Car
Hugging FaceCar The Car dataset from the UCI repository. Classify the acceptability level of a car for resale. Configurations and tasks Configuration Task Description car Multiclass classification What is the acceptability level of the car? car_binary Binary classification Is the car acceptable? Usage from datasets import load_dataset dataset = load_dataset("mstz/car", "car_binary")["train"]
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Data preview
500 rows · 7 columns · showing first 12| # | buying integer | maint integer | doors integer | persons integer | lug_boot integer | safety integer | acceptability_level integer |
|---|---|---|---|---|---|---|---|
| 1 | 3 | 3 | 2 | 2 | 0 | 0 | 0 |
| 2 | 3 | 3 | 2 | 2 | 0 | 1 | 0 |
| 3 | 3 | 3 | 2 | 2 | 0 | 2 | 0 |
| 4 | 3 | 3 | 2 | 2 | 1 | 0 | 0 |
| 5 | 3 | 3 | 2 | 2 | 1 | 1 | 0 |
| 6 | 3 | 3 | 2 | 2 | 1 | 2 | 0 |
| 7 | 3 | 3 | 2 | 2 | 2 | 0 | 0 |
| 8 | 3 | 3 | 2 | 2 | 2 | 1 | 0 |
| 9 | 3 | 3 | 2 | 2 | 2 | 2 | 0 |
| 10 | 3 | 3 | 2 | 4 | 0 | 0 | 0 |
| 11 | 3 | 3 | 2 | 4 | 0 | 1 | 0 |
| 12 | 3 | 3 | 2 | 4 | 0 | 2 | 0 |
Auto-generated charts
Car: 500 rows by 7 columns. These exploratory charts are generated automatically from the data - open the dataset in Helix to ask your own questions.
Charts
buying vs maint
Relationship between buying and maint.
Distribution of buying
Histogram of buying values.
Correlation of numeric columns
Pearson correlation between numeric columns.
Interesting queries to try
Columns
- buying numeric
- maint numeric
- doors numeric
- persons numeric
- lug_boot numeric
- safety numeric
- acceptability_level numeric