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data comes from harmonised sources, such as SG and Fasttrack
data comes from disharmonised sources, such as SG and a csv file with higher dimensionality
vizabi core assumes that datasets from all sources are harmonised...
which means it's easy to get labels for country, gender when country comes from SG and gender from fasttrack because both datasets have country and gender entities with their names available, so you request either one, no problem
however in case when i'm adding a csv by country, decile, other datasets don't have decile entities and their names, therefore vizabi can't get those. it needs to know that space can be composed of concepts coming from different datasources (edited)
The text was updated successfully, but these errors were encountered:
...so that the space won't get changed to a subspace. Fixes an issue with missing gender labels when switching to country-gender marker space.
Gapminder/tools-page#246
This is a more stable way to compose a label space in the presence of readers who may have a clue about which one is a "time" concept type but not about entity domains and sets
Gapminder/tools-page#246
vizabi core assumes that datasets from all sources are harmonised...
which means it's easy to get labels for country, gender when country comes from SG and gender from fasttrack because both datasets have country and gender entities with their names available, so you request either one, no problem
however in case when i'm adding a csv by country, decile, other datasets don't have decile entities and their names, therefore vizabi can't get those. it needs to know that space can be composed of concepts coming from different datasources (edited)
The text was updated successfully, but these errors were encountered: