Fixed assets by activity and by type of product, ISIC rev3 - SNA_TABLE9

Data - OECD

Author

Code

load_data("oecd/SNA_TABLE9_var.RData")
SNA_TABLE9 <- read_parquet("SNA_TABLE9.parquet")

Info

Last observation: A: 2022 (N = 48)

First observation: A: 1950 (N = 4)

Last data update: 02 aoû 2026, 09:12. Last compile: 18 aoû 2026, 03:12

Structure

Layout

OECD Website. html

Nobs

Code

SNA_TABLE9 |>
  left_join(SNA_TABLE9_var |> pluck("TRANSACT"), by = c("TRANSACT" = "id")) |>
  rename(`TRANSACT Description` = label) |>
  group_by(TRANSACT, `TRANSACT Description`, ACTIVITY) |>
  summarise(nobs = n()) |>
  arrange(-nobs) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}

Data Structure

Code

SNA_TABLE9_var |>
  pluck("VAR_DESC") %>%
  {if (is_html_output()) print_table(.) else .}

id	description
LOCATION	Country
TRANSACT	Transaction
ACTIVITY	Activity
MEASURE	Measure
TIME	Year
OBS_VALUE	Observation Value
TIME_FORMAT	Time Format
OBS_STATUS	Observation Status
UNIT	Unit
POWERCODE	Unit multiplier
REFERENCEPERIOD	Reference period

ACTIVITY

Code

SNA_TABLE9 |>
  left_join(SNA_TABLE9_var |> pluck("ACTIVITY"), by = c("ACTIVITY" = "id")) |>
  rename(`ACTIVITY Description` = label) |>
  group_by(ACTIVITY, `ACTIVITY Description`) |>
  summarise(nobs = n()) |>
  arrange(-nobs) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}

TRANSACT

Code

SNA_TABLE9 |>
  left_join(SNA_TABLE9_var |> pluck("TRANSACT"), by = c("TRANSACT" = "id")) |>
  rename(`TRANSACT Description` = label) |>
  group_by(TRANSACT, `TRANSACT Description`) |>
  summarise(nobs = n()) |>
  arrange(-nobs) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}

MEASURE

Code

SNA_TABLE9_var |>
  pluck("MEASURE") %>%
  {if (is_html_output()) print_table(.) else .}

id	label
C	Current prices

Example: AN1111GAY

Code

SNA_TABLE9 |>
  filter(TRANSACT == "AN1111GAY") |>
  left_join(SNA_TABLE9_var |> pluck("LOCATION"), by = c("LOCATION" = "id")) |>
  rename(countryname = label) |>
  group_by(LOCATION, countryname) |>
  summarise(nobs = n()) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}