diff --git a/saqc/__main__.py b/saqc/__main__.py
index 8fbb3cb7c9cf8578a088824bfe1257d121ac652b..7b7a3c5b05f191b974fa3e4e1657f79e245ccadf 100644
--- a/saqc/__main__.py
+++ b/saqc/__main__.py
@@ -95,12 +95,12 @@ def main(config, data, flagger, outfile, nodata, log_level, fail):
     data_result, flagger_result = saqc.readConfig(config).getResult(raw=True)
 
     if outfile:
-        data_result = data_result.to_df()
-        flags = flagger_result.toFrame()
-        unflagged = (flags == UNFLAGGED) | flags.isna()
-        flags[unflagged] = GOOD
+        data_frame = data_result.to_df()
+        flags_frame = flagger_result.toFrame()
+        unflagged = (flags_frame == UNFLAGGED) | flags_frame.isna()
+        flags_frame[unflagged] = GOOD
 
-        fields = {"data": data_result, "flags": flags}
+        fields = {"data": data_frame, "flags": flags_frame}
 
         out = (
             pd.concat(fields.values(), axis=1, keys=fields.keys())
diff --git a/saqc/core/register.py b/saqc/core/register.py
index c3b3945fa01e63557ebbcfafe41740aabc2531bf..5d991e8036dd3ee21d8477486f21146db8ed0e19 100644
--- a/saqc/core/register.py
+++ b/saqc/core/register.py
@@ -249,14 +249,14 @@ def _maskData(data, flagger, columns, thresh) -> Tuple[dios.DictOfSeries, dios.D
     return data, mask
 
 
-def _isflagged(flags: Union[np.array, pd.Series], thresh: float) -> Union[np.array, pd.Series]:
+def _isflagged(flagscol: Union[np.array, pd.Series], thresh: float) -> Union[np.array, pd.Series]:
     """
     Return a mask of flags accordingly to `thresh`. Return type is same as flags.
     """
     if thresh == UNFLAGGED:
-        return flags > UNFLAGGED
+        return flagscol > UNFLAGGED
 
-    return flags >= thresh
+    return flagscol >= thresh
 
 
 def _prepareFlags(flagger: Flagger, masking) -> Flagger:
diff --git a/saqc/funcs/breaks.py b/saqc/funcs/breaks.py
index aede9d6310ba6e124f3b485c9c10c24c27f3b206..d9cbbc6d0e11735ad70888eea72a0f37d4d825a9 100644
--- a/saqc/funcs/breaks.py
+++ b/saqc/funcs/breaks.py
@@ -124,7 +124,7 @@ def flagIsolated(
 
     mask = data[field].isna()
 
-    flags = pd.Series(data=0, index=mask.index, dtype=bool)
+    bools = pd.Series(data=0, index=mask.index, dtype=bool)
     for srs in groupConsecutives(mask):
         if np.all(~srs):
             start = srs.index[0]
@@ -134,7 +134,7 @@ def flagIsolated(
                 if left.all():
                     right = mask[stop: stop + gap_window].iloc[1:]
                     if right.all():
-                        flags[start:stop] = True
+                        bools[start:stop] = True
 
     flagger[mask, field] = flag
     return data, flagger
diff --git a/tests/core/test_core.py b/tests/core/test_core.py
index c13f8a5b85eeaac88d498f7a24be092940812c51..a784cdbaceeecba991b3da662dd9a444acf4f1e5 100644
--- a/tests/core/test_core.py
+++ b/tests/core/test_core.py
@@ -86,10 +86,10 @@ def test_dtypes(data, flags):
     Test if the categorical dtype is preserved through the core functionality
     """
     flagger = initFlagsLike(data)
-    flags = flagger.toDios()
+    flags_raw = flagger.toDios()
     var1, var2 = data.columns[:2]
 
-    pdata, pflagger = SaQC(data, flags=flags).flagAll(var1).flagAll(var2).getResult(raw=True)
+    pdata, pflagger = SaQC(data, flags=flags_raw).flagAll(var1).flagAll(var2).getResult(raw=True)
 
     for c in pflagger.columns:
         assert pflagger[c].dtype == flagger[c].dtype
diff --git a/tests/funcs/test_constants_detection.py b/tests/funcs/test_constants_detection.py
index 6fcde58d1c96d5874c63f9516768ec41d32f5085..d6b7a68f8845bb420965aaf29178bebae5ab3a83 100644
--- a/tests/funcs/test_constants_detection.py
+++ b/tests/funcs/test_constants_detection.py
@@ -23,8 +23,8 @@ def test_constants_flagBasic(data):
     field, *_ = data.columns
     flagger = initFlagsLike(data)
     data, flagger_result = flagConstants(data, field, flagger, window="15Min", thresh=0.1, flag=BAD)
-    flags = flagger_result[field]
-    assert np.all(flags[expected] == BAD)
+    flagscol = flagger_result[field]
+    assert np.all(flagscol[expected] == BAD)
 
 
 def test_constants_flagVarianceBased(data):
diff --git a/tests/funcs/test_modelling.py b/tests/funcs/test_modelling.py
index 95574936aaaf56b15a6317af26e83ddd9de3c6c3..de9f1efb89ad2140522b4b58ea7ced54d324bc3e 100644
--- a/tests/funcs/test_modelling.py
+++ b/tests/funcs/test_modelling.py
@@ -54,20 +54,20 @@ def test_modelling_mask(dat):
 
     common = dict(data=data, field=field, flagger=flagger, mode='periodic')
     data_seasonal, flagger_seasonal = mask(**common, period_start="20:00", period_end="40:00", include_bounds=False)
-    flags = flagger_seasonal[field]
-    m = (20 <= flags.index.minute) & (flags.index.minute <= 40)
+    flagscol = flagger_seasonal[field]
+    m = (20 <= flagscol.index.minute) & (flagscol.index.minute <= 40)
     assert all(flagger_seasonal[field][m] == UNFLAGGED)
     assert all(data_seasonal[field][m].isna())
 
     data_seasonal, flagger_seasonal = mask(**common, period_start="15:00:00", period_end="02:00:00")
-    flags = flagger_seasonal[field]
-    m = (15 <= flags.index.hour) & (flags.index.hour <= 2)
+    flagscol = flagger_seasonal[field]
+    m = (15 <= flagscol.index.hour) & (flagscol.index.hour <= 2)
     assert all(flagger_seasonal[field][m] == UNFLAGGED)
     assert all(data_seasonal[field][m].isna())
 
     data_seasonal, flagger_seasonal = mask(**common, period_start="03T00:00:00", period_end="10T00:00:00")
-    flags = flagger_seasonal[field]
-    m = (3 <= flags.index.hour) & (flags.index.hour <= 10)
+    flagscol = flagger_seasonal[field]
+    m = (3 <= flagscol.index.hour) & (flagscol.index.hour <= 10)
     assert all(flagger_seasonal[field][m] == UNFLAGGED)
     assert all(data_seasonal[field][m].isna())