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Currently, when using a tree chart that maps a data column to values in a (JSON) tree, the chart code will cause all events whose data (for the tree column) does not have any corresponding mid in the JSON tree to be silently discarded from the global crossfilter, as no match is effectively found.
As this scenario is likely to be quite common, it needs to be handled gracefully within the tree code.
This could also be partially mitigated during source data preparation, by checking that there are at least no mismatches between values that need to be used in the tree column and the available mids of the JSON tree.
Within the tree chart code, this could be handled by adding a (top-level?) tree node 'other' (or any other name as appropriate - this should be configurable), mapping all the variable levels not present in the JSON tree as mids to this node just after loading the JSON tree for a variable and before invoking the chart-making function for it.
pros: being per-chart, it doesn't need to touch the actual dataset
cons: the extra top-level node may not be desirable; although data rows needing to be put into this bucked should normally be as few as possible (otherwise the whole mismatch between data and JSON tree mids would make the whole chart and filter(s) analytically weak)
Alternatively, data rows with unknown values (aka values that are not present as mids in the JSON tree) should be ignored altogether within each tree chart instance, although this is not likely to be doable without actually moving the rows with unknown values to some specific 'bucket'.
The text was updated successfully, but these errors were encountered:
Currently, when using a tree chart that maps a data column to values in a (JSON) tree, the chart code will cause all events whose data (for the tree column) does not have any corresponding
mid
in the JSON tree to be silently discarded from the global crossfilter, as no match is effectively found.As this scenario is likely to be quite common, it needs to be handled gracefully within the tree code.
This could also be partially mitigated during source data preparation, by checking that there are at least no mismatches between values that need to be used in the tree column and the available
mid
s of the JSON tree.Within the tree chart code, this could be handled by adding a (top-level?) tree node 'other' (or any other name as appropriate - this should be configurable), mapping all the variable levels not present in the JSON tree as
mid
s to this node just after loading the JSON tree for a variable and before invoking the chart-making function for it.pros: being per-chart, it doesn't need to touch the actual dataset
cons: the extra top-level node may not be desirable; although data rows needing to be put into this bucked should normally be as few as possible (otherwise the whole mismatch between data and JSON tree
mid
s would make the whole chart and filter(s) analytically weak)Alternatively, data rows with unknown values (aka values that are not present as
mid
s in the JSON tree) should be ignored altogether within each tree chart instance, although this is not likely to be doable without actually moving the rows with unknown values to some specific 'bucket'.The text was updated successfully, but these errors were encountered: