fix(CSVDocumentSplitter): use positional column index instead of column label

haystack/components/preprocessors/csv_document_splitter.py

@@ -145,8 +145,10 @@ def run(self, documents: list[Document]) -> dict[str, list[Document]]:
                 )
                 continue
 
-            # Sort split_dfs first by row index, then by column index
-            split_dfs.sort(key=lambda dataframe: (dataframe.index[0], dataframe.columns[0]))
+            # Sort split_dfs first by row index, then by column index. Column
+            # labels can be non-integer strings when read_csv_kwargs sets
+            # header, so sort by positional index instead of the label.
+            split_dfs.sort(key=lambda dataframe: (dataframe.index[0], df.columns.get_loc(dataframe.columns[0])))
 
             for split_id, split_df in enumerate(split_dfs):
                 split_documents.append(
@@ -156,7 +158,7 @@ def run(self, documents: list[Document]) -> dict[str, list[Document]]:
                             **deepcopy(document.meta),
                             "source_id": document.id,
                             "row_idx_start": int(split_df.index[0]),
-                            "col_idx_start": int(split_df.columns[0]),
+                            "col_idx_start": int(df.columns.get_loc(split_df.columns[0])),
                             "split_id": split_id,
                         },
                     )

test/components/preprocessors/test_csv_document_splitter.py

@@ -398,3 +398,19 @@ def test_split_by_row_with_empty_rows(self, caplog: LogCaptureFixture) -> None:
     def test_incorrect_split_mode(self) -> None:
         with pytest.raises(ValueError, match="not recognized"):
             CSVDocumentSplitter(split_mode="incorrect_mode")  # type: ignore[arg-type]
+
+    def test_read_csv_kwargs_header_zero(self) -> None:
+        splitter = CSVDocumentSplitter(
+            row_split_threshold=1,
+            column_split_threshold=None,
+            read_csv_kwargs={"header": 0},
+        )
+        doc = Document(content="name,score\nAda,9\n\nBob,8")
+        result = splitter.run([doc])["documents"]
+        assert len(result) == 2
+        for split_doc in result:
+            assert split_doc.meta["col_idx_start"] == 0
+        assert result[0].meta["row_idx_start"] == 0
+        assert result[1].meta["row_idx_start"] == 2
+        assert "Ada,9" in result[0].content
+        assert "Bob,8" in result[1].content