Indices of Consumer prices - ICP

Data - ECB

Last observation: Q4 2025 (N = 963) · déc. 2025 (N = 24836) · 2025 (N = 26052)

First observation: 1986 (N = 1) · janv. 1987 (N = 6) · Q1 2005 (N = 52)

Last data update: 01 sept. 2026, 02:08

Last compile: 02 sept. 2026, 23:12

Structure

Info

Housing

Greece

Code
ICP |>
  filter(REF_AREA %in% c("GR"),
         ICP_ITEM %in% c("HOUSE0", "041000", "040000"),
         ICP_SUFFIX == "INX") |>
  month_to_date() |>
  filter(!is.na(OBS_VALUE)) |>
  ggplot() +  ylab("HICP - Overall index") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = OBS_VALUE, color = Icp_item)) +
  
  theme(legend.position = c(0.65, 0.15),
        legend.title = element_blank()) +
  scale_x_date(breaks = seq(1920, 2100, 2) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  scale_y_log10(breaks = seq(0, 200, 5),
                     labels = dollar_format(accuracy = 1, prefix = ""))

Spain

Code
ICP |>
  filter(REF_AREA %in% c("ES"),
         ICP_ITEM %in% c("HOUSE0", "041000", "040000"),
         ICP_SUFFIX == "INX") |>
  month_to_date() |>
  filter(!is.na(OBS_VALUE)) |>
  ggplot() +  ylab("HICP - Overall index") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = OBS_VALUE, color = Icp_item)) + 
  
  theme(legend.position = c(0.65, 0.15),
        legend.title = element_blank()) +
  scale_x_date(breaks = seq(1920, 2100, 2) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  scale_y_log10(breaks = seq(0, 200, 5),
                     labels = dollar_format(accuracy = 1, prefix = ""))

France

Code
ICP |>
  filter(REF_AREA %in% c("FR"),
         ICP_ITEM %in% c("HOUSE0", "041000", "040000"),
         ICP_SUFFIX == "INX") |>
  month_to_date() |>
  filter(!is.na(OBS_VALUE)) |>
  ggplot() +  ylab("HICP - Overall index") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = OBS_VALUE, color = Icp_item)) +
  
  theme(legend.position = c(0.65, 0.15),
        legend.title = element_blank()) +
  scale_x_date(breaks = seq(1920, 2100, 2) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  scale_y_log10(breaks = seq(0, 200, 5),
                     labels = dollar_format(accuracy = 1, prefix = ""))

Harmonised Index of Consumer Prices - HICP

Euro area Broad Indexes (1960-)

Code
ICP |>
  filter(REF_AREA %in% c("U2"),
         # 000000: HICP - Overall index
         # XEF000: HICP - All-items excluding energy and food
         ICP_ITEM %in% c("000000", "XEF000", "XE0000"),
         # ANR: Annual Rate of Change
         ICP_SUFFIX == "ANR",
         FREQ == "M") |>
  month_to_date() |>
  filter(!is.na(OBS_VALUE)) |>
  ggplot() + theme_minimal() + ylab("HICP - Broad indexes") + xlab("") +
  geom_line(aes(x = date, y = OBS_VALUE/100, color = TITLE)) + 
  
  scale_x_date(breaks = seq(1920, 2100, 2) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  theme(legend.position = c(0.75, 0.9),
        legend.title = element_blank()) +
  scale_y_continuous(breaks = 0.01*seq(0, 200, 1),
                labels = percent_format(accuracy = 1))

Euro area Broad Indexes (1996-)

Code
ICP |>
  filter(REF_AREA %in% c("U2"),
         # 000000: HICP - Overall index
         # XEF000: HICP - All-items excluding energy and food
         ICP_ITEM %in% c("000000", "XEF000", "XE0000"),
         # ANR: Annual Rate of Change
         ICP_SUFFIX == "ANR",
         FREQ == "M") |>
  month_to_date() |>
  filter(!is.na(OBS_VALUE),
         date >= as.Date("1996-01-01")) |>
  ggplot() + theme_minimal() + ylab("HICP - Broad indexes") + xlab("") +
  geom_line(aes(x = date, y = OBS_VALUE/100, color = TITLE)) + 
  scale_x_date(breaks = seq(1920, 2100, 2) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  theme(legend.position = c(0.75, 0.9),
        legend.title = element_blank()) +
  scale_y_continuous(breaks = 0.01*seq(0, 200, 1),
                labels = percent_format(accuracy = 1))

