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Pentair plc: research and development expense

Research and development expense for Pentair plc. Inspect selected reporting periods, original units and SEC filing links; download the financial history.

All Pentair plc financial histories

What this measure means

Research and development costs recognized as expense. Capitalization policies and acquired projects can make this differ from total cash invested in development.

Exact concept: us-gaap:ResearchAndDevelopmentExpense. Each value covers an annual-duration reporting interval, shown with both start and end dates. Different units remain separate; no currency conversion or interpolation is applied.

Coverage of this history

Selected reporting periods run from 2008-01-01 to 2025-12-31. The SEC response was captured on 2026-09-19.

Selected filing history

Research and development expense in original reported units, latest-filed observation per period
Period startPeriod endValueUnitFiledSource filing
2025-01-012025-12-3195,900,000USD2026-02-2410-K · 0000077360-26-000007
2024-01-012024-12-3193,600,000USD2026-02-2410-K · 0000077360-26-000007
2023-01-012023-12-3199,800,000USD2026-02-2410-K · 0000077360-26-000007
2022-01-012022-12-3192,200,000USD2025-02-2510-K · 0000077360-25-000006
2021-01-012021-12-3185,900,000USD2024-02-2010-K · 0000077360-24-000007
2020-01-012020-12-3175,700,000USD2023-02-2110-K · 0000077360-23-000006
2019-01-012019-12-3178,900,000USD2022-02-2210-K · 0000077360-22-000006
2018-01-012018-12-3176,700,000USD2021-02-1610-K · 0000077360-21-000005
2017-01-012017-12-3173,200,000USD2020-02-2510-K · 0000077360-20-000006
2016-01-012016-12-3173,300,000USD2019-02-1910-K · 0000077360-19-000006
2015-01-012015-12-3198,700,000USD2018-02-2710-K · 0000077360-18-000007
2014-01-012014-12-3196,400,000USD2017-02-2110-K · 0000077360-17-000008
2013-01-012013-12-31122,800,000USD2016-02-2610-K · 0000077360-16-000058
2012-01-012012-12-3192,300,000USD2015-02-2410-K · 0000077360-15-000007
2011-01-012011-12-3178,200,000USD2014-02-2510-K · 0000077360-14-000010
2010-01-042010-12-3167,156,000USD2013-02-2610-K · 0001193125-13-077034
2010-01-012010-12-3167,156,000USD2012-04-1310-K/A · 0001193125-12-162828
2009-01-012009-12-3157,884,000USD2012-04-1310-K/A · 0001193125-12-162828
2008-01-012008-12-3162,450,000USD2011-02-2310-K · 0000950123-11-016702

Related financial histories

Inspect the source

Entity
Pentair plc / CIK 0000077360
Captured
2026-09-19T11:13:46.600Z
SEC response SHA-256
6e53bdf7b8d6c97ab74ccf05b0546ac311908ea094021bab8dd19bce2b336e1c

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/0000077360.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"])))