diff --git a/CHANGELOG.md b/CHANGELOG.md
index ec5745c7a1293df9234d97cdd047a9a7ddc49a95..3409d90b0f40720f9ba0238b310cc8aaa454347d 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -9,7 +9,6 @@ SPDX-License-Identifier: GPL-3.0-or-later
 [List of commits](https://git.ufz.de/rdm-software/saqc/-/compare/v2.5.0...develop)
 ### Added
 - `generics`: target broadcasting and numpy array support
-- `flagGeneric`: target broadcasting
 - `SaQC`: automatic translation of incoming flags
 - Option to change the flagging scheme after initialization
 - `flagByClick`: manually assign flags using a graphical user interface
diff --git a/saqc/funcs/generic.py b/saqc/funcs/generic.py
index 165190ce8713f03da06842ef9ad9e3b1a67b22cd..56c00bb2505ad27aa95adb4ed3688beb821eafcc 100644
--- a/saqc/funcs/generic.py
+++ b/saqc/funcs/generic.py
@@ -83,15 +83,17 @@ def _inferBroadcast(obj, trg_shape) -> pd.DataFrame:
         return np.full(trg_shape, obj)
     return obj
 
+
 def _inferDF(obj, cols, index):
     # infer dataframe if result is numpy array of fitting shape
     if isinstance(obj, np.ndarray):
         lc = len(cols)
         li = len(index)
-        if (obj.shape == (li,lc)) or (obj.shape == (li,)):
+        if (obj.shape == (li, lc)) or (obj.shape == (li,)):
             return pd.DataFrame(obj, columns=cols, index=index)
     return obj
 
+
 def _castResult(obj) -> DictOfSeries:
     # Note: the actual keys aka. column names
     # we use here to create a DictOfSeries