Dataset Viewer
CarModel
stringlengths 12
33
| Year
int64 2.01k
2.03k
| Mileage
float64 0
161k
| EngineSize
float64 1.5
6.4
| Doors
int64 2
4
| Price
float64 3.5k
180k
|
|---|---|---|---|---|---|
Jeep Wrangler Unlimited Sahara
| 2,022
| 32,582
| 2
| 4
| 32,991
|
Dodge Charger Scat Pack
| 2,021
| 46,396
| 6.4
| 4
| 37,895
|
Nissan Sentra SV
| 2,023
| 21,704
| 2
| 4
| 18,495
|
Hyundai Elantra N
| 2,025
| 8
| 2
| 4
| 35,623
|
Kia Forte LXS
| 2,021
| 35,256
| 2
| 4
| 15,795
|
Honda Accord Sport
| 2,020
| 41,457
| 1.5
| 4
| 23,155
|
Toyota Camry SE
| 2,023
| 19,129
| 2.5
| 4
| 26,064
|
Jeep Wagoneer
| 2,024
| 27,068
| 3
| 4
| 46,250
|
Jeep Grand Cherokee
| 2,022
| 14,475
| 3.6
| 4
| 30,195
|
Nissan Armada SL
| 2,025
| 0
| 3.5
| 4
| 61,644
|
Nissan Rogue SL
| 2,021
| 31,436
| 2.5
| 4
| 25,989
|
Chevrolet Suburban LT
| 2,021
| 56,549
| 5.3
| 4
| 41,994
|
BMW 1 Series 128i Coupe
| 2,008
| 160,500
| 3
| 2
| 3,500
|
Dodge Challenger GT
| 2,023
| 17,993
| 3.6
| 2
| 27,895
|
Porsche 718 Cayman GT4 RS
| 2,024
| 6,776
| 4
| 2
| 180,000
|
INFINITI G37 Journey
| 2,010
| 99,373
| 3.6
| 2
| 12,250
|
Ford Mustang Coupe
| 2,025
| 4
| 2.3
| 2
| 32,109
|
Chevrolet Corvette Stingray
| 2,022
| 10,939
| 6.2
| 2
| 59,916
|
Honda Fit EX
| 2,020
| 49,821
| 1.5
| 4
| 18,887
|
Toyota Corolla SE
| 2,023
| 10,447
| 2
| 4
| 23,900
|
Audi A7 3.0T Prestige
| 2,018
| 76,746
| 3
| 4
| 22,992
|
MAZDA MAZDA3 s
| 2,024
| 27,085
| 2.5
| 4
| 21,899
|
Hyundai Accent SE
| 2,016
| 54,190
| 1.6
| 4
| 7,995
|
Honda Civic Sport
| 2,025
| 2,604
| 2
| 4
| 26,908
|
Ford Mustang Convertible
| 2,017
| 97,976
| 3.7
| 2
| 15,995
|
McLaren MP4-12C Spider
| 2,013
| 19,404
| 3.8
| 2
| 114,999
|
MAZDA MX-5 Miata RF Grand Touring
| 2,025
| 0
| 2
| 2
| 39,739
|
BMW M4 Convertible
| 2,018
| 46,764
| 3
| 2
| 42,295
|
MINI Cooper S
| 2,019
| 51,641
| 2
| 2
| 19,604
|
Jaguar F-TYPE V8 S Convertible 2D
| 2,014
| 71,500
| 5
| 2
| 25,000
|
Dataset Card: [Cars-tabular]
Purpose
This dataset was created for educational purposes as part of a homework assignment.
It is intended to practice building, augmenting, and publishing datasets on the Hugging Face Hub.
Composition
- Number of samples:
- Original: N samples
- Augmented: M samples
- Features:
- [list features/columns here, e.g.
CarModel,Year,Mileage... ortext,complexity_label... orimage,has_groot]
- [list features/columns here, e.g.
Collection
- Source:
- Tabular (Cars): values manually collected from [source, e.g. online car listings or Google Sheets].
- Size:
- At least 30 original entries for tabular
Preprocessing & Augmentation
- Preprocessing:
- Cars: cleaned numeric + categorical values.
- Augmentation techniques:
- Tabular: Gaussian noise, sampling perturbations.
Labels
- Cars: Target =
Price(continuous).
Splits
original: manually collected data (30+).augmented: synthetic data (300 for tabular).
Intended Use & Limitations
- Use: Coursework, experimenting with dataset creation, augmentation, and Hugging Face tools.
- Limits:
- Not suitable for production ML training.
- Synthetic samples may not represent real-world distributions.
- Small dataset sizes → limited generalization.
Ethical Notes
- No personally identifiable information (PII) or sensitive content.
- Text is student-authored, not scraped.
- Labels are for demonstration purposes only.
License
MIT License (for educational use).
(You can also set to cc-by-4.0 or apache-2.0 if required by your class.)
AI Usage Disclosure
- No generative AI was used to produce original tabular; only augmentation steps.
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