diff --git a/CHANGELOG.md b/CHANGELOG.md
index 6731aa25e3a53a09da14156df029fb9f6976d5a7..839310af7c89e234921ce0d54afdbadd97558a88 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -9,6 +9,7 @@ SPDX-License-Identifier: GPL-3.0-or-later
## Unreleased
[List of commits](https://git.ufz.de/rdm-software/saqc/-/compare/v2.3.0...develop)
### Added
+- Methods `logicalAnd` and `logicalOr`
### Changed
### Removed
### Fixed
diff --git a/saqc/funcs/flagtools.py b/saqc/funcs/flagtools.py
index 80420a1cdd18ac939a7981a0cda961219e263b3a..d378c70af9e58009eaedcde790da754b5a3c4a95 100644
--- a/saqc/funcs/flagtools.py
+++ b/saqc/funcs/flagtools.py
@@ -7,8 +7,9 @@
# -*- coding: utf-8 -*-
from __future__ import annotations
+import operator
import warnings
-from typing import TYPE_CHECKING, Any, Union
+from typing import TYPE_CHECKING, Any, Callable, Sequence, Union
import numpy as np
import pandas as pd
@@ -17,6 +18,7 @@ from typing_extensions import Literal
from dios import DictOfSeries
from saqc.constants import BAD, FILTER_ALL, UNFLAGGED
from saqc.core.register import _isflagged, flagging, register
+from saqc.lib.tools import toSequence
if TYPE_CHECKING:
from saqc.core.core import SaQC
@@ -531,3 +533,139 @@ class FlagtoolsMixin:
self._flags[repeated, field] = flag
return self
+
+ @register(
+ mask=["field"],
+ demask=["field"],
+ squeeze=["field"],
+ multivariate=False,
+ handles_target=True,
+ )
+ def andGroup(
+ self: "SaQC",
+ field: str,
+ group: Sequence["SaQC"] | dict["SaQC", str | Sequence[str]],
+ target: str | None = None,
+ flag: float = BAD,
+ **kwargs,
+ ) -> "SaQC":
+ """
+ Flag all values, if a given variable is also flagged in all other given SaQC objects.
+
+ Parameters
+ ----------
+ field : str
+ Name of the field to check for flags. 'field' needs to present in all
+ objects in 'qcs'.
+
+ qcs : list of SaQC
+ A list of SaQC objects to check for flags.
+
+ target : str, default none
+ Name of the field the generated flags will be written to. If None, the result
+ will be written to 'field',
+
+ flag: float, default ``BAD``
+ The quality flag to set.
+
+ Returns
+ -------
+ saqc.SaQC
+ """
+
+ return _groupOperation(
+ base=self,
+ field=field,
+ target=target,
+ func=operator.and_,
+ group=group,
+ flag=flag,
+ **kwargs,
+ )
+
+ @register(
+ mask=["field"],
+ demask=["field"],
+ squeeze=["field"],
+ multivariate=False,
+ handles_target=True,
+ )
+ def orGroup(
+ self: "SaQC",
+ field: str,
+ group: Sequence["SaQC"] | dict["SaQC", str | Sequence[str]],
+ target: str | None = None,
+ flag: float = BAD,
+ **kwargs,
+ ) -> "SaQC":
+ """
+ Flag all values, if a given variable is also flagged in at least one other of the given SaQC objects.
+
+ Parameters
+ ----------
+ field : str
+ Name of the field to check for flags. 'field' needs to present in all
+ objects in 'qcs'.
+
+ qcs : list of SaQC
+ A list of SaQC objects to check for flags.
+
+ target : str, default none
+ Name of the field the generated flags will be written to. If None, the result
+ will be written to 'field',
+
+ flag: float, default ``BAD``
+ The quality flag to set.
