %>%
  summarise(Nobs = n(),
            min = first(TIME_PERIOD),
            max = last(TIME_PERIOD)) %>%
  arrange(-Nobs) %>%
  mutate(Flag = gsub(" ", "-", str_to_lower(gsub(" ", "-", Ref_area))),
         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 .}

Quarterly

Code 
PCPI_PC_CP_A_PT %>%
  filter(FREQ == "Q") %>%
  left_join(REF_AREA, by = "REF_AREA") %>%
  group_by(REF_AREA, Ref_area) %>%
  summarise(Nobs = n(),
            min = first(TIME_PERIOD),
            max = last(TIME_PERIOD)) %>%
  arrange(-Nobs) %>%
  mutate(Flag = gsub(" ", "-", str_to_lower(gsub(" ", "-", Ref_area))),
         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 .}

Annual

Code 
PCPI_PC_CP_A_PT %>%
  filter(FREQ == "A") %>%
  left_join(REF_AREA, by = "REF_AREA") %>%
  group_by(REF_AREA, Ref_area) %>%
  summarise(Nobs = n(),
            min = first(TIME_PERIOD),
            max = last(TIME_PERIOD)) %>%
  arrange(-Nobs) %>%
  mutate(Flag = gsub(" ", "-", str_to_lower(gsub(" ", "-", Ref_area))),
         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 .}

New Zealand

All

Code 
PCPI_PC_CP_A_PT %>%
  filter(REF_AREA %in% c("NZ"),
         FREQ == "A") %>%
  year_to_date2() %>%
  transmute(date, value = OBS_VALUE/100, variable = "Inflation") %>%
  bind_rows(CBPOL_M %>%
              filter(REF_AREA %in% c("NZ"),
                     FREQ == "M") %>%
              transmute(date, value = OBS_VALUE/100, variable = "Policy rates")) %>%
  filter(date >= as.Date("1980-01-01")) %>%
  ggplot(.) + theme_minimal() + xlab("") + ylab("") +
  geom_line(aes(x = date, y = value, color = variable)) +
  scale_y_continuous(breaks = 0.01*seq(-100, 300, 5),
                     labels = scales::percent_format(accuracy = 1)) +
  theme(legend.position = c(0.65, 0.85),
        legend.title = element_blank()) +
  scale_x_date(breaks = as.Date(paste0(seq(1700, 2030, 5), "-01-01")),
               labels = date_format("%Y"))

1985-

Code 
PCPI_PC_CP_A_PT %>%
  filter(REF_AREA %in% c("NZ"),
         FREQ == "A") %>%
  year_to_date2() %>%
  transmute(date, value = OBS_VALUE/100, variable = "Inflation") %>%
  bind_rows(CBPOL_M %>%
              filter(REF_AREA %in% c("NZ"),
                     FREQ == "M") %>%
              transmute(date, value = OBS_VALUE/100, variable = "Policy rates")) %>%
  filter(date >= as.Date("1985-01-01")) %>%
  ggplot(.) + theme_minimal() + xlab("") + ylab("") +
  geom_line(aes(x = date, y = value, color = variable)) +
  scale_y_continuous(breaks = 0.01*seq(-100, 300, 5),
                     labels = scales::percent_format(accuracy = 1)) +
  theme(legend.position = c(0.65, 0.85),
        legend.title = element_blank()) +
  scale_x_date(breaks = as.Date(paste0(seq(1700, 2030, 5), "-01-01")),
               labels = date_format("%Y"))

France, Germany, Italy, United States

Code 
PCPI_PC_CP_A_PT %>%
  filter(REF_AREA %in% c("FR", "DE", "IT", "US"),
         FREQ == "M") %>%
  left_join(REF_AREA, by = "REF_AREA") %>%
  month_to_date2() %>%
  ggplot(.) + theme_minimal() +
  geom_line(aes(x = date, y = OBS_VALUE / 100, color = Ref_area, linetype = Ref_area)) +
  scale_y_continuous(breaks = 0.01*seq(-100, 300, 5),
                     labels = scales::percent_format(accuracy = 1)) +
  scale_color_manual(values = viridis(5)[1:4]) +
  theme(legend.position = c(0.65, 0.85),
        legend.title = element_blank()) +
  scale_x_date(breaks = as.Date(paste0(seq(1700, 2030, 5), "-01-01")),
               labels = date_format("%y")) + 
  xlab("") + ylab("Inflation Rates")

Japan, Canada, Australia, UK

Code 
PCPI_PC_CP_A_PT %>%
  filter(REF_AREA %in% c("JP", "CA", "AU", "GB"),
         FREQ == "M") %>%
  left_join(REF_AREA, by = "REF_AREA") %>%
  month_to_date2() %>%
  ggplot(.) + theme_minimal() +
  geom_line(aes(x = date, y = OBS_VALUE / 100, color = Ref_area, linetype = Ref_area)) +
  scale_y_continuous(breaks = 0.01*seq(-100, 300, 5),
                     labels = scales::percent_format(accuracy = 1)) +
  scale_color_manual(values = viridis(5)[1:4]) +
  theme(legend.position = c(0.65, 0.85),
        legend.title = element_blank()) +
  scale_x_date(breaks = as.Date(paste0(seq(1700, 2030, 5), "-01-01")),
               labels = date_format("%y")) + 
  xlab("") + ylab("Inflation Rates")

Spain, Austria, Norway, Sweden

Code 
PCPI_PC_CP_A_PT %>%
  filter(REF_AREA %in% c("ES", "AT", "NO", "SE"),
         FREQ == "M") %>%
  left_join(REF_AREA, by = "REF_AREA") %>%
  month_to_date2() %>%
  ggplot(.) + theme_minimal() +
  geom_line(aes(x = date, y = OBS_VALUE / 100, color = Ref_area, linetype = Ref_area)) +
  scale_y_continuous(breaks = 0.01*seq(-100, 300, 5),
                     labels = scales::percent_format(accuracy = 1)) +
  scale_color_manual(values = viridis(5)[1:4]) +
  theme(legend.position = c(0.65, 0.85),
        legend.title = element_blank()) +
  scale_x_date(breaks = as.Date(paste0(seq(1700, 2030, 5), "-01-01")),
               labels = date_format("%y")) + 
  xlab("") + ylab("Inflation Rates")

Ireland, Greece, Denmark, Iceland

Code 
PCPI_PC_CP_A_PT %>%
  filter(REF_AREA %in% c("IE", "GR", "DK", "IS"),
         FREQ == "M") %>%
  left_join(REF_AREA, by = "REF_AREA") %>%
  month_to_date2() %>%
  ggplot(.) + theme_minimal() +
  geom_line(aes(x = date, y = OBS_VALUE / 100, color = Ref_area, linetype = Ref_area)) +
  scale_y_continuous(breaks = 0.01*seq(-100, 300, 5),
                     labels = scales::percent_format(accuracy = 1)) +
  scale_color_manual(values = viridis(5)[1:4]) +
  theme(legend.position = c(0.65, 0.85),
        legend.title = element_blank()) +
  scale_x_date(breaks = as.Date(paste0(seq(1700, 2030, 5), "-01-01")),
               labels = date_format("%y")) + 
  xlab("") + ylab("Inflation Rates")