Euro area Broad Indexes (2008-)

Code
ICP |>
  filter(REF_AREA %in% c("U2"),
         # 000000: HICP - Overall index
         # XEF000: HICP - All-items excluding energy and food
         ICP_ITEM %in% c("000000", "XEF000", "XE0000"),
         # ANR: Annual Rate of Change
         ICP_SUFFIX == "ANR",
         FREQ == "M") |>
  month_to_date() |>
  filter(!is.na(OBS_VALUE),
         date >= as.Date("2007-01-01")) |>
  ggplot() + theme_minimal() + ylab("HICP - Broad indexes") + xlab("") +
  geom_line(aes(x = date, y = OBS_VALUE/100, color = KEY)) + 
  scale_x_date(breaks = seq(1920, 2100, 2) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  theme(legend.position = c(0.75, 0.9),
        legend.title = element_blank()) +
  scale_y_continuous(breaks = 0.01*seq(0, 200, 1),
                labels = percent_format(accuracy = 1))

Spain Broad Indexes

1996-2021

Code
ICP |>
  filter(REF_AREA %in% c("ES"),
         # 000000: HICP - Overall index
         # XEF000: HICP - All-items excluding energy and food
         ICP_ITEM %in% c("000000", "XEF000", "XE0000"),
         # ANR: Annual Rate of Change
         ICP_SUFFIX == "ANR",
         FREQ == "M") |>
  month_to_date() |>
  filter(!is.na(OBS_VALUE),
         date >= as.Date("1996-01-01")) |>
  ggplot() + theme_minimal() + ylab("HICP - Broad indexes") + xlab("") +
  geom_line(aes(x = date, y = OBS_VALUE/100, color = TITLE)) + 
  
  geom_hline(yintercept = 0.02, linetype = "dashed",  color = "black") +
  geom_hline(yintercept = 0, linetype = "dashed",  color = "black") +
  scale_x_date(breaks = seq(1920, 2100, 2) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  theme(legend.position = c(0.2, 0.9),
        legend.title = element_blank()) +
  scale_y_continuous(breaks = 0.01*seq(-100, 200, 0.5),
                labels = percent_format(accuracy = 0.1))

2010-2013

Code
ICP |>
  filter(REF_AREA %in% c("ES"),
         # 000000: HICP - Overall index
         # XEF000: HICP - All-items excluding energy and food
         ICP_ITEM %in% c("000000", "XEF000", "XE0000"),
         # ANR: Annual Rate of Change
         ICP_SUFFIX == "ANR",
         FREQ == "M") |>
  month_to_date() |>
  filter(!is.na(OBS_VALUE),
         date >= as.Date("2010-01-01"),
         date <= as.Date("2014-01-01")) |>
  ggplot() + theme_minimal() + ylab("HICP - Broad indexes") + xlab("") +
  geom_line(aes(x = date, y = OBS_VALUE/100, color = TITLE)) + 
  
  geom_hline(yintercept = 0.02, linetype = "dashed",  color = "black") +
  geom_hline(yintercept = 0, linetype = "dashed",  color = "black") +
  scale_x_date(breaks = seq(1920, 2100, 1) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  theme(legend.position = c(0.5, 0.11),
        legend.title = element_blank()) +
  scale_y_continuous(breaks = 0.01*seq(-100, 200, 0.5),
                labels = percent_format(accuracy = 0.1))

