Why is there only one of each PropulsionTypeID 3 (Electric) and 7 (Gas/Petrol)?

Why is there only one of each PropulsionTypeID 3 (Electric) and 7 (Gas/Petrol)?

• A. They are likely mislabelled and should have been put in the categories electric/petrol (3) and petrol (7).
• B. They were intended to be kept separate to distinguish electric from petrol.
• C. They correspond to hybrid fuels not listed.
• D. They are legacy categories no longer used.

Answer: (A)

This question is about how category IDs map to real-world categories and why consistency matters in a dataset. If PropulsionTypeID 3 is meant to represent Electric and 7 to represent Gas/Petrol, you’d expect many records to use those IDs whenever those propulsion types appear. Seeing only one record for each strongly suggests a labeling error rather than a deliberate design choice. A mislabeling could happen if the category labels were changed or if the mapping between IDs and meanings wasn’t updated everywhere, causing records to be assigned the wrong IDs or for two nearby labels to end up counting as distinct when they should be the same. The most plausible fix is to correct the mappings so ID 3 truly means Electric and ID 7 truly means Petrol, ensuring consistency across the dataset. The other possibilities don’t fit the data pattern as well: keeping them separate to distinguish electric from petrol wouldn’t typically result in only one record per ID, and notions of hybrids or legacy categories don’t explain the simple mislabeling scenario.

This question is about how category IDs map to real-world categories and why consistency matters in a dataset. If PropulsionTypeID 3 is meant to represent Electric and 7 to represent Gas/Petrol, you’d expect many records to use those IDs whenever those propulsion types appear. Seeing only one record for each strongly suggests a labeling error rather than a deliberate design choice. A mislabeling could happen if the category labels were changed or if the mapping between IDs and meanings wasn’t updated everywhere, causing records to be assigned the wrong IDs or for two nearby labels to end up counting as distinct when they should be the same. The most plausible fix is to correct the mappings so ID 3 truly means Electric and ID 7 truly means Petrol, ensuring consistency across the dataset. The other possibilities don’t fit the data pattern as well: keeping them separate to distinguish electric from petrol wouldn’t typically result in only one record per ID, and notions of hybrids or legacy categories don’t explain the simple mislabeling scenario.