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Merge pull request #13 from eduaguilera/catalin/create-utils-code-to-name
Create utils code to name
2 parents 6444744 + 812dd7c commit ef097e2

17 files changed

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‎DESCRIPTION‎

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@@ -13,6 +13,7 @@ Imports:
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mipfp,
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purrr,
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readr,
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rlang,
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stringr,
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tidyr
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Encoding: UTF-8
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here,
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knitr,
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pointblank,
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rlang,
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rmarkdown,
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testthat (>= 3.0.0),
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tibble

‎NAMESPACE‎

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# Generated by roxygen2: do not edit by hand
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export(add_area_code)
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export(add_area_name)
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export(add_item_code)
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export(add_item_name)
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export(add_process_code)
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export(add_process_name)
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export(build_supply_use)
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export(expand_trade_sources)
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export(get_bilateral_trade)
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export(get_faostat_data)
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export(get_file_path)
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export(get_processing_coefs)
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export(get_wide_cbs)
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importFrom(rlang,":=")

‎R/WHEP-package.R‎

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#' @keywords internal
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"_PACKAGE"
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## usethis namespace: start
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#' @importFrom rlang :=
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## usethis namespace: end
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NULL

‎R/code_names.R‎

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#' Get area names from area codes
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#'
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#' @description
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#' Add a new column to an existing tibble with the corresponding name
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#' for each code. The codes are assumed to be from those defined by
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#' the `FABIO` model.
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#'
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#' @param table The table that will be modified with a new column.
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#' @param code_column The name of the column in `table` containing the codes.
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#' @param name_column The name of the output column containing the names.
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#'
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#' @returns A tibble with all the contents of `table` and an extra column
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#' named `name_column`, which contains the names. If there is no name match,
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#' an `NA` is included.
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#'
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#' @export
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#'
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#' @examples
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#' table <- tibble::tibble(area_code = c(1, 2, 4444, 3))
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#'
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#' add_area_name(table)
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#'
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#' table |>
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#' dplyr::rename(my_area_code = area_code) |>
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#' add_area_name(code_column = "my_area_code")
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#'
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#' add_area_name(table, name_column = "my_custom_name")
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add_area_name <- function(
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table,
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code_column = "area_code",
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name_column = "area_name") {
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regions <- .get_regions(name_column, code_column)
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table |>
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dplyr::left_join(regions, {{ code_column }})
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}
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#' Get area codes from area names
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#'
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#' @description
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#' Add a new column to an existing tibble with the corresponding code
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#' for each name. The codes are assumed to be from those defined by
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#' the `FABIO` model.
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#'
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#' @param table The table that will be modified with a new column.
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#' @param code_column The name of the output column containing the codes.
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#' @param name_column The name of the column in `table` containing the names.
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#'
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#' @returns A tibble with all the contents of `table` and an extra column
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#' named `code_column`, which contains the codes. If there is no code match,
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#' an `NA` is included.
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#'
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#' @export
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#'
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#' @examples
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#' table <- tibble::tibble(
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#' area_name = c("Armenia", "Afghanistan", "Dummy Country", "Albania")
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#' )
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#'
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#' add_area_code(table)
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#'
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#' table |>
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#' dplyr::rename(my_area_name = area_name) |>
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#' add_area_code(name_column = "my_area_name")
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#'
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#' add_area_code(table, code_column = "my_custom_code")
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add_area_code <- function(
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table,
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name_column = "area_name",
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code_column = "area_code") {
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regions <- .get_regions(name_column, code_column)
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table |>
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dplyr::left_join(regions, {{ name_column }})
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}
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#' Get item names from item codes
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#'
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#' @description
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#' Add a new column to an existing tibble with the corresponding name
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#' for each item code. The codes are assumed to be from those defined by
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#' FAOSTAT.
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#'
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#' @param table The table that will be modified with a new column.
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#' @param code_column The name of the column in `table` containing the codes.
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#' @param name_column The name of the output column containing the names.
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#'
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#' @returns A tibble with all the contents of `table` and an extra column
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#' named `name_column`, which contains the names. If there is no name match,
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#' an `NA` is included.
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#'
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#' @export
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#'
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#' @examples
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#' table <- tibble::tibble(item_code = c(2559, 2744, 9876))
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#' add_item_name(table)
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#'
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#' table |>
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#' dplyr::rename(my_item_code = item_code) |>
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#' add_item_name(code_column = "my_item_code")