Greece

2010-2013

Code
ICP |>
  filter(REF_AREA %in% c("GR"),
         # 000000: HICP - Overall index
         # XEF000: HICP - All-items excluding energy and food
         ICP_ITEM %in% c("000000", "XEF000", "XE0000"),
         # ANR: Annual Rate of Change
         ICP_SUFFIX == "ANR",
         FREQ == "M") |>
  month_to_date() |>
  filter(!is.na(OBS_VALUE),
         date >= as.Date("2010-01-01"),
         date <= as.Date("2014-01-01")) |>
  ggplot() + theme_minimal() + ylab("HICP - Broad indexes") + xlab("") +
  geom_line(aes(x = date, y = OBS_VALUE/100, color = TITLE)) + 
  
  geom_hline(yintercept = 0.02, linetype = "dashed",  color = "black") +
  geom_hline(yintercept = 0, linetype = "dashed",  color = "black") +
  scale_x_date(breaks = seq(1920, 2100, 1) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  theme(legend.position = c(0.2, 0.9),
        legend.title = element_blank()) +
  scale_y_continuous(breaks = 0.01*seq(-100, 200, 0.5),
                labels = percent_format(accuracy = 0.1))

Germany Broad Indexes

1996-2021

Code
ICP |>
  filter(REF_AREA %in% c("DE"),
         # 000000: HICP - Overall index
         # XEF000: HICP - All-items excluding energy and food
         ICP_ITEM %in% c("000000", "XEF000", "XE0000"),
         # ANR: Annual Rate of Change
         ICP_SUFFIX == "ANR",
         FREQ == "M") |>
  month_to_date() |>
  filter(!is.na(OBS_VALUE),
         date >= as.Date("1996-01-01")) |>
  ggplot() + theme_minimal() + ylab("HICP - Broad indexes") + xlab("") +
  geom_line(aes(x = date, y = OBS_VALUE/100, color = TITLE)) + 
  
  geom_hline(yintercept = 0.02, linetype = "dashed",  color = "black") +
  geom_hline(yintercept = 0, linetype = "dashed",  color = "black") +
  scale_x_date(breaks = seq(1920, 2100, 2) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  theme(legend.position = c(0.2, 0.9),
        legend.title = element_blank()) +
  scale_y_continuous(breaks = 0.01*seq(-100, 200, 0.5),
                labels = percent_format(accuracy = 0.1))

Annual - Euro area Broad Indexes

1996-2021

Code
ICP |>
  filter(REF_AREA %in% c("U2"),
         # 000000: HICP - Overall index
         # XEF000: HICP - All-items excluding energy and food
         ICP_ITEM %in% c("XEFUN0", "XEF000", "XE0000"),
         # ANR: Annual Rate of Change
         ICP_SUFFIX == "INX",
         STS_INSTITUTION == 3,
         FREQ == "M") |>
  month_to_date() |>
  filter(!is.na(OBS_VALUE),
         date >= as.Date("1996-01-01"),
         month(date) == 1) |>
  group_by(ICP_ITEM) |>
  mutate(OBS_VALUE = 100*(OBS_VALUE/lag(OBS_VALUE, 1) - 1)) |>
  select(KEY, ICP_ITEM, Icp_item, date, OBS_VALUE) |>
  na.omit() |>
  ggplot() + theme_minimal() + ylab("HICP - Broad indexes") + xlab("") +
  geom_line(aes(x = date, y = OBS_VALUE/100, color = Icp_item)) + 
  
  geom_hline(yintercept = 0.02, linetype = "dashed",  color = "black") +
  geom_hline(yintercept = 0, linetype = "dashed",  color = "black") +
  scale_x_date(breaks = seq(1920, 2100, 2) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  theme(legend.position = c(0.75, 0.9),
        legend.title = element_blank()) +
  scale_y_continuous(breaks = 0.01*seq(0, 200, 0.5),
                labels = percent_format(accuracy = 0.1))

