pricingpricesused-goodscraigslistindustrial-partsvehiclesgovernment-surplus

US Second-Hand Asking Prices: 148k Craigslist and Government-Surplus Listings (Goods, Parts, Vehicles)

Updated Oct 20, 2026

$99

Fixed price

Sample structure: 78.1 / 100

0 download links issued

Seller: Brick and Mortar

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Source, license and coverage

Supplier documentation. These claims are separate from the automated sample score. A listing edit date is not a data freshness date.

License: Brick & Mortar data licence: internal commercial use incl. model training, no redistribution
Source / creator: Craigslist for-sale listings (400+ US markets), GovDeals and PublicSurplus auction listings, Facebook Marketplace (Minneapolis), city council purchase filings; collected 2026-10-01 to 2026-10-10.
Collection method: What a used thing is offered at, across the US, in one table. We swept Craigslist for-sale sections in 400+ markets and the two biggest government surplus auction sites in early October 2026, and added a Minneapolis Marketplace sample. Each row is one listing with its price and the *basis* of that price: an ask (what a seller wants), a bid (current auction bid), or paid (what a council paid, from public filings). Industrial-part listings carry an extracted maker and part number so the same part can be compared across sellers; vehicles carry year, make, model and mileage where stated.
Coverage start: Not applicable
Coverage end: Not applicable
Data last updated: 2026-10-20
Update schedule: snapshot

Source documentation ↗

License terms ↗

Sample structure score: 78.1 / 100

This automated check describes the inspected sample, not factual accuracy, legal rights, representativeness, or the quality of the entire dataset. It is not a customer rating.

Assessed 10 sample records (CSV) on 2026-10-20. All records in the provided sample were checked.

Check	Points	Evidence
Populated cells	28.1 / 50	101 of 180 top-level cells contain a value. Null, absent and blank values count as missing; zero and false count as populated.
Consistent value types	30 / 30	101 of 101 populated cells match their column's most common observed type. Types are inferred, not checked against real-world truth.
Consistent record shape	20 / 20	10 of 10 records have the expected fields. CSV/TSV use the header width; JSON uses the union of observed keys.

Field-level findings and improvements

Check missing cells and mixed types below. Document intentional missing values or mixed types in your field descriptions. Do not fill legitimate unknowns with invented values just to increase this score.

Field	Missing cells	Most common type	Other populated types
listing_id	0 / 10	string	0 / 10
source	0 / 10	string	0 / 10
basis	0 / 10	string	0 / 10
domain	0 / 10	string	0 / 10
category	0 / 10	string	0 / 10
title	0 / 10	string	0 / 10
maker	9 / 10	string	0 / 1
part_number	10 / 10	unknown	0 / 0
price_usd	0 / 10	number	0 / 10
condition	10 / 10	unknown	0 / 0
seller_type	0 / 10	string	0 / 10
observed_on	0 / 10	string	0 / 10
market	0 / 10	string	0 / 10
state	10 / 10	unknown	0 / 0
vehicle_year	10 / 10	unknown	0 / 0
vehicle_make	10 / 10	unknown	0 / 0
vehicle_model	10 / 10	unknown	0 / 0
vehicle_mileage	10 / 10	unknown	0 / 0

How the score is calculated, its limitations, and how to correct an assessment →

About this data

148,149 second-hand asking prices and surplus-auction bids from Craigslist across 400+ US markets, GovDeals and PublicSurplus, plus Minneapolis Facebook Marketplace vehicles and equipment (October 2026): title, category, price, basis (ask / bid / paid), seller type, market, date, with maker and part number on surplus-auction and dealer part listings and year/make/model on vehicles. One CSV, 148,149 rows; column meanings in the schema. No seller names, profile links, phone numbers or emails (phone and email patterns are stripped from titles). No listing descriptions or photos. Prices in euros are left out.

Retrieve with your agent or Python

Create an account and configure DATABAZAAR_API_KEY. This example retrieves free or already purchased data; it never makes a purchase. For a multi-file dataset, choose a file index from the manifest.

Download the Python example

python3 retrieve-dataset.py b6c225b3-bd9b-487b-8d3f-03bc5a910116 --output dataset.bin

Schema

Name	Type	Description
listing_id	string
source	string
basis	string
domain	string
category	string
title	string
maker	string
part_number	unknown
price_usd	number
condition	unknown
seller_type	string
observed_on	string
market	string
state	unknown
vehicle_year	unknown
vehicle_make	unknown
vehicle_model	unknown
vehicle_mileage	unknown

Sample Data

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For AI Agents

Via MCP Server

# 1. Add to your agent's MCP config (claude_desktop_config.json or similar):
{
  "mcpServers": {
    "databazaar": { "command": "npx", "args": ["databazaar-mcp"] }
  }
}

# 2. Your agent can then call:
search_datasets({ query: "US Second-Hand Asking Prices: " })
// Found: b6c225b3-bd9b-487b-8d3f-03bc5a910116
buy_now({ dataset_id: "b6c225b3-bd9b-487b-8d3f-03bc5a910116" })  // uses your saved card

Via REST API

# Authenticate with your API key:
curl https://api.databazaar.io/datasets/b6c225b3-bd9b-487b-8d3f-03bc5a910116 \
  -H "Authorization: Bearer YOUR_API_KEY"

# Purchase:
curl -X POST https://api.databazaar.io/datasets/b6c225b3-bd9b-487b-8d3f-03bc5a910116/buy \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"dataset_id": "b6c225b3-bd9b-487b-8d3f-03bc5a910116"}'