bug: remove include_groups flag

this does not work with all versions of pandas
Roestlab · Mar 28, 2024 · a1c38f0 · a1c38f0
1 parent aab89fe
commit a1c38f0
Showing 1 changed file with 3 additions and 3 deletions.
diff --git a/massdash/loaders/access/OSWDataAccess.py b/massdash/loaders/access/OSWDataAccess.py
@@ -486,7 +486,7 @@ def getIdentifiedPrecursors(self, qvalue: float = 0.01, run: Optional[str] = Non
                 WHERE SCORE_MS2.QVALUE <= {qvalue} AND PRECURSOR.DECOY = 0 AND SCORE_PEPTIDE.QVALUE <= {qvalue} AND SCORE_PROTEIN.QVALUE <= {qvalue} and SCORE_MS2.RANK == 1"""
             df = pd.read_sql(stmt, self.conn)
             df = df.merge(self.runHashTable, left_on='RUN_ID', right_on='ID')
-            return df[['RUN_NAME', 'Precursor']].groupby('RUN_NAME').apply(lambda x: set(x['Precursor']), include_groups=False).to_dict()
+            return df[['RUN_NAME', 'Precursor']].groupby('RUN_NAME').apply(lambda x: set(x['Precursor'])).to_dict()
 
     def getIdentifiedPrecursorIntensities(self, qvalue: float = 0.01, run: Optional[str] = None, precursorLevel=False):
         if isinstance(run, str):
@@ -568,7 +568,7 @@ def getIdentifiedPeptides(self, qvalue: float = 0.01, run: Optional[str] = None)
                 WHERE SCORE_PEPTIDE.QVALUE <= {qvalue} AND PEPTIDE.DECOY = 0 """
             df = pd.read_sql(stmt, self.conn)
             df = df.merge(self.runHashTable, left_on='RUN_ID', right_on='ID')
-            return df[['RUN_NAME', 'Peptide']].groupby('RUN_NAME').apply(lambda x: set(x['Peptide']), include_groups=False).to_dict()
+            return df[['RUN_NAME', 'Peptide']].groupby('RUN_NAME').apply(lambda x: set(x['Peptide'])).to_dict()
 
     def getIdentifiedProteins(self, qvalue: float = 0.01, run: Optional[str] = None) -> Union[set, Dict[str, set]]:
         if isinstance(run, str):
@@ -589,7 +589,7 @@ def getIdentifiedProteins(self, qvalue: float = 0.01, run: Optional[str] = None)
                 WHERE SCORE_PROTEIN.QVALUE <= {qvalue} AND PROTEIN.DECOY = 0 """
             df = pd.read_sql(stmt, self.conn)
             df = df.merge(self.runHashTable, left_on='RUN_ID', right_on='ID')
-            return df[['RUN_NAME', 'Protein']].groupby('RUN_NAME').apply(lambda x: set(x['Protein']), include_groups=False).to_dict()
+            return df[['RUN_NAME', 'Protein']].groupby('RUN_NAME').apply(lambda x: set(x['Protein'])).to_dict()
 
     def getSoftware(self):
         return "OpenSWATH"