Monthly - Euro area Broad Indexes

1996-2021

Code
ICP |>
  filter(REF_AREA %in% c("U2"),
         # 000000: HICP - Overall index
         # XEF000: HICP - All-items excluding energy and food
         ICP_ITEM %in% c("XEFUN0", "XEF000", "XE0000"),
         # ANR: Annual Rate of Change
         ICP_SUFFIX == "ANR",
         FREQ == "M") |>
  month_to_date() |>
  filter(!is.na(OBS_VALUE),
         date >= as.Date("1996-01-01")) |>
  ggplot() + theme_minimal() + ylab("HICP - Broad indexes") + xlab("") +
  geom_line(aes(x = date, y = OBS_VALUE/100, color = TITLE, linetype = TITLE)) + 
  
  geom_hline(yintercept = 0.02, linetype = "dashed",  color = "black") +
  geom_hline(yintercept = 0, linetype = "dashed",  color = "black") +
  scale_x_date(breaks = seq(1920, 2100, 2) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  theme(legend.position = c(0.75, 0.9),
        legend.title = element_blank()) +
  scale_y_continuous(breaks = 0.01*seq(0, 200, 0.5),
                labels = percent_format(accuracy = 0.1))

2009-2021

Code
ICP |>
  filter(REF_AREA %in% c("U2"),
         # 000000: HICP - Overall index
         # XEF000: HICP - All-items excluding energy and food
         ICP_ITEM %in% c("XEFUN0", "XEF000", "XE0000"),
         # ANR: Annual Rate of Change
         ICP_SUFFIX == "ANR",
         FREQ == "M") |>
  month_to_date() |>
  filter(!is.na(OBS_VALUE),
         date >= as.Date("2009-01-01")) |>
  ggplot() + theme_minimal() + ylab("HICP - Broad indexes") + xlab("") +
  geom_line(aes(x = date, y = OBS_VALUE/100, color = TITLE, linetype = TITLE)) + 
  
  geom_hline(yintercept = 0.02, linetype = "dashed",  color = "black") +
  geom_hline(yintercept = 0, linetype = "dashed",  color = "black") +
  scale_x_date(breaks = seq(1920, 2100, 1) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  theme(legend.position = c(0.75, 0.9),
        legend.title = element_blank()) +
  scale_y_continuous(breaks = 0.01*seq(0, 200, 0.5),
                labels = percent_format(accuracy = 0.1))

2009-2014

Code
ICP |>
  filter(REF_AREA %in% c("U2"),
         # 000000: HICP - Overall index
         # XEF000: HICP - All-items excluding energy and food
         ICP_ITEM %in% c("XEFUN0", "000000", "XE0000"),
         # ANR: Annual Rate of Change
         ICP_SUFFIX == "ANR",
         FREQ == "M") |>
  month_to_date() |>
  filter(!is.na(OBS_VALUE),
         date >= as.Date("2009-01-01"),
         date <= as.Date("2014-12-31")) |>
  ggplot() + theme_minimal() + ylab("HICP - Broad indexes") + xlab("") +
  geom_line(aes(x = date, y = OBS_VALUE/100, color = TITLE, linetype = TITLE)) + 
  
  geom_hline(yintercept = 0.02, linetype = "dashed",  color = "black") +
  scale_x_date(breaks = seq(1920, 2100, 1) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  theme(legend.position = c(0.6, 0.2),
        legend.title = element_blank()) +
  scale_y_continuous(breaks = 0.01*seq(0, 200, 0.5),
                labels = percent_format(accuracy = 0.1)) + 
  geom_vline(xintercept = as.Date("2011-04-07"), linetype = "dashed", color = "black") + 
  geom_vline(xintercept = as.Date("2011-07-07"), linetype = "dashed", color = "black")

2013-2021

Code
ICP |>
  filter(REF_AREA %in% c("U2"),
         # 000000: HICP - Overall index
         # XEF000: HICP - All-items excluding energy and food
         ICP_ITEM %in% c("XEFUN0", "000000", "XE0000"),
         # ANR: Annual Rate of Change
         ICP_SUFFIX == "ANR",
         FREQ == "M") |>
  month_to_date() |>
  filter(!is.na(OBS_VALUE),
         date >= as.Date("2013-01-01"),
         date <= as.Date("2021-12-31")) |>
  ggplot() + theme_minimal() + ylab("HICP - Broad indexes") + xlab("") +
  geom_line(aes(x = date, y = OBS_VALUE/100, color = TITLE)) + 
  
