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NGL Energy Partners LP: accumulated other comprehensive income or loss

Accumulated other comprehensive income or loss for NGL Energy Partners LP. Inspect selected reporting periods, original units and SEC filing links; download the financial history.

All NGL Energy Partners LP financial histories

What this measure means

Cumulative other comprehensive items after tax, such as translation and unrealized hedging or securities effects. These amounts have not passed through net income.

Exact concept: us-gaap:AccumulatedOtherComprehensiveIncomeLossNetOfTax. Each value is a balance at the reporting date, not a flow earned over a year. Different units remain separate; no currency conversion or interpolation is applied.

Coverage of this history

Selected reporting periods run from 2013-03-31 to 2026-03-31. The SEC response was captured on 2026-09-20.

Selected filing history

Accumulated other comprehensive income or loss in original reported units, latest-filed observation per period
Period startPeriod endValueUnitFiledSource filing
At date2026-03-310USD2026-05-2810-K · 0001504461-26-000012
At date2025-03-319,000USD2026-05-2810-K · 0001504461-26-000012
At date2024-03-31-499,000USD2025-05-2910-K · 0001504461-25-000014
At date2023-03-31-450,000USD2024-06-0610-K · 0001504461-24-000013
At date2022-03-31-308,000USD2023-05-3110-K · 0001504461-23-000041
At date2021-03-31-266,000USD2022-06-0610-K · 0001504461-22-000010
At date2020-03-31-385,000USD2021-06-0310-K · 0001504461-21-000025
At date2019-03-31-255,000USD2020-06-0110-K · 0001504461-20-000022
At date2018-03-31-1,815,000USD2019-05-3010-K · 0001504461-19-000038
At date2017-03-31-1,828,000USD2018-05-3010-K · 0001504461-18-000024
At date2016-03-31-157,000USD2017-05-2610-K · 0001504461-17-000019
At date2015-12-31-148,000USD2016-05-3110-K · 0001504461-16-000020
At date2015-09-30-136,000USD2016-05-3110-K · 0001504461-16-000020
At date2015-06-30-117,000USD2016-05-3110-K · 0001504461-16-000020
At date2015-03-31-109,000USD2016-05-3110-K · 0001504461-16-000020
At date2014-12-31-89,000USD2016-05-3110-K · 0001504461-16-000020
At date2014-09-30-73,000USD2016-05-3110-K · 0001504461-16-000020
At date2014-06-30-51,000USD2016-05-3110-K · 0001504461-16-000020
At date2014-03-31-236,000USD2015-06-0110-K · 0001104659-15-042429
At date2013-03-3124,000USD2014-05-3010-K · 0001104659-14-042788

Related financial histories

Inspect the source

Entity
NGL Energy Partners LP / CIK 0001504461
Captured
2026-09-20T09:12:09.647Z
SEC response SHA-256
14ba990d3cf36d5e7ae8ac6320a63f21b781c4bb39a44868ddd630c8e0ac49af

Current SEC company facts · Download the original response snapshot (gzip) · Download the selected JSON

Latest-filed annual-report facts per unit and reporting period at capture time. Duration facts cover 300 to 400 days. This selection can include restatements and is not a point-in-time backtest dataset. Missing concepts are omitted, never zero-filled. Values retain original units and are not currency converted. Extended concepts require compatible unit shapes and at least three reporting ends with changing values within one unit. Constant or incompatible added histories are omitted.

Public company accounting reference, not market prices, returns, an investment recommendation, or ALPHAC performance. Validate a separately constructed return series with the validation API; accounting values are not returns.

Use this in research

A financial period ends before its results become public. Use the filing date as a minimum availability boundary, inspect amendments, and retain the original filing vintage when testing historical signals. This latest-filed selection can contain information unavailable at the time.

These pages do not supply prices, total-return histories, corporate-action adjustments or a tradable universe. Build those inputs separately before evaluating a strategy. A profitable backtest can still reflect selection bias or costs that were left out.

Research methodology · Execution and cost assumptions · Check backtest overfitting

Build with the open-source tools

Use these accounting records as inspectable inputs. When you have constructed a return series, the validation tools can help test its statistical evidence and preserve the result with its limitations.

Read the published dataset with Python
import json
from urllib.request import urlopen

with urlopen("https://canlicapital.com/company-data/0001504461.json") as response:
    record = json.load(response)
print(record["fetched_at"])
print(record["policy"])
for concept in record["concepts"]:
    print(concept["tag"], next(iter(concept["observations"])))