Portland General Electric Co /Or/ (POR) Interest Expense (2009 - 2026)
Analysis
Portland General Electric Co /Or/ (POR) Interest Expense (2009 - 2026) Analysis & Trends
Peer Set
Peer Comparison
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 64.00 Mn |
| Mar 31, 2026 | 62.00 Mn |
| Dec 31, 2025 | 70.00 Mn |
| Sep 30, 2025 | 60.00 Mn |
| Jun 30, 2025 | 60.00 Mn |
| Mar 31, 2025 | 60.00 Mn |
| Dec 31, 2024 | 70.00 Mn |
| Sep 30, 2024 | 53.00 Mn |
| Jun 30, 2024 | 52.00 Mn |
| Mar 31, 2024 | 51.00 Mn |
| Dec 31, 2023 | 59.00 Mn |
| Sep 30, 2023 | 42.00 Mn |
| Jun 30, 2023 | 41.00 Mn |
| Mar 31, 2023 | 44.00 Mn |
| Dec 31, 2022 | 41.00 Mn |
| Sep 30, 2022 | 39.00 Mn |
| Jun 30, 2022 | 38.00 Mn |
| Mar 31, 2022 | 38.00 Mn |
| Dec 31, 2021 | 37.00 Mn |
| Sep 30, 2021 | 33.00 Mn |
API Access
Portland General Electric Co /Or/ Interest Expense 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=interest-expense&ticker=POR&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "interest-expense", "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=interest-expense&ticker=POR&period=max&api_key=YOUR_API_KEY");
const data = await res.json();