Last observation: juin 2026 (N = 368)
First observation: mai 1914 (N = 1)
Last data update: 01 août 2026, 21:27
Last compile: 14 sept. 2026, 22:11
CPI_NCPD_COI_RT_M |>
left_join(ref_area, by = "ref_area") |>
group_by(ref_area, Ref_area) |>
summarise(Nobs = n()) |>
mutate(Flag = gsub(" ", "-", str_to_lower(Ref_area)),
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 .}CPI_NCPD_COI_RT_M |>
left_join(indicator, by = "indicator") |>
group_by(indicator, Indicator) |>
summarise(Nobs = n()) %>%
{if (is_html_output()) print_table(.) else .}| indicator | Indicator | Nobs |
|---|---|---|
| CPI_NCPD_COI_RT | National consumer price index (CPI) by COICOP, percentage change from previous period (%) | 486669 |
CPI_NCPD_COI_RT_M |>
left_join(classif1, by = "classif1") |>
group_by(classif1, Classif1) |>
summarise(Nobs = n()) %>%
{if (is_html_output()) print_table(.) else .}| classif1 | Classif1 | Nobs |
|---|---|---|
| COI_COICOP_CP01 | COICOP2012: 1. Food and non-alcoholic beverages | 50140 |
| COI_COICOP_CP01T12 | COICOP2012: General - Individual consumption expenditure of households | 63860 |
| COI_COICOP_CP02 | COICOP2012: 2. Alcoholic beverages, tobacco and narcotics | 35724 |
| COI_COICOP_CP03 | COICOP2012: 3. Clothing and footwear | 37794 |
| COI_COICOP_CP04 | COICOP2012: 4. Housing, water, electricity, gas and other fuels | 37545 |
| COI_COICOP_CP05 | COICOP2012: 5. Furnishings, household equipment and routine household maintenance | 37873 |
| COI_COICOP_CP06 | COICOP2012: 6. Health | 34460 |
| COI_COICOP_CP07 | COICOP2012: 7. Transport | 38341 |
| COI_COICOP_CP08 | COICOP2012: 8. Communication | 25961 |
| COI_COICOP_CP09 | COICOP2012: 9. Recreation and culture | 36112 |
| COI_COICOP_CP10 | COICOP2012: 10. Education | 18544 |
| COI_COICOP_CP11 | COICOP2012: 11. Restaurants and hotels | 32933 |
| COI_COICOP_CP12 | COICOP2012: 12. Miscellaneous goods and services | 37382 |
CPI_NCPD_COI_RT_M |>
left_join(source, by = "source") |>
group_by(source, Source) |>
summarise(Nobs = n()) |>
arrange(-Nobs) %>%
{if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}