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Prices

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Prices

Tabel 1: Consumer Price Index by time and index

PRXPRISF_raw <- 
  statgl_url("PRXPRISF", lang = language) %>% 
  statgl_fetch(
    time      = px_all(),
    index     = 4,
    .col_code = TRUE
  ) %>% 
  as_tibble()

PRXPRISF <- 
  PRXPRISF_raw %>% 
  drop_na() %>% 
  separate(time, c("year", "month"), sep = " ") %>% 
  filter(month == (PRXPRISF_raw %>% pull(time) %>% word(2))[1]) %>% 
  mutate(month = month %>% str_to_sentence()) %>% 
  spread(index, value)

PRXPRISF %>% 
  select(-month) %>% 
  rename(" " = 1) %>% 
  statgl_table()

	Jan 2008=100
2008	100
2009	104
2010	105
2011	107
2012	112
2013	114
2014	115
2015	117
2016	118
2017	119
2018	119
2019	120
2020	123
2021	123
2022	124
2023	127
2024	130
2025	134

See the table in our Statbank: PRXPRISF

Tabel 2: Consumer price index by time and type

PRXPRISH_raw <- 
  statgl_url("PRXPRISH", lang = language) %>%
  statgl_fetch(
    time      = px_top(21),
    type      = px_all(),
    .col_code = TRUE
  ) %>% 
  as_tibble()

PRXPRISH <-
  PRXPRISH_raw %>% 
  separate(time, c("year", "month"), sep = " ") %>% 
  arrange(desc(year), month) %>% 
  mutate(
    year = year %>% fct_inorder(),
    month = month %>% fct_inorder()
  ) %>%
  mutate(month = month %>% str_to_sentence()) %>% 
  spread(month, value) 

PRXPRISH %>% 
  select(-type) %>% 
  rename(" " = 1) %>% 
  statgl_table(replace_0s = TRUE) %>% 
  pack_rows(index = PRXPRISH[["type"]] %>% table())

	January	July
Rate of change from the same period the previous year
1981	13,3	NA
1980	12,5	11,0
1979	7,5	9,8
1978	9,3	8,9
1977	7,0	8,1
1976	13,2	10,0
1975	16,4	14,5
1974	15,6	16,6
1973	7,7	11,8
1972	5,7	6,3
1971	NA	NA

See the table in our Statbank: PRXPRISH

Tabel 3: Consumer price index (2008=100) by commodity group and time

PRXPRISV_raw <- 
  statgl_url("PRXPRISV", lang = language) %>% 
  statgl_fetch(
    "commodity group" = px_all(),
    time              = px_top(5),
    .col_code         = TRUE
  ) %>% 
  as_tibble()

PRXPRISV <- 
  PRXPRISV_raw %>% 
  arrange(time) %>% 
  mutate(
    time = time %>% fct_inorder(),
    `commodity group` = `commodity group` %>% trimws() %>% fct_inorder()
    ) %>% 
  spread(time, value)

PRXPRISV %>% 
  rename(" " = 1) %>% 
  statgl_table() %>% 
  row_spec(1, bold = TRUE)

	2008 Jan	2008 Jul	2009 Jan	2009 Jul	2010 Jan
All goods and services	100	103,0	103,5	103,9	105,0
Food etc.	100	105,3	106,0	108,9	111,0
Bread and cereals	100	107,5	109,5	111,5	109,8
Meat	100	106,9	106,5	109,4	110,9
Fish	100	101,8	101,3	104,8	109,7
Milk, cream, cheese and eggs	100	104,9	104,5	103,8	106,6
Butter, margarine, oils and fats	100	104,7	115,7	117,6	122,2
Fruit	100	105,6	103,2	106,6	105,1
Vegetables	100	109,6	110,0	107,3	111,9
Sugar, jam, honey, chocolate and confectionery	100	107,9	108,8	110,1	113,0
Foodproducts n.e.c.	100	108,9	107,7	109,3	110,0
Coffee, tee and cocoa	100	101,5	106,4	106,1	107,2
Mineral waters, soft drinks, fruit and vegetable juices	100	104,1	107,3	114,0	114,4
Alcohol and tobacco	100	104,2	104,2	105,0	105,6
Alcohol	100	104,9	104,9	106,0	107,0
Tobacco	100	103,4	103,4	104,0	104,0
Clothing and footwear	100	102,6	103,1	100,2	101,8
Housing	100	103,9	104,9	105,1	105,9
Furnishing and household services	100	102,6	102,1	114,3	111,5
Medicine, pharmaceutical articles	100	102,0	102,0	104,4	106,2
Transportation	100	102,7	103,7	103,8	104,9
Telephone and postage	100	94,8	94,8	95,0	95,0
Leisure and culture	100	102,0	101,5	99,0	99,3
Restaurants and hotels	100	99,2	100,5	100,6	101,1
Other goods and services	100	100,8	105,0	96,2	98,4

See the table in our Statbank: PRXPRISV

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Last updated: 10. november 2025