  geom_hline(yintercept = 0.02, linetype = "dashed",  color = "black") +
  scale_x_date(breaks = seq(1920, 2100, 1) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  theme(legend.position = c(0.3, 0.9),
        legend.title = element_blank()) +
  scale_y_continuous(breaks = 0.01*seq(0, 200, 0.5),
                labels = percent_format(accuracy = 0.1)) + 
  geom_vline(xintercept = as.Date("2011-04-07"), linetype = "dashed", color = "black") + 
  geom_vline(xintercept = as.Date("2011-07-07"), linetype = "dashed", color = "black")

Euro area - Long

Code
ICP |>
  filter(REF_AREA %in% c("U2"),
         # 000000: HICP - Overall index
         # XEF000: HICP - All-items excluding energy and food
         ICP_ITEM %in% c("000000"),
         # ANR: Annual Rate of Change
         ICP_SUFFIX == "ANR",
         FREQ == "M") |>
  month_to_date() |>
  filter(!is.na(OBS_VALUE)) |>
  ggplot() + theme_minimal() + ylab("HICP - Overall index") + xlab("") +
  geom_line(aes(x = date, y = OBS_VALUE/100, color = TITLE, linetype = TITLE)) +
  geom_hline(yintercept = 0.02, linetype = "dashed",  color = viridis(3)[2]) +
  scale_x_date(breaks = seq(1920, 2100, 5) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  theme(legend.position = c(0.75, 0.8),
        legend.title = element_blank()) +
  scale_y_continuous(breaks = 0.01*seq(0, 200, 2),
                labels = percent_format(accuracy = 1))

Germany, France, United Kinggom

Code
ICP |>
  filter(REF_AREA %in% c("DE", "FR", "GB"),
         # 000000: HICP - Overall index
         ICP_ITEM == "000000",
         FREQ == "M",
         UNIT_INDEX_BASE == "2015 = 100") |>
  month_to_date() |>
  filter(!is.na(OBS_VALUE)) |>
  ggplot() + 
  geom_line(aes(x = date, y = OBS_VALUE, color = Ref_area)) + 
  
  theme_minimal() +
  scale_x_date(breaks = seq(1920, 2100, 2) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  theme(legend.position = c(0.75, 0.3),
        legend.title = element_blank()) +
  scale_y_log10(breaks = seq(0, 200, 5),
                     labels = dollar_format(accuracy = 1, prefix = "")) +
  ylab("HICP - Overall index") + xlab("")

Decomposition between Services and Goods

France

Monthly

Code
ICP |>
  filter(REF_AREA %in% c("FR"),
         # 000000: HICP - Overall index
         ICP_ITEM %in% c("SERV00", "041000", "IGXE00"),
         FREQ == "M",
         UNIT_INDEX_BASE == "2015 = 100",
         UNIT == "PURE_NUMB") |>
  month_to_date() |>
  filter(!is.na(OBS_VALUE)) |>
  ggplot() + 
  geom_line(aes(x = date, y = OBS_VALUE, color = Icp_item)) + 
  
  theme_minimal() +
  scale_x_date(breaks = seq(1920, 2100, 2) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  theme(legend.position = c(0.35, 0.85),
        legend.title = element_blank()) +
  scale_y_log10(breaks = seq(0, 200, 5),
                     labels = dollar_format(accuracy = 1, prefix = "")) +
  ylab("HICP - Overall index") + xlab("")

Annual

Code
ICP |>
  filter(REF_AREA %in% c("FR"),
         # 000000: HICP - Overall index
         ICP_ITEM %in% c("SERV00", "041000", "IGXE00"),
         UNIT == "PURE_NUMB",
         FREQ == "A") |>
  year_to_date() |>
  group_by(ICP_ITEM) |>
  mutate(OBS_VALUE = 100*OBS_VALUE/OBS_VALUE[date == as.Date("1996-01-01")]) |>
  ggplot() + ylab("HICP - Overall index") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = OBS_VALUE, color = Icp_item)) + 
  
  scale_x_date(breaks = seq(1920, 2100, 2) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  theme(legend.position = c(0.25, 0.15),
        legend.title = element_blank()) +
  scale_y_log10(breaks = seq(0, 200, 5),
                labels = dollar_format(accuracy = 1, prefix = ""))

