Every DOE 202(c) emergency order of 2025-2026 in one CSV: 66 this year, and emergency orders in force on 76 days

Description and use

The project compiled all 85 DOE 202(c) orders for 2025–2026 into a single CSV and created a Python script to validate their counts.

Problem

The U.S. Department of Energy publishes emergency orders as text on its website, making it difficult to aggregate and analyze them efficiently.

Outcome

The project produced a validated CSV of 85 DOE 202(c) orders for 2025-2026, enabling quick analysis of order counts, durations, and geographic distribution. The Python script and tests ensure data integrity.

Workflow

• 1. Scraped DOE 2025 and 2026 order pages.
• 2. Parsed order details (date, area, plant) into a structured format.
• 3. Exported the data to a CSV file.
• 4. Wrote a Python script using the standard library to load the CSV and count rows.
• 5. Added unit tests to compare the script’s counts with the official DOE table.
• 6. Hosted the code and data on GitHub under an Apache-2.0 license.
• 7. Published the results on Dev.to with a link to the repository.

Evidence

I put every order, extension and amendment from DOE's 2025 and 2026 pages into one CSV (85 rows), with a small standard-library Python script whose tests check the counts against the table.

Source

The data is CC BY 4.0 and the code is Apache-2.0: https://github.com/munimtechnologies/eia860m-slip/blob/main/docs/doe-202c-orders.md

Source