How to get the most out of our filters!


For some operations, it helps to consider only a subset of all occupations in a taxonomy. If you don't specify a subset, our default is onet_simplified_2019. That is a subset defined by AdeptID of O*NET 2019 occupations, excluding several uncommon and poorly defined occupations. Specifying the name of a taxonomy uses the entire set of occupations in that taxonomy. You can use List Occupation Codes to see which codes are included in a subset or a taxonomy.

We are beginning to implement more complex ways to specify the occupation subset. For some operations, it is useful to include or exclude occupations related to other occupations specified. For example, with Recommend Destination Jobs, you might be considering a career change. So you might want to exclude occupations in the same area as those in your history. To do that, you can specify onet_simplified_2019-onet_major_group(source_occupations) as the occupation_subset.

Similarly, for Recommend Source Jobs, you can specify occupation_subset as onet_simplified_2019-onet_major_group(destination_occupations) to consider sources outside the area of the target occupation.

Filtering with dictionaries

When you filter results within each filter dictionary, the API uses AND operation. When you filter results between filter dictionaries, the API uses OR operation.

Example of within a filter dictionary using AND operation:

{"wage_min”:45000, "wage_max”:60000}  

Both conditions will be fulfilled.

Example of between filter dictionaries using OR operation:

 {"wage_min”:45000, "wage_max”:60000},  
 {"wage_min”:70000, "wage_max”:85000}  

The results returned will include occupations within the wage range of $45,000-$60,000 or $70,000-$85,000.