Germany

Code
ICP |>
  filter(REF_AREA %in% c("DE"),
         # 000000: HICP - Overall index
         ICP_ITEM %in% c("SERV00", "041000", "IGXE00"),
         FREQ == "M",
         UNIT_INDEX_BASE == "2015 = 100",
         UNIT == "PURE_NUMB") |>
  month_to_date() |>
  filter(!is.na(OBS_VALUE)) |>
  ggplot() + 
  geom_line(aes(x = date, y = OBS_VALUE, color = Icp_item)) + 
  
  theme_minimal() +
  scale_x_date(breaks = seq(1920, 2100, 2) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  theme(legend.position = c(0.35, 0.85),
        legend.title = element_blank()) +
  scale_y_log10(breaks = seq(0, 200, 5),
                     labels = dollar_format(accuracy = 1, prefix = "")) +
  ylab("HICP - Overall index") + xlab("")

Greece

Code
ICP |>
  filter(REF_AREA %in% c("GR"),
         # 000000: HICP - Overall index
         ICP_ITEM %in% c("SERV00", "041000", "IGXE00"),
         FREQ == "M",
         UNIT_INDEX_BASE == "2015 = 100",
         UNIT == "PURE_NUMB") |>
  month_to_date() |>
  filter(!is.na(OBS_VALUE)) |>
  ggplot() + 
  geom_line(aes(x = date, y = OBS_VALUE, color = Icp_item)) + 
  
  theme_minimal() +
  scale_x_date(breaks = seq(1920, 2100, 2) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  theme(legend.position = c(0.35, 0.85),
        legend.title = element_blank()) +
  scale_y_log10(breaks = seq(0, 200, 5),
                     labels = dollar_format(accuracy = 1, prefix = "")) +
  ylab("HICP - Overall index") + xlab("")

Portugal

Code
ICP |>
  filter(REF_AREA %in% c("PT"),
         # 000000: HICP - Overall index
         ICP_ITEM %in% c("SERV00", "041000", "IGXE00"),
         FREQ == "M",
         UNIT_INDEX_BASE == "2015 = 100",
         UNIT == "PURE_NUMB") |>
  month_to_date() |>
  filter(!is.na(OBS_VALUE)) |>
  ggplot() + 
  geom_line(aes(x = date, y = OBS_VALUE, color = Icp_item)) + 
  
  theme_minimal() +
  scale_x_date(breaks = seq(1920, 2100, 2) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  theme(legend.position = c(0.35, 0.85),
        legend.title = element_blank()) +
  scale_y_log10(breaks = seq(0, 200, 5),
                     labels = dollar_format(accuracy = 1, prefix = "")) +
  ylab("HICP - Overall index") + xlab("")

Further Decomposing

Germany

Code
ICP |>
  filter(REF_AREA %in% c("DE"),
         # 000000: HICP - Overall index
         ICP_ITEM %in% c("110000", "120000", "030000", "041000"),
         FREQ == "M",
         UNIT_INDEX_BASE == "2015 = 100",
         UNIT == "PURE_NUMB") |>
  month_to_date() |>
  filter(!is.na(OBS_VALUE)) |>
  ggplot() + 
  geom_line(aes(x = date, y = OBS_VALUE, color = Icp_item)) + 
  
  theme_minimal() +
  scale_x_date(breaks = seq(1920, 2100, 2) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  theme(legend.position = c(0.35, 0.85),
        legend.title = element_blank()) +
  scale_y_log10(breaks = seq(0, 200, 5),
                     labels = dollar_format(accuracy = 1, prefix = "")) +
  ylab("HICP - Overall index") + xlab("")