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#'
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#' add_item_name(table, name_column = "my_custom_name")
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add_item_name <- function(
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table,
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code_column = "item_code",
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name_column = "item_name") {
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items <- .get_items(name_column, code_column)
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table |>
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dplyr::left_join(items, {{ code_column }})
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}
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#' Get item codes from item names
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#'
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#' @description
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#' Add a new column to an existing tibble with the corresponding code
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#' for each item name. The codes are assumed to be from those defined by
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#' the FAOSTAT.
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#'
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#' @param table The table that will be modified with a new column.
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#' @param code_column The name of the output column containing the codes.
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#' @param name_column The name of the column in `table` containing the names.
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#'
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#' @returns A tibble with all the contents of `table` and an extra column
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#' named `code_column`, which contains the codes. If there is no code match,
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#' an `NA` is included.
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#'
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#' @export
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#'
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#' @examples
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#' table <- tibble::tibble(item_name = c("Cottonseed", "Eggs", "Dummy Item"))
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#' add_item_code(table)
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#'
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#' table |>
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#' dplyr::rename(my_item_name = item_name) |>
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#' add_item_code(name_column = "my_item_name")
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#'
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#' add_item_code(table, code_column = "my_custom_code")
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add_item_code <- function(
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table,
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name_column = "item_name",
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code_column = "item_code") {
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items <- .get_items(name_column, code_column)
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table |>
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dplyr::left_join(items, {{ name_column }})
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}
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#' Get process names from process codes
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#'
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#' @description
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#' Add a new column to an existing tibble with the corresponding name
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#' for each process code. The codes are assumed to be from those defined by
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#' the FABIO model.
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#'
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#' @param table The table that will be modified with a new column.
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#' @param code_column The name of the column in `table` containing the codes.
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#' @param name_column The name of the output column containing the names.
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#'
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#' @returns A tibble with all the contents of `table` and an extra column
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#' named `name_column`, which contains the names. If there is no name match,
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#' an `NA` is included.
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#'
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#' @export
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#'
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#' @examples
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#' table <- tibble::tibble(process_code = c("p017", "p076", "dummy"))
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#' add_process_name(table)
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#'
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#' table |>
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#' dplyr::rename(my_process_code = process_code) |>
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#' add_process_name(code_column = "my_process_code")
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#'
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#' add_process_name(table, name_column = "my_custom_name")
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add_process_name <- function(
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table,
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code_column = "process_code",
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name_column = "process_name") {
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processes <- .get_processes(name_column, code_column)
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table |>
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dplyr::left_join(processes, {{ code_column }})
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}
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#' Get process codes from process names
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#'
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#' @description
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#' Add a new column to an existing tibble with the corresponding code
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#' for each process name. The codes are assumed to be from those defined by
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#' the FABIO model.
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#'
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#' @param table The table that will be modified with a new column.
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#' @param code_column The name of the output column containing the codes.
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#' @param name_column The name of the column in `table` containing the names.
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#'
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#' @returns A tibble with all the contents of `table` and an extra column
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#' named `code_column`, which contains the codes. If there is no code match,
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#' an `NA` is included.
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#'
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#' @export
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#'
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#' @examples
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#' table <- tibble::tibble(
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#' process_name = c("Beans production", "Olive Oil extraction", "Dummy")
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#' )
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#' add_process_code(table)
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#'
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#' table |>
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#' dplyr::rename(my_process_name = process_name) |>
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#' add_process_code(name_column = "my_process_name")
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#'
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#' add_process_code(table, code_column = "my_custom_code")
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add_process_code <- function(
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table,
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name_column = "process_name",
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code_column = "process_code") {
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processes <- .get_processes(name_column, code_column)
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table |>
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dplyr::left_join(processes, {{ name_column }})
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}
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.get_regions <- function(name_column, code_column) {
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"input/raw/regions.csv" |>
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.read_local_csv() |>
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dplyr::select(!!name_column := area, !!code_column := area_code)
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}
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.get_items <- function(name_column, code_column) {
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"input/raw/items.csv" |>
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.read_local_csv() |>
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dplyr::select(!!name_column := item, !!code_column := item_code)
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}
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.get_processes <- function(name_column, code_column) {
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"input/raw/processes.csv" |>
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.read_local_csv() |>
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dplyr::select(!!name_column := process, !!code_column := process_code)
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}

‎R/utils.R‎

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"Name",
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"No",
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"proc",
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"process",
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"process_code",
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"processeditem",
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"product_fraction",
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"SACO_link",

‎inst/extdata/input/raw/items.csv‎

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item_code,item
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2666,Abaca
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2617,Apples and products
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2615,Bananas
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2513,Barley and products
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2546,Beans
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2656,Beer
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2731,Bovine Meat
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2740,"Butter, Ghee"
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2532,Cassava and products
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2520,"Cereals, Other"
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2614,"Citrus, Other"
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2642,Cloves
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2633,Cocoa Beans and products
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2578,Coconut Oil
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248,Coconuts
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2560,Coconuts - Incl Copra
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2630,Coffee and products
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2661,Cotton lint
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2559,Cottonseed
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2575,Cottonseed Oil
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2619,Dates
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2744,Eggs
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2737,"Fats, Animals, Raw"
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2107,Firewood
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2000,Fodder cereal and grasses
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2001,Fodder legumes
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2003,Fodder mix
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2002,Fodder vegetables and roots
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2625,"Fruits, Other"
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2613,Grapefruit and products
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2620,Grapes and products (excl wine)
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3000,Grassland
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2572,Groundnut Oil
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2552,Groundnuts
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2667,"Hard Fibres, Other"
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776,Hemp
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2748,Hides and skins
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2745,Honey
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677,Hops
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2662,Jute
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2663,Jute-Like Fibres
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310,Kapok fruit
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2612,"Lemons, Limes and products"
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772,Linum
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2582,Maize Germ Oil
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2514,Maize and products
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2735,"Meat, Other"
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2848,Milk - Excluding Butter
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2517,Millet and products
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2544,Molasses
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2732,Mutton & Goat Meat
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2551,Nuts and products
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2516,Oats
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2736,"Offals, Edible"
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254,"Oil, palm fruit"
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2586,"Oilcrops Oil, Other"
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2570,"Oilcrops, Other"
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2580,Olive Oil
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2563,Olives (including preserved)
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2602,Onions
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2611,"Oranges, Mandarines"
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2106,Other crop residues
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2577,Palm Oil
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2562,Palm kernels
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2576,Palmkernel Oil
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2547,Peas
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2640,Pepper
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2733,Pigmeat
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2641,Pimento
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2618,Pineapples and products
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2616,Plantains
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2531,Potatoes and products
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2734,Poultry Meat
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2549,"Pulses, Other and products"
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2574,Rape and Mustard Oil
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2558,Rape and Mustardseed
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2807,Rice and products
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2534,"Roots, Other"
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2672,Rubber
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2515,Rye and products
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3500,Scavenging
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328,Seed cotton
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2561,Sesame seed
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2579,Sesameseed Oil
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2747,Silk
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2665,Sisal
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2664,"Soft-Fibres, Other"
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2518,Sorghum and products
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2571,Soyabean Oil
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2555,Soyabeans
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2645,"Spices, Other"
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2105,Straw
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2542,Sugar (Raw Equivalent)
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2537,Sugar beet
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2536,Sugar cane
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2557,Sunflower seed
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2573,Sunflowerseed Oil
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2533,Sweet potatoes
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2635,Tea (including mate)
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3002,Temporary grassland
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2671,Tobacco
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2601,Tomatoes and products
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2605,"Vegetables, Other"
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2511,Wheat and products
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2655,Wine
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2746,Wool (Clean Eq.)
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2535,Yams

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