Vehicle_Ownership_by_Race_in_Brazil
<|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully.  <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. Description:'This dataset presents secondary data from the National Family Budget Survey 2017 - 2018 (POF 2017 - 2018) of the Brazilian Institute of Geography and Statistics (IBGE). POF 2017- 2018 collected data on people's consumption habits in 57,920 dwellings sampled, equivalent to a total of 68,862,296 dwellings in Brazil. The sample represents Brazil's urban areas, large regions (North, Northeast, Midwest, Southeast, and South), states, metropolitan regions, and states' capitals. Also, it is representative of Brazil and large regions in rural areas. Datasets regarding residents, inventory, and dwelling were joined to analyze vehicle ownership by residents' race. The registered vehicles were automobiles, motorcycles, and bicycles. Each row in the dataset contains a sampled dwelling, sample weight, total residents, number of black, brown, white, ' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["Vehicle ownership, racial inequality, race, bicycle, urban mobility, Family Budget Survey"]} <|eot_id|>
 Here is the Description of a dataset. Description:'This dataset presents secondary data from the National Family Budget Survey 2017 - 2018 (POF 2017 - 2018) of the Brazilian Institute of Geography and Statistics (IBGE). POF 2017- 2018 collected data on people's consumption habits in 57,920 dwellings sampled, equivalent to a total of 68,862,296 dwellings in Brazil. The sample represents Brazil's urban areas, large regions (North, Northeast, Midwest, Southeast, and South), states, metropolitan regions, and states' capitals. Also, it is representative of Brazil and large regions in rural areas. Datasets regarding residents, inventory, and dwelling were joined to analyze vehicle ownership by residents' race. The registered vehicles were automobiles, motorcycles, and bicycles. Each row in the dataset contains a sampled dwelling, sample weight, total residents, number of black, brown, white, ' . Please return only a json list of at most 3 Keywords corresponding to the Description:.
This dataset presents secondary data from the National Family Budget Survey 2017 - 2018 (POF 2017 - 2018) of the Brazilian Institute of Geography and Statistics (IBGE). POF 2017- 2018 collected data on people's consumption habits in 57,920 dwellings sampled, equivalent to a total of 68,862,296 dwellings in Brazil. The sample represents Brazil's urban areas, large regions (North, Northeast, Midwest, Southeast, and South), states, metropolitan regions, and states' capitals. Also, it is representative of Brazil and large regions in rural areas. Datasets regarding residents, inventory, and dwelling were joined to analyze vehicle ownership by residents' race. The registered vehicles were automobiles, motorcycles, and bicycles. Each row in the dataset contains a sampled dwelling, sample weight, total residents, number of black, brown, white, 
Vehicle ownership, racial inequality, race, bicycle, urban mobility, Family Budget Survey