+
+ Returns
+ -------
+ saqc.SaQC
+ """
+ return _groupOperation(
+ base=self,
+ field=field,
+ target=target,
+ func=operator.or_,
+ group=group,
+ flag=flag,
+ **kwargs,
+ )
+
+
+def _groupOperation(
+ base: "SaQC",
+ field: str,
+ func: Callable[[pd.Series, pd.Series], pd.Series],
+ group: Sequence["SaQC"] | dict["SaQC", str | Sequence[str]],
+ target: str | None = None,
+ flag: float = BAD,
+ **kwargs,
+) -> "SaQC":
+ # Should this be multivariate? And what would multivariate mean in this context
+
+ dfilter = kwargs.get("dfilter", FILTER_ALL)
+ if target is None:
+ target = field
+
+ # harmonise `group` to type dict[SaQC, list[str]]
+ if not isinstance(group, dict):
+ group = {qc: field for qc in group}
+
+ for k, v in group.items():
+ group[k] = toSequence(v)
+
+ qcs_items: list[tuple["SaQC", list[str]]] = list(group.items())
+ # generate initial mask from the first `qc` object on the popped first field
+ mask = _isflagged(qcs_items[0][0]._flags[qcs_items[0][1].pop(0)], thresh=dfilter)
+
+ for qc, fields in qcs_items:
+ if field not in qc._flags:
+ raise KeyError(f"variable {field} is missing in given SaQC object")
+ for field in fields:
+ mask = func(mask, _isflagged(qc._flags[field], thresh=FILTER_ALL))
+
+ if target not in base._data:
+ base = base.copyField(field=field, target=target)
+
+ base._flags[mask, target] = flag
+ return base
diff --git a/tests/funcs/test_flagtools.py b/tests/funcs/test_flagtools.py
index 457edab8ab666175cafc9bb5df6cf01f5bb70af1..f885c91e1a106d44ac69f2fe22784d4fcb6ff47d 100644
--- a/tests/funcs/test_flagtools.py
+++ b/tests/funcs/test_flagtools.py
@@ -4,15 +4,16 @@
#
# SPDX-License-Identifier: GPL-3.0-or-later
+import operator
+
import numpy as np
import pandas as pd
-
-# -*- coding: utf-8 -*-
import pytest
from saqc import BAD as B
from saqc import UNFLAGGED as U
from saqc import SaQC
+from saqc.funcs.flagtools import _groupOperation
N = np.nan
@@ -98,3 +99,70 @@ def test_propagateFlagsIrregularIndex(got, expected, kwargs):
saqc = SaQC(data=data, flags=flags).propagateFlags(field="x", **kwargs)
result = saqc._flags.history["x"].hist[1].astype(float)
assert result.equals(expected)
+
+
+@pytest.mark.parametrize(
+ "left,right,expected",
+ [
+ ([B, U, U, B], [B, B, U, U], [B, U, U, U]),
+ ([B, B, B, B], [B, B, B, B], [B, B, B, B]),
+ ([U, U, U, U], [U, U, U, U], [U, U, U, U]),
+ ],
+)
+def test_andGroup(left, right, expected):
+
+ data = pd.DataFrame({"data": [1, 2, 3, 4]})
+
+ base = SaQC(data=data)
+ this = SaQC(data=data, flags=pd.DataFrame({"data": pd.Series(left)}))
+ that = SaQC(data=data, flags=pd.DataFrame({"data": pd.Series(right)}))
+ result = base.andGroup(field="data", group=[this, that])
+
+ assert pd.Series(expected).equals(result.flags["data"])
+
+
+@pytest.mark.parametrize(
+ "left,right,expected",
+ [
+ ([B, U, U, B], [B, B, U, U], [B, B, U, B]),
+ ([B, B, B, B], [B, B, B, B], [B, B, B, B]),
+ ([U, U, U, U], [U, U, U, U], [U, U, U, U]),
+ ],
+)
+def test_orGroup(left, right, expected):
+
+ data = pd.DataFrame({"data": [1, 2, 3, 4]})
+
+ base = SaQC(data=data)
+ this = SaQC(data=data, flags=pd.DataFrame({"data": pd.Series(left)}))
+ that = SaQC(data=data, flags=pd.DataFrame({"data": pd.Series(right)}))
+ result = base.orGroup(field="data", group=[this, that])
+
+ assert pd.Series(expected).equals(result.flags["data"])
+
+
+@pytest.mark.parametrize(
+ "left,right,expected",
+ [
+ ([B, U, U, B], [B, B, U, U], [B, B, U, B]),
+ ([B, B, B, B], [B, B, B, B], [B, B, B, B]),
+ ([U, U, U, U], [U, U, U, U], [U, U, U, U]),
+ ],
+)
+def test__groupOperation(left, right, expected):
+
+ data = pd.DataFrame(
+ {"x": [0, 1, 2, 3], "y": [0, 11, 22, 33], "z": [0, 111, 222, 333]}
+ )
+ base = SaQC(data=data)
+ this = SaQC(
+ data=data, flags=pd.DataFrame({k: pd.Series(left) for k in data.columns})
+ )
+ that = SaQC(
+ data=data, flags=pd.DataFrame({k: pd.Series(right) for k in data.columns})
+ )
+ result = _groupOperation(
+ base=base, field="x", func=operator.or_, group={this: "y", that: ["y", "z"]}
+ )
+
+ assert pd.Series(expected).equals(result.flags["x"])