# US Airport-Pair Fares & Route Traffic — DOT DB1B Benchmarks (`nexgensignal/us-airport-pair-fare-records`) Actor

US DOT DB1B average fares and traffic by city-pair market and quarter — distance, passengers, fare and carrier shares for route economics and competitive benchmarking.

- **URL**: https://apify.com/nexgensignal/us-airport-pair-fare-records.md
- **Developed by:** [NexGen Signal](https://apify.com/nexgensignal) (community)
- **Categories:** Business
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $33.50 / 1,000 fare records

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.
Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have.

Learn more: https://docs.apify.com/actors/running/actors-in-store.md#pay-per-event

## What's an Apify Actor?

Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.
Actors are written with capital "A".

## How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.
The best way to integrate Actors is as follows.

- **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use).
- **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`.
- **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`.
- **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`.
- **Any other language** — the [REST API](https://docs.apify.com/api/v2.md).

For usage examples, see the [API](#api) section below.

For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt).

# README

## US Airport-Pair Fare Benchmarks — Quarterly Markets, Per Record

**Official source. No API key. Pay per record.**

### Who this is for and the decision it supports

Airline network planners, travel-analytics and pricing teams benchmarking average fares and traffic on US city-pair markets (US DOT DB1B).

One record answers: for this origin-destination market and quarter, what were the average fare, traffic and the largest/lowest-fare carrier shares — a route-economics and competitive benchmark.

### What one record is

Each record is one DB1B city-pair market x quarter: city and airport ids, distance, passengers, average fare, and largest/lowest-fare carrier and their market shares and fares.

### Your first run

Paste this input and run it:

```json
{
  "maxRecords": 10
}
```

Run it and get clean per-market fare rows immediately — no DB1B zip wrangling. Here is a real record from that exact input:

```json
{
  "record_id": "199311013510986ABECHI",
  "tbl": "Table 1a",
  "year": 1993,
  "quarter": 1,
  "citymarketid_1": 30135,
  "citymarketid_2": 30977,
  "city1": "Allentown/Bethlehem/Easton, PA",
  "city2": "Chicago, IL",
  "airportid_1": 10135,
  "airportid_2": 10986,
  "airport_1": "ABE",
  "airport_2": "CHI"
}
```

**What the sample costs:** $0.05 per record. The sample above delivers 10 records, so it costs at most **$0.50**.

### Pulling in bulk

Raise Maximum records to pull the full historical panel of US city-pair markets. A buyer pulls the full multi-decade panel to model fare trends, market concentration and route economics.

To expand from the sample: raise **Maximum records**, and widen any filters shown in the input. You are billed only for records actually delivered, so a sample stays cheap and a full pull is predictable.

### When to run it again

US DOT publishes DB1B quarterly; the actor returns the full series (earliest quarters first).

**Update schedule:** Quarterly — US DOT releases DB1B each quarter with a lag. Verified live: records carry year and quarter; the source is the official DB1B market table.

### How this is different

US airport-PAIR (route/market) fares and traffic — distinct from the country-level EU Air Passenger Flow actor. This is route-level economics.

### Limitations (source coverage vs product coverage)

- ROUTE/MARKET level (city-pair), and fares are AVERAGE market fares over a quarter — not bookable, current, or itinerary-level prices.
- By default the newest available quarter is returned first (currently 2026 Q1). Use the **year** (and optional **quarter**) inputs for a historical window; the full multi-decade panel back to 1993 stays reachable. Each record is one market-quarter, unique on the source key (tbl1apk).
- Excludes some ticket types per DB1B methodology.

### FAQ

**Are these current bookable fares?**

No. They are quarterly average market fares from US DOT DB1B, historical by design.

**Can I pull only the latest quarter?**

Yes. Leave year blank for the newest quarter first; set year (and optional quarter) for a historical window, e.g. year=1993, quarter=1. An unavailable period returns an honest empty result.

**Route or country level?**

Route/market (city-pair) level.

### Related actors

- eu-air-passenger-flow-records — country-level EU air passenger volumes
- company-data-enrichment-api — resolve carriers to legal entities
- world-bank-project-records — transport-sector development projects

### Source, licence and how it is built

Source and licence are carried on every record (`source`, `licence`, `attribution`, `observed_at`). The actor reads only the official public endpoint, honours the source's robots and licence terms, and emits values unmodified with full provenance. Records are keyed on a stable id so re-runs upsert cleanly into a table you keep. Row delivery and billing are exactly equal: you are charged once per record delivered (push-then-charge), so an empty run costs nothing.

Part of NexGen Signal — official-source data products.

# Actor input Schema

## `maxRecords` (type: `integer`):

Maximum records delivered and billed. You are billed only for records actually delivered. Raise it to pull the full set.

## `year` (type: `string`):

Leave blank for the latest available quarter first. Set a 4-digit year (e.g. 2026) for a historical window.

## `quarter` (type: `string`):

Optional quarter within the chosen year.

## Actor input object example

```json
{
  "maxRecords": 10,
  "year": "",
  "quarter": ""
}
```

# Actor output Schema

## `results` (type: `string`):

The delivered US airport-pair fare benchmark record.

# API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

## JavaScript example

```javascript
import { ApifyClient } from 'apify-client';

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {
    "maxRecords": 10,
    "year": "",
    "quarter": ""
};

// Run the Actor and wait for it to finish
const run = await client.actor("nexgensignal/us-airport-pair-fare-records").call(input);

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

```

## Python example

```python
from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = {
    "maxRecords": 10,
    "year": "",
    "quarter": "",
}

# Run the Actor and wait for it to finish
run = client.actor("nexgensignal/us-airport-pair-fare-records").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{
  "maxRecords": 10,
  "year": "",
  "quarter": ""
}' |
apify call nexgensignal/us-airport-pair-fare-records --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,nexgensignal/us-airport-pair-fare-records"
        }
    }
}

```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/X2FZzEWVORD0QTcxi/builds/7O9gyfqp773eDUgIe/openapi.json