File size: 17,698 Bytes
7000343
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
035884e
7000343
035884e
7000343
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
3ff6d67
7000343
 
 
 
 
 
 
 
 
 
 
 
 
 
 
035884e
 
 
7000343
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
3ff6d67
7000343
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
3ff6d67
 
 
 
 
 
 
 
 
 
7000343
 
 
 
 
 
 
 
 
 
3ff6d67
 
 
 
 
 
 
 
 
 
7000343
 
 
 
 
 
 
 
 
 
3ff6d67
 
 
 
 
 
 
 
 
 
7000343
 
 
 
 
 
 
 
 
 
3ff6d67
 
 
 
 
 
 
 
 
 
7000343
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
97bce2d
7000343
 
 
97bce2d
7000343
 
 
97bce2d
7000343
 
 
97bce2d
7000343
 
 
97bce2d
7000343
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
035884e
7000343
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356

---
language:
- en
license: cc-by-nc-4.0
pretty_name: "Copart Salvage Vehicle Auction Dataset"
tags:
- open-data
- data-science
- web-scraping
- scraper
- crawler
- data-collection
- copart
- salvage
- auction
- vehicles
- automotive
- insurance
- total-loss
- copart-com
size_categories:
- 1M<n<10M
task_categories:
- other
configs:
- config_name: auction-listings
  data_files:
  - path: "auction-listings/data/*.parquet"
    split: train
---

# Copart Salvage Vehicle Auction Dataset

Salvage vehicle auction listings with damage assessments, condition grades, title status, and yard locations from Copart's nationwide network.


This dataset is a preview sample of the [Copart dataset](https://rebrowser.net/products/datasets/copart) published by Rebrowser. If you're doing academic research, you may be eligible for free access to a much larger slice — see [Free Datasets for Research](https://rebrowser.net/free-datasets-for-research).


This dataset contains **1** entity, each in its own folder: Auction Listings (`auction-listings`). See below for a full field breakdown, sample counts, and data distributions for each.

*Found this useful? ❤️ Like this dataset on HuggingFace to help us keep publishing fresh data. Found an error? [Let us know](https://rebrowser.net/contact-us).*


---

### Auction Listings
Daily sample of Copart salvage auction lots with damage types, condition codes, title status, mileage, repair costs, and yard locations across the US.




> **1,018,838** total records from 2025-11-16 to 2026-02-22, **up to 30,000** rows in this sample (2.9% of full dataset).
> Exported as one file per day, up to 1,000 rows each, last undefined days retained.


![Record Growth](auction-listings/chart-growth.svg)

