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For a dataset with a geographic dimension, the user should be able to aggregate values over that dimension and then use the aggregated data to display a choropleth map.
The hard aspect of this is having the "right" map, i.e. one that captures all the values in the dataset but does not extend much beyond it. Even worse, the identifiers used in the map for regions must also be found in the data, or an alignment must be made at run-time.
In an ideal case, this would also work for subsets of the data and display an appropriate map to match each query's result space.
Take a look at original issue for comments
The text was updated successfully, but these errors were encountered:
Moved from openspending/openspending#509
For a dataset with a geographic dimension, the user should be able to aggregate values over that dimension and then use the aggregated data to display a choropleth map.
The hard aspect of this is having the "right" map, i.e. one that captures all the values in the dataset but does not extend much beyond it. Even worse, the identifiers used in the map for regions must also be found in the data, or an alignment must be made at run-time.
In an ideal case, this would also work for subsets of the data and display an appropriate map to match each query's result space.
Take a look at original issue for comments
The text was updated successfully, but these errors were encountered: