Many vectors (indicators, multipliers) are create in the wide form to conform matrixes in analytical functions. For printing it is more useful to have them in long form.
Usage
vector_transpose_longer(
data_table,
names_to = "nace_r2",
values_to = "value",
key_column_name = NULL,
.keep = FALSE
)
vector_transpose(
data_table,
names_to = "nace_r2",
values_to = "value",
key_column_name = NULL,
.keep = FALSE
)
Arguments
- data_table
A matrix or vector that normally has a key column.
- names_to
Defaults to
'nace_r2'
.- values_to
Defaults to
'value'
.- key_column_name
The name of the first column. Defaults to
NULL
when it is not changed. It should usually match the key column of the matrix or vector you would like to join the new vector created withvector_transpose_longer
.- .keep
Keep the indicator identifier column? Defaults to
FALSE
.
Value
A long form vector with a key column, and optionally the identifier of the indicator in the first column.
Details
This is a wrapper around pivot_longer
so you do not necessarily need to
import or load the entire tidyr package.
See also
Other iotables processing functions:
conforming_vector_create()
,
household_column_get()
,
iotable_year_get()
,
key_column_create()
,
matrix_round()
,
output_get()
,
primary_input_get()
,
rows_add()
,
supplementary_add()
,
total_tax_add()
,
vector_transpose_wider()
Examples
vector_transpose_longer(
data.frame(indicator = "my_inidcator",
agriculture = 0.0123,
manufacturing = 0.1436,
trade = 0.0921)
)
#> # A tibble: 3 × 2
#> nace_r2 value
#> <chr> <dbl>
#> 1 agriculture 0.0123
#> 2 manufacturing 0.144
#> 3 trade 0.0921