| Field | Type | Fill Rate | Description |
| --- | --- | --- | --- |
| `_primaryKey` | `string` | 100% | Unique identifier for this record |
| `_firstSeenAt` | `datetime` | 100% | First time this record was seen |
| `_lastSeenAt` | `datetime` | 100% | Last time this record was updated |
| `lotId` | `string` | 100% | Unique Copart lot number (auction identifier) |
| `updatedAt` | `datetime` | 100% | Timestamp when Copart last updated the listing data |
| `vin` 🔒 | `string` | 100% | Vehicle Identification Number (17-character unique code) |
| `yardNumber` | `string` | 100% | Copart yard/facility number |
| `yardName` | `string` | 100% | Copart yard/facility name (e.g., "FL - MIAMI NORTH") |
| `saleDate` | `datetime` | 87% | Scheduled auction sale date |
| `saleDayOfWeek` | `string` | 87% | Day of week for the auction (e.g., TUESDAY, FRIDAY) |
| `saleTime` | `string` | 87% | Auction start time in HHMM format (e.g., "1000" = 10:00 AM) |
| `saleTimeZone` | `string` | 100% | Time zone for auction time (e.g., EST) |
| `itemNumber` | `string` | 100% | Item sequence number within the auction |
| `vehicleType` | `string` | 100% | Type code (V = Vehicle, C = Cycle/Motorcycle, K = Truck/Commercial) |
| `year` | `float` | 100% | Vehicle model year |
| `make` | `string` | 100% | Vehicle manufacturer (e.g., NISSAN, TOYOTA, MERCEDES-BENZ) |
| `modelGroup` | `string` | 100% | Vehicle model group (e.g., SENTRA, TACOMA, GLE-CLASS) |
| `modelDetail` | `string` | 100% | Detailed model name (e.g., SENTRA SV, TACOMA DOU, GLE COUPE) |
| `bodyStyle` | `string` | 15% | Vehicle body style |
| `exteriorColor` | `string` | 100% | Vehicle exterior color (e.g., WHITE, BLACK, GRAY) |
| `damageDescription` | `string` | 100% | Primary damage description (e.g., FRONT END, REAR END, MINOR DENT/SCRATCHES) |
| `secondaryDamage` | `string` | 43% | Secondary damage description (e.g., SIDE, REAR END) |
| `saleTitleState` | `string` | 100% | State where the title is held (e.g., FL) |
| `saleTitleType` | `string` | 100% | Title type code (SC = Salvage Certificate, CD = Certificate of Destruction, NR = Non-Repairable, DV = Dealer Vehicle, ST = Salvage Title, CT = Clear Title, RB = Rebuildable, AQ = Acquisition) |
| `hasKeys` | `string` | 100% | Whether keys are available (YES/NO/EXM - Exempt) |
| `lotCondCode` | `string` | 96% | Lot condition code (D = Drivable, E = Enhanced inspection, S = Stationary) |
| `mileage` | `float` | 100% | Odometer reading in miles |
| `odometerBrand` | `string` | 100% | Odometer status (A = Actual, N = Not Actual, E = Exempt) |
| `estRetailValue` 🔒 | `float` | 100% | Estimated retail value in USD |
| `repairCost` | `float` | 100% | Estimated repair cost in USD |
| `engine` | `string` | 97% | Engine description (e.g., "3.5L 6", "2.0L 4") |
| `drivetrain` | `string` | 98% | Drivetrain type (All wheel drive, Front-wheel Drive, Rear-wheel drive) |
| `transmission` | `string` | 98% | Transmission type (e.g., AUTOMATIC) |
| `fuelType` | `string` | 99% | Fuel type (e.g., GAS) |
| `cylinders` | `float` | 97% | Number of engine cylinders |
| `runsDrives` | `string` | 96% | Run/drive status (Run & Drive Verified, Vehicle Starts, DEFAULT, null) |
| `saleStatus` | `string` | 100% | Auction sale status (Pure Sale, On Minimum Bid) |
| `highBid` 🔒 | `float` | 100% | Current high bid amount in USD |
| `specialNote` | `string` | 3% | Special notes (e.g., "ODOMETER IS IN KILOMETERS") |
| `locationCity` | `string` | 100% | Vehicle storage location city |
| `locationState` | `string` | 100% | Vehicle storage location state |
| `locationZip` | `string` | 100% | Vehicle storage location ZIP code |
| `locationCountry` | `string` | 100% | Vehicle storage location country (e.g., USA) |
| `currencyCode` | `string` | 100% | Currency code for prices (e.g., USD) |
| `imageThumbnail` 🔒 | `string` | 100% | Thumbnail image URL |
| `imageUrl` 🔒 | `string` | 100% | Full-size image URL |
| `gridRow` | `string` | 100% | Yard grid/row location (e.g., "A130", "SD006", "RACK", "*OFF" for offsite) |
| `makeOfferEligible` | `bool` | 100% | Whether Make-an-Offer is available |
| `buyItNowPrice` 🔒 | `float` | 100% | Buy-It-Now price in USD (0 if not available) |
| `trim` | `string` | 82% | Vehicle trim level (e.g., SV, EX, LUXE, AMG 53 4MATIC) |
| `rentals` | `bool` | 100% | Whether vehicle was a former rental |
| `wholesale` | `bool` | 100% | Whether listing is wholesale |
| `sellerName` 🔒 | `string` | 36% | Seller name (e.g., "State Farm Insurance", "GEICO") |
| `offsiteAddress1` | `string` | 1% | Offsite pickup address line 1 |
| `offsiteState` | `string` | 1% | Offsite pickup state |
| `offsiteCity` | `string` | 1% | Offsite pickup city |
| `offsiteZip` | `string` | 1% | Offsite pickup ZIP code |
| `saleLight` | `string` | 1% | Sale light indicator |
| `autoGrade` | `float` | 2% | Auto grade rating (e.g., 3.0, 2.5) |
| `announcements` | `string` | 1% | Auction announcements and special conditions |
| `listingUrl` 🔒 | `string` | 100% | Full URL to the Copart lot listing page |



