Pricing

Rating

Developer

Actor stats

Categories

Share

👁 ParseForge Banner

🚚 DAT Freight Rates Scraper

🚀 Pull live US and Canadian freight market rates in seconds. Filter by equipment, rate type, country, and time bucket. No API key, no registration, no manual CSV wrangling.

🕒 Last updated: 2026-05-16 · 📊 24 fields per record · 4 datasets in one feed · 183 state-level supply/demand rows · 3 years of monthly rate history

Copy to your AI assistant

Copy this block into ChatGPT, Claude, Cursor, or any LLM to start using this actor.

parseforge/dat-freight-rates-scraper on Apify. Call:ApifyClient("TOKEN").actor("parseforge/dat-freight-rates-scraper").call(run_input={...}), then client.dataset(run["defaultDatasetId"]).list_items().items for results. Key inputs:maxItems(integer,default10),datasets(array,default["national_history","load_truck_ratio","national_trends",),equipments(array,default["VAN","FLATBED","REEFER"]),rateTypes(array,default["SHIPPER_TO_BROKER_SPOT","BROKER_TO_CARRIER_SPOT","CONTRA), countries (array, default ["US", "CA"]), periodTypes (array, default ["Month", "Week"]). Full actor spec: fetch build via GEThttps://api.apify.com/v2/acts/parseforge~dat-freight-rates-scraper(Bearer TOKEN). Get token: https://console.apify.com/account/integrations

DAT Freight & Analytics runs the largest load board in North America, and the Trendlines pages it publishes are the closest thing the trucking industry has to a public price index. This scraper turns those pages into a flat Apify dataset. Every run captures the national rate history (spot and contract, weekly and monthly, going back roughly three years), the load-to-truck ratio for every US state and Canadian province, the week, month, and year-over-year percentage moves, and the current national diesel reference price. The output is one row per data point, which is the shape spreadsheets, Postgres, and pandas already speak.

Freight brokers, dispatchers, and 3PL pricing teams check DAT daily to figure out what a lane should pay. When the dashboard hangs or the iQ subscription is between renewals, the only fallback is calling carriers one by one. This actor gives you a programmatic version of the public Trendlines view, so quotes go out backed by current numbers and contract negotiations cite the same baseline both sides reference. Pair it with a scheduled Apify run and you have a daily rate sheet feeding your CRM, BI tool, or rate sheet, with zero scraping plumbing to maintain.

📋 What the DAT Freight Rates Scraper does

• 📡 National rate history. Monthly buckets back ~3 years and weekly buckets back ~1 year, with the average rate per mile in USD plus the average fuel surcharge per trip.
• 🚚 Load-to-truck ratio per state. One row per US state and Canadian province for van, flatbed, and reefer, with the load count, truck count, and computed ratio.
• 📈 Trend percentages. Week, month, and year-over-year change for spot rate, load-to-truck ratio, load postings, truck postings, and fuel.
• ⛽ National diesel price. The reference price per gallon DAT publishes alongside the rates.
• 🎛️ Smart filters. Restrict by equipment (van, flatbed, reefer, intermodal), rate type (spot shipper-to-broker, spot broker-to-carrier, contract), country (US, CA), period type (month, week), or state code.
• 🧾 One flat row per data point. Every dataset writes to the same shape, so SQL joins and pandas pivots are trivial.

Every record carries its source URL on dat.com, the dataset tag, every relevant filter (equipment, rate type, country, state, period), the numeric values, and a precise scrape timestamp. The schema is stable, so daily appends stitch into a clean longitudinal store.

💡 Why it matters: A broker who avoids one underquoted load per week saves hundreds of dollars in margin. Owning a current rate feed instead of refreshing a vendor dashboard ten times an hour pays for itself within the first month.

🎬 Full Demo

🚧 Coming soon: a 3-minute walkthrough of the input form, a sample run, and a Google Sheets dashboard that consumes the dataset.

⚙️ Input

Example: van and reefer monthly US spot rates plus load-to-truck for Texas and California.

{
"datasets":["national_history","load_truck_ratio"],
"equipments":["VAN","REEFER"],
"rateTypes":["SHIPPER_TO_BROKER_SPOT"],
"countries":["US"],
"periodTypes":["Month"],
"states":["TX","CA"]
}

Example: full national snapshot for a daily warehousing job.

