Compare State Gas Prices for Travel Cost Planning

TL;DR — The Fuel Prices Scraper exports AAA's per-state gas averages as JSON. Compare the states on your route, plan fills on the cheap side of borders, and price the trip on the day's actual data.

Why fuel stops are a planning decision

Interstate price gaps are structural — taxes, formulations, distance from supply. A route through five states crosses five different fuel markets, and the difference between filling in one versus the next is real money over a long trip.

The job-to-be-done: a current per-state table, joined to your route, that answers "where should I buy."

How does this compare to the alternatives?

Pump-level apps win in the moment. For pre-trip budgeting and recurring route costing, a state-level data pull is the right grain.

How to compare in 4 steps

How do I pull my route's states?

import os
from apify_client import ApifyClient

client = ApifyClient(os.environ["APIFY_TOKEN"])
run = client.actor("thirdwatch/fuel-prices-scraper").call(
    run_input={"states": ["nevada", "california", "oregon", "arizona", "utah"]}
)
rows = list(client.dataset(run["defaultDatasetId"]).iterate_items())

How do I rank the fill stops?

import pandas as pd
df = pd.DataFrame(rows)
print(df[["region", "regular", "diesel"]].sort_values("regular"))

Cheapest first — those are your planned fill states.

How do I estimate the trip cost?

MPG, TANK = 28, 15
legs = {"nevada": 300, "california": 450, "oregon": 250}  # miles per state
cost = sum(m / MPG * df.set_index("region").loc[s.title(), "regular"]
           for s, m in legs.items())
print(f"Estimated fuel cost: ${cost:.0f}")

How do I keep estimates honest?

Refresh the pull the week of departure — week_ago and month_ago columns show whether prices are rising or stable, so you know if today's estimate will hold.

Sample output

{"region": "Arizona", "scope": "state:az", "date": "2026-09-21",
 "regular": 3.55, "mid_grade": 3.84, "premium": 4.10,
 "diesel": 3.72, "e85": 2.91,
 "yesterday": 3.54, "week_ago": 3.50, "month_ago": 3.62, "year_ago": 3.48}

Common pitfalls

State averages mask metro premiums — resort and urban areas run above the mean. Border-town stations know their advantage; the average understates what you'll actually pay at the convenient stop. Prices move daily — refresh close to departure. The actor supplies the comparison; the detour math stays yours.

Related use cases

• Track gas prices by state for fleet costs
• Monitor fuel price trends for logistics budgets
• Build a fuel cost model with AAA data
• Blog hub