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During population creation, stattype guessing will set values in very sparse columns to null. Consequently, the failure doesn't occur during population creation, but rather when running analysis.
A column might not originally have all null values, but does after stattype guessing nullifies some of them. Then, in order to make a valid population with no all-NaN columns, one must drop columns from the underlying table. This violates the contract that a table with a population(s) associated with it should not be modified.
Potential solution:
Create a separate copy of a table each time a new population is created for it. This way, if an observation needs to be incorporated into a population, it can be incorporated only into that population's copy of a table rather than into the original table (shared by populations, as it is now).
The text was updated successfully, but these errors were encountered:
During population creation, stattype guessing will set values in very sparse columns to null. Consequently, the failure doesn't occur during population creation, but rather when running analysis.
A column might not originally have all null values, but does after stattype guessing nullifies some of them. Then, in order to make a valid population with no all-NaN columns, one must drop columns from the underlying table. This violates the contract that a table with a population(s) associated with it should not be modified.
Potential solution:
Create a separate copy of a table each time a new population is created for it. This way, if an observation needs to be incorporated into a population, it can be incorporated only into that population's copy of a table rather than into the original table (shared by populations, as it is now).
The text was updated successfully, but these errors were encountered: