re-implement annotatons #39
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GregorDeCillia
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Mar 29, 2023
this is the first step to resolving #27 by adding a function that creates sc_table() like objects based on sdmx archives The sdmx format contains all metadata that is necessary for STATcubeR to reuse the existing $tabulate() workflow and this first version already provides support for various features via the base class (sc_data) - $tabulate() to aggregate data - $total_codes() to set/unset total codes - $recoder to recode datasets (change labels) change codes, toggle visibility of elements, reorder elements, etc. - importing german and english labels simultaniously (both languages are included in a zip download) and allowing to swhitch between them using $language<-(). New features - sdmx arcives provide a $parent column in the $fields() table which are used to represent hierarchical classifications. Previously, this was only possible with od_table() There are still some improvements. See the issue #27 for more details - properly parse time variables - currently they are treated as generic categories. - parse element annotations (detailed descriptions for classification elements) and add them to $field()$de_desc just like with OGD dataset - parse value annotations (see #39) - provide a print/fromat method - add a reasonable logic for total codes that takes the parent codes into account - fill meta$measures$fun and $meta$measures$precision based on the sdmx metadata - modify very long codes which use the @-symbol (probably for escapes) - extend documentation - possibly check SuperCROSS compability
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In early versions, STATcubeR used to include annotations in the output of
as.dataframe.sc_table(). This was dropped when support for OGD Datasets was introduced in #11 . Back then, the annotations were included using separate columns.It is planned to re-implement this feature in a slightly different manner using
{tibble}and{vctrs}by providing a custom vector class that acts as a "annotated numeric". The result of printing those values should look something like thisAnnotations should either replace the values while printing or use color coding to reference a specific annotation
The "annotation legend" (which color corresponds to which annotation) can then be included in the footer of the tibble. Some technical details
sc_tabulate()andas.data.frame.sc_table()should be to return simple tibbles that only include columns of typenumericandfactor. Adding annotations should be "opt-in"as.numeric()method which drops the annotations and returns a canonical double-typesc_tabulate()is called in a way where aggregation viarowsums()is necessary andannotationsis set toTRUE, an error will be thrown.The text was updated successfully, but these errors were encountered: