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AGILENT TECHNOLOGIES, INC.: current accounts payable

Current accounts payable for AGILENT TECHNOLOGIES, INC. Inspect selected reporting periods, original units and SEC filing links; download the financial history.

All AGILENT TECHNOLOGIES, INC. financial histories

What this measure means

Current amounts owed to suppliers for goods and services received. This is one component of current liabilities, not all accrued obligations.

Exact concept: us-gaap:AccountsPayableCurrent. 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 2008-10-31 to 2025-10-31. The SEC response was captured on 2026-09-19.

Selected filing history

Current accounts payable in original reported units, latest-filed observation per period
Period startPeriod endValueUnitFiledSource filing
At date2025-10-31570,000,000USD2025-12-2210-K · 0001090872-25-000087
At date2024-10-31540,000,000USD2025-12-2210-K · 0001090872-25-000087
At date2023-10-31418,000,000USD2024-12-2010-K · 0001090872-24-000049
At date2022-10-31580,000,000USD2023-12-2010-K · 0001090872-23-000020
At date2021-10-31446,000,000USD2022-12-2110-K · 0001090872-22-000026
At date2020-10-31354,000,000USD2021-12-1710-K · 0001090872-21-000027
At date2019-10-31354,000,000USD2020-12-1810-K · 0001090872-20-000020
At date2018-11-01340,000,000USD2019-12-1910-K · 0001090872-19-000022
At date2018-10-31340,000,000USD2019-12-1910-K · 0001090872-19-000022
At date2017-10-31305,000,000USD2018-12-2010-K · 0001090872-18-000019
At date2016-10-31257,000,000USD2017-12-2110-K · 0001090872-17-000018
At date2015-10-31279,000,000USD2016-12-2010-K · 0001090872-16-000082
At date2014-10-31302,000,000USD2015-12-2110-K · 0001090872-15-000051
At date2013-10-31432,000,000USD2014-12-2210-K · 0001090872-14-000045
At date2012-10-31461,000,000USD2013-12-1910-K · 0001090872-13-000029
At date2011-10-31472,000,000USD2012-12-2010-K · 0001090872-12-000018
At date2010-10-31499,000,000USD2011-12-1610-K · 0001047469-11-010124
At date2009-10-31307,000,000USD2010-12-2010-K · 0001047469-10-010499
At date2008-10-31308,000,000USD2009-12-2110-K · 0001047469-09-010861

Related financial histories

Inspect the source

Entity
AGILENT TECHNOLOGIES, INC. / CIK 0001090872
Captured
2026-09-19T11:16:24.066Z
SEC response SHA-256
c1dc449b186de4294c8dbdbb9e3b0f74eee3628c3fc5836652ff7ab8c2040ac9

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/0001090872.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"])))