> 🔒 **Premium fields** are included in the data files but their values are replaced with `[PREMIUM]`. To access real values, [use our website](https://rebrowser.net/products/datasets/copart).



#### Field Distributions


<details>
<summary><strong>Top Vehicle Makes</strong> (<code>make</code>)</summary>


| Value | Count | Share |
| --- | --- | --- |
| TOYOTA | 131,688 | `████░░░░░░░░░░░░░░░░` 18.3% |
| FORD | 116,128 | `███░░░░░░░░░░░░░░░░░` 16.1% |
| CHEVROLET | 102,578 | `███░░░░░░░░░░░░░░░░░` 14.3% |
| HONDA | 93,404 | `███░░░░░░░░░░░░░░░░░` 13.0% |
| NISSAN | 80,779 | `██░░░░░░░░░░░░░░░░░░` 11.2% |
| HYUNDAI | 56,228 | `██░░░░░░░░░░░░░░░░░░` 7.8% |
| KIA | 44,470 | `█░░░░░░░░░░░░░░░░░░░` 6.2% |
| JEEP | 36,601 | `█░░░░░░░░░░░░░░░░░░░` 5.1% |
| DODGE | 30,622 | `█░░░░░░░░░░░░░░░░░░░` 4.3% |
| SUBARU | 26,914 | `█░░░░░░░░░░░░░░░░░░░` 3.7% |

</details>


<details>
<summary><strong>Top Damage Types</strong> (<code>damageDescription</code>)</summary>


| Value | Count | Share |
| --- | --- | --- |
| FRONT END | 548,537 | `███████████░░░░░░░░░` 56.1% |
| REAR END | 148,356 | `███░░░░░░░░░░░░░░░░░` 15.2% |
| SIDE | 129,950 | `███░░░░░░░░░░░░░░░░░` 13.3% |
| MINOR DENT/SCRATCHES | 45,327 | `█░░░░░░░░░░░░░░░░░░░` 4.6% |
| MECHANICAL | 27,744 | `█░░░░░░░░░░░░░░░░░░░` 2.8% |
| NORMAL WEAR | 20,783 | `░░░░░░░░░░░░░░░░░░░░` 2.1% |
| ALL OVER | 19,550 | `░░░░░░░░░░░░░░░░░░░░` 2.0% |
| ROLLOVER | 13,893 | `░░░░░░░░░░░░░░░░░░░░` 1.4% |
| UNDERCARRIAGE | 11,905 | `░░░░░░░░░░░░░░░░░░░░` 1.2% |
| VANDALISM | 11,108 | `░░░░░░░░░░░░░░░░░░░░` 1.1% |

</details>


<details>
<summary><strong>Title Type Distribution</strong> (<code>saleTitleType</code>)</summary>


| Value | Count | Share |
| --- | --- | --- |
| SC | 302,025 | `███████░░░░░░░░░░░░░` 32.9% |
| ST | 279,175 | `██████░░░░░░░░░░░░░░` 30.4% |
| CT | 151,611 | `███░░░░░░░░░░░░░░░░░` 16.5% |
| SV | 57,488 | `█░░░░░░░░░░░░░░░░░░░` 6.3% |
| RB | 39,166 | `█░░░░░░░░░░░░░░░░░░░` 4.3% |
| SM | 21,375 | `░░░░░░░░░░░░░░░░░░░░` 2.3% |
| BS | 19,537 | `░░░░░░░░░░░░░░░░░░░░` 2.1% |
| S1 | 17,721 | `░░░░░░░░░░░░░░░░░░░░` 1.9% |
| RS | 16,033 | `░░░░░░░░░░░░░░░░░░░░` 1.7% |
| CD | 13,231 | `░░░░░░░░░░░░░░░░░░░░` 1.4% |

</details>


<details>
<summary><strong>Listings by State</strong> (<code>locationState</code>)</summary>


| Value | Count | Share |
| --- | --- | --- |
| CA | 91,817 | `████░░░░░░░░░░░░░░░░` 18.7% |
| TX | 86,246 | `████░░░░░░░░░░░░░░░░` 17.6% |
| FL | 62,571 | `███░░░░░░░░░░░░░░░░░` 12.7% |
| IL | 44,721 | `██░░░░░░░░░░░░░░░░░░` 9.1% |
| PA | 42,764 | `██░░░░░░░░░░░░░░░░░░` 8.7% |
| GA | 40,129 | `██░░░░░░░░░░░░░░░░░░` 8.2% |
| NY | 31,027 | `█░░░░░░░░░░░░░░░░░░░` 6.3% |
| MI | 30,966 | `█░░░░░░░░░░░░░░░░░░░` 6.3% |
| TN | 30,953 | `█░░░░░░░░░░░░░░░░░░░` 6.3% |
| AL | 30,051 | `█░░░░░░░░░░░░░░░░░░░` 6.1% |

</details>






---

## Pre-built Views on Rebrowser

Rebrowser web viewer lets you filter, sort, and export any slice of this dataset interactively. These pre-built views are ready to open:


### Auction Listings


[Listings with Bid Over $1,000](https://rebrowser.net/products/datasets/copart/auction-listings/views/listings-with-bid-over-1000) — 178,426 records

↳ `[{"field":"highBid","op":"gt","value":1000},{"sort":"highBid DESC"}]`

[Salvage Title Auctions](https://rebrowser.net/products/datasets/copart/auction-listings/views/salvage-title-auctions) — 250,152 records

↳ `[{"field":"saleTitleType","op":"is","value":"ST"},{"sort":"saleDate ASC"}]`

[Run and Drive Vehicles](https://rebrowser.net/products/datasets/copart/auction-listings/views/run-and-drive-vehicles) — 585,933 records

↳ `[{"field":"lotCondCode","op":"is","value":"D"},{"sort":"estRetailValue DESC"}]`

[Listings with Estimated Value Over $10,000](https://rebrowser.net/products/datasets/copart/auction-listings/views/listings-valued-over-10000) — 443,204 records

↳ `[{"field":"estRetailValue","op":"gt","value":10000},{"sort":"estRetailValue DESC"}]`

[Make-an-Offer Eligible Lots](https://rebrowser.net/products/datasets/copart/auction-listings/views/make-offer-eligible-lots) — 104,434 records

↳ `[{"field":"makeOfferEligible","op":"isTrue"},{"sort":"_lastSeenAt DESC"}]`


*[See all 38 views →](https://rebrowser.net/products/datasets/copart/auction-listings)*