{
"datasets":["national_history","load_truck_ratio","national_trends","fuel_price"],
"equipments":["VAN","FLATBED","REEFER"],
"rateTypes":["SHIPPER_TO_BROKER_SPOT","BROKER_TO_CARRIER_SPOT","CONTRACT"],
"countries":["US","CA"],
"periodTypes":["Month","Week"]
}

⚠️ Good to Know: This actor pulls from the public Trendlines API that powers dat.com/trendlines. The numbers are the same ones DAT publishes to the general public. Lane-level rates (specific origin-destination city pairs) are gated behind DAT's paid iQ subscription and are not part of this scraper's scope.

📊 Output

Every record is one flat object representing a single data point from one of the four datasets.

🧾 Schema

📦 Sample records

✨ Why choose this Actor

📊 A full run with default filters produces roughly 1,800 records covering three years of national rate history, current state-level supply/demand for three equipment categories, every published trend percentage, and the latest diesel reference price.

📈 How it compares to alternatives

If you want a turnkey freight market data feed without paying a paid index subscription or maintaining your own crawler, this actor is the shortest path.

🚀 How to use

1. 📝 Sign up for Apify. Create a free account at console.apify.com/sign-up?fpr=vmoqkp.
2. 🎛️ Pick your datasets. Leave the defaults to grab everything, or narrow to just national_history for a pure time-series pull.
3. 🔍 Set your filters. Choose equipment, rate type, country, period granularity, and optional state codes.
4. ▶️ Run. Click Start and watch the dataset fill.
5. 📤 Export. Pull JSON, CSV, or XLSX, or wire the dataset into Make, Zapier, BigQuery, Postgres, or your own webhook.

⏱️ Total time: Under two minutes from sign-up to first dataset row.

💼 Business use cases

🌟 Beyond business use cases

Data like this powers more than commercial workflows. The same structured records support research, education, civic projects, and personal initiatives.

🔌 Automating DAT Freight Rates Scraper

Wire this actor into the rest of your stack with a few lines of code or a saved schedule.

• 🟢 Node.js client for calling the actor from JavaScript or TypeScript projects.
• 🐍 Python client for notebooks, FastAPI endpoints, or Airflow DAGs.
• 📚 Apify API reference for raw REST integration in any language.

Schedules turn this actor into a low-cost market data subscription. Run it daily for an always-fresh rate sheet feeding your CRM, hourly during contract season for rapid bid reactions, or weekly for a longitudinal warehouse you can backfill into BigQuery or Postgres. The dataset chains naturally with downstream actors and webhooks, so you can branch on a load-to-truck ratio threshold or post a Slack alert when the national diesel price moves more than a configured percentage.

❓ Frequently Asked Questions

🔌 Integrate with any app

• Zapier - route every new dataset row to spreadsheets, Slack, or your CRM.
• Make - chain Apify runs into visual automations with conditional logic.
• n8n - self-hosted workflows for full data ownership.
• Google Sheets - drop CSV exports into shared sheets for rate-desk review.
• Airtable - structured base for cross-equipment rate trackers.
• Slack - push spread alerts and tight-supply notifications straight into channels.

🔗 Recommended Actors

• 📰 Freightwaves Scraper - freight news, analytics, and SONAR commentary alongside this rate feed.
• 🛡️ FMCSA Carrier Safety Scraper - safety ratings and inspection history for carriers you are about to dispatch.
• 📦 UPS Package Tracking Scraper - parcel-side visibility to complement truckload rates.
• 🚚 FedEx Package Tracking Scraper - second parcel network for end-to-end shipment dashboards.
• 📈 FRED Economic Data Scraper - macro indicators (fuel CPI, freight indices, GDP) to contextualise the freight cycle.

💡 Pro Tip: browse the complete ParseForge collection for more logistics, freight, and market-data actors.

🆘 Need Help? Open our contact form and we will respond within one business day.

⚠️ Disclaimer: This actor extracts publicly available freight market data from the DAT Trendlines pages for informational purposes only. None of the data returned constitutes pricing or financial advice. You are responsible for ensuring your use complies with DAT's terms of service and any obligations that apply in your jurisdiction, especially when redistributing data.