I have a source dataset with missing values corresponding to NULL.
In my flow, I use:
update_schema(None, missingValues=["NULL"])
The resulting datapackage.json has the missingValues field set as above, while the dumped files have empty fields (if I use CSV) or null (if I use JSON). Now I cannot parse the dumped file using the datapackage.json, as its schema corresponds to the original source file. Is this the expected behavior? Or is there another way of dealing with missing values?
I am sorry, this is probably a basic understanding question. Hope that someone can help.
I have a source dataset with missing values corresponding to
NULL.In my flow, I use:
update_schema(None, missingValues=["NULL"])The resulting
datapackage.jsonhas themissingValuesfield set as above, while the dumped files have empty fields (if I use CSV) ornull(if I use JSON). Now I cannot parse the dumped file using thedatapackage.json, as its schema corresponds to the original source file. Is this the expected behavior? Or is there another way of dealing with missing values?I am sorry, this is probably a basic understanding question. Hope that someone can help.