---

## Code Examples

```python
import pandas as pd
from pathlib import Path

# ── Auction Listings ─────────────────────────────────────────────────────────
# Load the last 7 days of auction listings
files = sorted(Path('rebrowser/copart-dataset/auction-listings/data').glob('*.parquet'))[-7:]
listings = pd.concat([pd.read_parquet(f) for f in files])

# Top 10 most common makes
print(listings['make'].value_counts().head(10).to_string())

# Average mileage by damage type
damage_mileage = listings.groupby('damageDescription')['mileage'].mean().sort_values(ascending=False)
print(damage_mileage.head(10).round(0).to_string())

# Count of listings by title type and condition code
print(pd.crosstab(listings['saleTitleType'], listings['lotCondCode']).to_string())

# Run-and-drive vehicles by state, sorted by volume
drivable = listings[listings['lotCondCode'] == 'D']
print(drivable['locationState'].value_counts().head(10).to_string())

# Average repair cost by damage type
repair_by_damage = listings.groupby('damageDescription')['repairCost'].mean().sort_values(ascending=False)
print(repair_by_damage.head(10).round(2).to_string())
```

---

## Use Cases


### Salvage Value Modeling

Build predictive models for salvage vehicle pricing using damage type, condition grade, mileage, and repair cost data. Identify undervalued lots by comparing repair costs against market values.


### Parts Sourcing Pipeline

Monitor incoming auction inventory by make, model, and damage type to source high-demand parts. Filter by yard location and condition code to optimize logistics and pickup costs.


### Regional Market Analysis

Compare auction volume, vehicle mix, and damage patterns across states and Copart yards. Track seasonal trends in inventory and identify geographic arbitrage opportunities.


### Title Status Research

Analyze the distribution of salvage certificates, clean titles, and rebuildable designations across vehicle types. Study how title classification varies by state and affects auction outcomes.



---

## Full Dataset on Rebrowser


This is a 1,000-row preview sample. The full dataset is at [rebrowser.net/products/datasets/copart](https://rebrowser.net/products/datasets/copart)

Doing academic research? You may qualify for free access to a larger slice. See [Free Datasets for Research](https://rebrowser.net/free-datasets-for-research).

On Rebrowser you can:
- **Filter before you buy** — use the web UI to apply filters on any field and sort by any column. Preview results before purchasing. You only pay for records that match your criteria.
- **Export in your format** — CSV, JSON, JSONL, or Parquet depending on your plan.
- **Access via API** — integrate dataset queries into your pipelines and workflows.
- **Choose your freshness** — plans range from a 14-day lag to real-time data with no delay.
- **Select only the fields you need** — keep exports lean. Premium fields with richer data are available on higher plans.

[Pricing](https://rebrowser.net/pricing) starts at **$2 per 1,000 rows** with volume discounts.

---

## License & Terms

**Free for research and non-commercial use** with attribution. See [license terms](https://rebrowser.net/free-datasets-for-research#license) and [how to cite](https://rebrowser.net/free-datasets-for-research#citation).

```bibtex
@misc{rebrowser_copart,
  author       = {Rebrowser},
  title        = {Copart Salvage Vehicle Auction Dataset},
  year         = {2026},
  howpublished = {\url{https://rebrowser.net/products/datasets/copart}},
  note         = {Accessed: YYYY-MM-DD}
}
```

Commercial use requires a paid license — see [pricing](https://rebrowser.net/pricing). Use of this data is governed by the [Rebrowser Terms of Use](https://rebrowser.net/terms-of-use), which may be updated at any time independently of this dataset.

---

## Disclaimer

Rebrowser is an independent data provider and is not affiliated with, endorsed by, or sponsored by Copart. Any trademarks are the property of their respective owners. This dataset is compiled from publicly available information; we do not request or collect Copart user credentials. By using this dataset, you agree to comply with Copart's Terms of Service and all applicable laws and regulations. Images, logos, descriptions, and other materials included in this dataset remain the intellectual property of their respective owners and are provided solely for informational purposes. Rebrowser makes no warranties regarding the accuracy, completeness, or legality of the data and assumes no liability for how the data is used. You are solely responsible for ensuring that your use of this dataset does not infringe on the rights of any third party.


You can also find this data on [GitHub](https://github.com/rebrowser/copart-dataset), [Kaggle](https://www.kaggle.com/datasets/rebrowser/copart-dataset), [Zenodo](https://doi.org/10.5281/zenodo.18716356).