Read input-output tables from temporary directory
Validate the source input parameter and try to load the table
from the current sessions' temporary directory.
naio_10_cp1700Symmetric input-output table at basic prices (product by product)
naio_10_pyp1700Symmetric input-output table at basic prices (product by product) (previous years prices)
naio_10_cp1750Symmetric input-output table at basic prices (industry by industry)
naio_10_pyp1750Symmetric input-output table at basic prices (industry by industry) (previous years prices)
naio_10_cp15Supply table at basic prices incl. transformation into purchasers' prices
naio_10_cp16Use table at purchasers' prices
naio_10_cp1610Use table at basic prices
naio_10_pyp1610Use table at basic prices (previous years prices) (naio_10_pyp1610)
naio_10_cp1620Table of trade and transport margins at basic prices
naio_10_pyp1620Table of trade and transport margins at previous years' prices
naio_10_cp1630Table of taxes less subsidies on products at basic prices
naio_10_pyp1630Table of taxes less subsidies on products at previous years' prices
uk_2010_siotUnited Kingdom Input-Output Analytical Tables data
Source: naio_10_cp1700Symmetric input-output table at basic prices (product by product)
naio_10_pyp1700Symmetric input-output table at basic prices (product by product) (previous years prices)
naio_10_cp1750Symmetric input-output table at basic prices (industry by industry)
naio_10_pyp1750Symmetric input-output table at basic prices (industry by industry) (previous years prices)
naio_10_cp15Supply table at basic prices incl. transformation into purchasers' prices
naio_10_cp16Use table at purchasers' prices
naio_10_cp1610Use table at basic prices
naio_10_pyp1610Use table at basic prices (previous years prices) (naio_10_pyp1610)
naio_10_cp1620Table of trade and transport margins at basic prices
naio_10_pyp1620Table of trade and transport margins at previous years' prices
naio_10_cp1630Table of taxes less subsidies on products at basic prices
naio_10_pyp1630Table of taxes less subsidies on products at previous years' prices
uk_2010_siotUnited Kingdom Input-Output Analytical Tables data
R/iotables_read_tempdir.R
iotables_read_tempdir.RdRead input-output tables from temporary directory
Validate the source input parameter and try to load the table
from the current sessions' temporary directory.
naio_10_cp1700Symmetric input-output table at basic prices (product by product)naio_10_pyp1700Symmetric input-output table at basic prices (product by product) (previous years prices)naio_10_cp1750Symmetric input-output table at basic prices (industry by industry)naio_10_pyp1750Symmetric input-output table at basic prices (industry by industry) (previous years prices)naio_10_cp15Supply table at basic prices incl. transformation into purchasers' pricesnaio_10_cp16Use table at purchasers' pricesnaio_10_cp1610Use table at basic pricesnaio_10_pyp1610Use table at basic prices (previous years prices) (naio_10_pyp1610)naio_10_cp1620Table of trade and transport margins at basic pricesnaio_10_pyp1620Table of trade and transport margins at previous years' pricesnaio_10_cp1630Table of taxes less subsidies on products at basic pricesnaio_10_pyp1630Table of taxes less subsidies on products at previous years' pricesuk_2010_siotUnited Kingdom Input-Output Analytical Tables data
Arguments
- source
See the available list of sources above in the Description. Defaults to
source = "naio_10_cp1700".
Value
A nested data frame. Each input-output table is in a separate
row of the nested output, where all the metadata are in columns, and the
actual, tidy, ordered input-output table is in the data data column.
See also
Other import functions:
airpol_get(),
employment_get(),
iotables_download(),
iotables_metadata_get()
Examples
# \donttest{
# The table must be present in the sessions' temporary directory:
iotables_download(source = "naio_10_pyp1750")
#> The naio_10_pyp1750_processed.rds is retrieved from the temporary directory.
#> Returning the processed SIOTs from tempdir. You can override this with force_download=TRUE.
#> # A tibble: 96 x 10
#> unit stk_flow geo time unit_lab stk_flow_lab geo_lab time_lab
#> <chr> <chr> <chr> <date> <chr> <chr> <chr> <date>
#> 1 MIO_EUR DOM DK 2018-01-01 Million eu~ Domestic Denmark 2018-01-01
#> 2 MIO_EUR IMP DK 2018-01-01 Million eu~ Imports Denmark 2018-01-01
#> 3 MIO_EUR TOTAL DK 2018-01-01 Million eu~ Total Denmark 2018-01-01
#> 4 MIO_NAC DOM DK 2018-01-01 Million un~ Domestic Denmark 2018-01-01
#> 5 MIO_NAC IMP DK 2018-01-01 Million un~ Imports Denmark 2018-01-01
#> 6 MIO_NAC TOTAL DK 2018-01-01 Million un~ Total Denmark 2018-01-01
#> 7 MIO_EUR DOM DK 2017-01-01 Million eu~ Domestic Denmark 2017-01-01
#> 8 MIO_EUR IMP DK 2017-01-01 Million eu~ Imports Denmark 2017-01-01
#> 9 MIO_EUR TOTAL DK 2017-01-01 Million eu~ Total Denmark 2017-01-01
#> 10 MIO_NAC DOM DK 2017-01-01 Million un~ Domestic Denmark 2017-01-01
#> # ... with 86 more rows, and 2 more variables: year <dbl>, data <list>
iotables_read_tempdir (source = "naio_10_pyp1750")
#> # A tibble: 96 x 10
#> unit stk_flow geo time unit_lab stk_flow_lab geo_lab time_lab
#> <chr> <chr> <chr> <date> <chr> <chr> <chr> <date>
#> 1 MIO_EUR DOM DK 2018-01-01 Million eu~ Domestic Denmark 2018-01-01
#> 2 MIO_EUR IMP DK 2018-01-01 Million eu~ Imports Denmark 2018-01-01
#> 3 MIO_EUR TOTAL DK 2018-01-01 Million eu~ Total Denmark 2018-01-01
#> 4 MIO_NAC DOM DK 2018-01-01 Million un~ Domestic Denmark 2018-01-01
#> 5 MIO_NAC IMP DK 2018-01-01 Million un~ Imports Denmark 2018-01-01
#> 6 MIO_NAC TOTAL DK 2018-01-01 Million un~ Total Denmark 2018-01-01
#> 7 MIO_EUR DOM DK 2017-01-01 Million eu~ Domestic Denmark 2017-01-01
#> 8 MIO_EUR IMP DK 2017-01-01 Million eu~ Imports Denmark 2017-01-01
#> 9 MIO_EUR TOTAL DK 2017-01-01 Million eu~ Total Denmark 2017-01-01
#> 10 MIO_NAC DOM DK 2017-01-01 Million un~ Domestic Denmark 2017-01-01
#> # ... with 86 more rows, and 2 more variables: year <dbl>, data <list>
# }