France

Code
ICP |>
  filter(REF_AREA %in% c("FR"),
         # 000000: HICP - Overall index
         ICP_ITEM %in% c("110000", "120000", "030000", "041000"),
         FREQ == "M",
         UNIT_INDEX_BASE == "2015 = 100",
         UNIT == "PURE_NUMB") |>
  month_to_date() |>
  filter(!is.na(OBS_VALUE)) |>
  ggplot() + 
  geom_line(aes(x = date, y = OBS_VALUE, color = Icp_item)) + 
  
  theme_minimal() +
  scale_x_date(breaks = seq(1920, 2100, 2) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  theme(legend.position = c(0.75, 0.25),
        legend.title = element_blank()) +
  scale_y_log10(breaks = seq(0, 200, 5),
                     labels = dollar_format(accuracy = 1, prefix = "")) +
  ylab("HICP - Overall index") + xlab("")

Greece

Code
ICP |>
  filter(REF_AREA %in% c("GR"),
         # 000000: HICP - Overall index
         ICP_ITEM %in% c("110000", "120000", "030000", "041000"),
         FREQ == "M",
         UNIT_INDEX_BASE == "2015 = 100",
         UNIT == "PURE_NUMB") |>
  month_to_date() |>
  filter(!is.na(OBS_VALUE)) |>
  ggplot() + 
  geom_line(aes(x = date, y = OBS_VALUE, color = Icp_item)) + 
  
  theme_minimal() +
  scale_x_date(breaks = seq(1920, 2100, 2) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  theme(legend.position = c(0.75, 0.25),
        legend.title = element_blank()) +
  scale_y_log10(breaks = seq(0, 200, 5),
                     labels = dollar_format(accuracy = 1, prefix = "")) +
  ylab("HICP - Overall index") + xlab("")

Portugal

Code
ICP |>
  filter(REF_AREA %in% c("PT"),
         # 000000: HICP - Overall index
         ICP_ITEM %in% c("110000", "120000", "030000", "041000"),
         FREQ == "M",
         UNIT_INDEX_BASE == "2015 = 100",
         UNIT == "PURE_NUMB") |>
  month_to_date() |>
  filter(!is.na(OBS_VALUE)) |>
  ggplot() + 
  geom_line(aes(x = date, y = OBS_VALUE, color = Icp_item)) + 
  
  theme_minimal() +
  scale_x_date(breaks = seq(1920, 2100, 2) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  theme(legend.position = c(0.75, 0.25),
        legend.title = element_blank()) +
  scale_y_log10(breaks = seq(0, 200, 5),
                     labels = dollar_format(accuracy = 1, prefix = "")) +
  ylab("HICP - Overall index") + xlab("")

Price of Energy

Code
ICP |>
  filter(REF_AREA %in% c("DE"),
         # 000000: HICP - Overall index
         ICP_ITEM %in% c("NRGY00", "ELGAS0", "045500"),
         FREQ == "M",
         ICP_SUFFIX == "INX") |>
  month_to_date() |>
  filter(!is.na(OBS_VALUE)) |>
  ggplot() + 
  geom_line(aes(x = date, y = OBS_VALUE, color = Icp_item)) + 
  
  theme_minimal() +
  scale_x_date(breaks = seq(1920, 2100, 2) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  theme(legend.position = c(0.75, 0.25),
        legend.title = element_blank()) +
  scale_y_log10(breaks = seq(0, 200, 5),
                     labels = dollar_format(accuracy = 1, prefix = "")) +
  ylab("HICP - Overall index") + xlab("")

Deflation in Greece

Code
ICP |>
  filter(REF_AREA %in% c("GR"),
         FREQ == "M",
         UNIT_INDEX_BASE == "2015 = 100",
         UNIT == "PURE_NUMB") |>
  month_to_date() |>
  filter(!is.na(OBS_VALUE),
         date %in% as.Date(paste0(c(2012, 2014), "-01-01"))) |>
  select(date, ICP_ITEM, TITLE, OBS_VALUE) |>
  group_by(ICP_ITEM, TITLE) |>
  summarise(`% change` = round(100*(OBS_VALUE[2] - OBS_VALUE[1])/OBS_VALUE[1], 1)) |>
  arrange(`% change`) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}