Portland General Electric Co /Or/ (POR) Total Operating Expenses (2009 - 2026)
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Analysis
Portland General Electric Co /Or/ (POR) Total Operating Expenses (2009 - 2026) Analysis & Trends
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Peer Comparison
Historic Data
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Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 693.00 Mn |
| Mar 31, 2026 | 772.00 Mn |
| Dec 31, 2025 | 794.00 Mn |
| Sep 30, 2025 | 778.00 Mn |
| Jun 30, 2025 | 689.00 Mn |
| Mar 31, 2025 | 760.00 Mn |
| Dec 31, 2024 | 736.00 Mn |
| Sep 30, 2024 | 783.00 Mn |
| Jun 30, 2024 | 642.00 Mn |
| Mar 31, 2024 | 767.00 Mn |
| Dec 31, 2023 | 612.00 Mn |
| Sep 30, 2023 | 717.00 Mn |
| Jun 30, 2023 | 567.00 Mn |
| Mar 31, 2023 | 631.00 Mn |
| Dec 31, 2022 | 600.00 Mn |
| Sep 30, 2022 | 651.00 Mn |
| Jun 30, 2022 | 479.00 Mn |
| Mar 31, 2022 | 520.00 Mn |
| Dec 31, 2021 | 507.00 Mn |
| Sep 30, 2021 | 559.00 Mn |
API Access
Portland General Electric Co /Or/ Total Operating Expenses API
Pull this series into your own models, spreadsheets and apps with the Business Quant
Historical Metrics API. The request below matches the chart above — change the
frequency, period or values and it follows. Swap YOUR_API_KEY for your own key.
https://data.businessquant.com/historic?slug=total-operating-expenses&ticker=POR&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "total-operating-expenses", "ticker": "POR", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=total-operating-expenses&ticker=POR&period=max&api_key=YOUR_API_KEY");
const data = await res.json();