FIX: fix empty rows being deleted in read_excel by introducing drop_e…

…mpty_rows flag

py-polars/polars/io/spreadsheet/functions.py

@@ -55,6 +55,7 @@ def read_excel(
     schema_overrides: SchemaDict | None = ...,
     infer_schema_length: int | None = ...,
     raise_if_empty: bool = ...,
+    drop_empty_rows: bool = ...,
 ) -> pl.DataFrame: ...
 
 
@@ -72,6 +73,7 @@ def read_excel(
     schema_overrides: SchemaDict | None = ...,
     infer_schema_length: int | None = ...,
     raise_if_empty: bool = ...,
+    drop_empty_rows: bool = ...,
 ) -> pl.DataFrame: ...
 
 
@@ -89,6 +91,7 @@ def read_excel(
     schema_overrides: SchemaDict | None = ...,
     infer_schema_length: int | None = ...,
     raise_if_empty: bool = ...,
+    drop_empty_rows: bool = ...,
 ) -> NoReturn: ...
 
 
@@ -108,6 +111,7 @@ def read_excel(
     schema_overrides: SchemaDict | None = ...,
     infer_schema_length: int | None = ...,
     raise_if_empty: bool = ...,
+    drop_empty_rows: bool = ...,
 ) -> dict[str, pl.DataFrame]: ...
 
 
@@ -125,6 +129,7 @@ def read_excel(
     schema_overrides: SchemaDict | None = ...,
     infer_schema_length: int | None = ...,
     raise_if_empty: bool = ...,
+    drop_empty_rows: bool = ...,
 ) -> pl.DataFrame: ...
 
 
@@ -142,6 +147,7 @@ def read_excel(
     schema_overrides: SchemaDict | None = ...,
     infer_schema_length: int | None = ...,
     raise_if_empty: bool = ...,
+    drop_empty_rows: bool = ...,
 ) -> dict[str, pl.DataFrame]: ...
 
 
@@ -160,6 +166,7 @@ def read_excel(
     schema_overrides: SchemaDict | None = None,
     infer_schema_length: int | None = N_INFER_DEFAULT,
     raise_if_empty: bool = True,
+    drop_empty_rows: bool = True,
 ) -> pl.DataFrame | dict[str, pl.DataFrame]:
     """
     Read Excel spreadsheet data into a DataFrame.
@@ -231,6 +238,9 @@ def read_excel(
     raise_if_empty
         When there is no data in the sheet,`NoDataError` is raised. If this parameter
         is set to False, an empty DataFrame (with no columns) is returned instead.
+    drop_empty_rows
+        A boolean flag whether to drop empty rows or not from the dataframe. Default
+        is True.
 
     Returns
     -------
@@ -298,6 +308,7 @@ def read_excel(
         raise_if_empty=raise_if_empty,
         has_header=has_header,
         columns=columns,
+        drop_empty_rows=drop_empty_rows,
     )
 
 
@@ -529,6 +540,7 @@ def _read_spreadsheet(
     columns: Sequence[int] | Sequence[str] | None = None,
     has_header: bool = True,
     raise_if_empty: bool = True,
+    drop_empty_rows: bool = True,
 ) -> pl.DataFrame | dict[str, pl.DataFrame]:
     if isinstance(source, (str, Path)):
         source = normalize_filepath(source)
@@ -560,6 +572,7 @@ def _read_spreadsheet(
                 read_options=read_options,
                 raise_if_empty=raise_if_empty,
                 columns=columns,
+                drop_empty_rows=drop_empty_rows,
             )
             for name in sheet_names
         }
@@ -748,6 +761,7 @@ def _csv_buffer_to_frame(
     read_options: dict[str, Any],
     schema_overrides: SchemaDict | None,
     raise_if_empty: bool,
+    drop_empty_rows: bool,
 ) -> pl.DataFrame:
     """Translate StringIO buffer containing delimited data as a DataFrame."""
     # handle (completely) empty sheet data
@@ -781,11 +795,19 @@ def _csv_buffer_to_frame(
         separator=separator,
         **read_options,
     )
-    return _drop_null_data(df, raise_if_empty=raise_if_empty)
+    return _drop_null_data(
+        df, raise_if_empty=raise_if_empty, drop_empty_rows=drop_empty_rows
+    )
 
 
-def _drop_null_data(df: pl.DataFrame, *, raise_if_empty: bool) -> pl.DataFrame:
-    """If DataFrame contains columns/rows that contain only nulls, drop them."""
+def _drop_null_data(
+    df: pl.DataFrame, *, raise_if_empty: bool, drop_empty_rows: bool = True
+) -> pl.DataFrame:
+    """
+    If DataFrame contains columns/rows that contain only nulls, drop them.
+
+    If `drop_empty_rows` is set to `False`, empty rows are not dropped.
+    """
     null_cols = []
     for col_name in df.columns:
         # note that if multiple unnamed columns are found then all but the first one
@@ -806,8 +828,9 @@ def _drop_null_data(df: pl.DataFrame, *, raise_if_empty: bool) -> pl.DataFrame:
 
     if len(df) == 0 and len(df.columns) == 0:
         return _empty_frame(raise_if_empty)
-
-    return df.filter(~F.all_horizontal(F.all().is_null()))
+    if drop_empty_rows:
+        return df.filter(~F.all_horizontal(F.all().is_null()))
+    return df
 
 
 def _empty_frame(raise_if_empty: bool) -> pl.DataFrame:  # noqa: FBT001
@@ -839,6 +862,7 @@ def _read_spreadsheet_openpyxl(
     schema_overrides: SchemaDict | None,
     columns: Sequence[int] | Sequence[str] | None,
     raise_if_empty: bool,
+    drop_empty_rows: bool,
 ) -> pl.DataFrame:
     """Use the 'openpyxl' library to read data from the given worksheet."""
     infer_schema_length = read_options.pop("infer_schema_length", None)
@@ -895,7 +919,9 @@ def _read_spreadsheet_openpyxl(
         strict=False,
     )
 
-    df = _drop_null_data(df, raise_if_empty=raise_if_empty)
+    df = _drop_null_data(
+        df, raise_if_empty=raise_if_empty, drop_empty_rows=drop_empty_rows
+    )
     df = _reorder_columns(df, columns)
     return df
 
@@ -908,6 +934,7 @@ def _read_spreadsheet_calamine(
     schema_overrides: SchemaDict | None,
     columns: Sequence[int] | Sequence[str] | None,
     raise_if_empty: bool,
+    drop_empty_rows: bool,
 ) -> pl.DataFrame:
     # if we have 'schema_overrides' and a more recent version of `fastexcel`
     # we can pass translated dtypes to the engine to refine the initial parse
@@ -965,7 +992,9 @@ def _read_spreadsheet_calamine(
     if schema_overrides:
         df = df.cast(dtypes=schema_overrides)
 
-    df = _drop_null_data(df, raise_if_empty=raise_if_empty)
+    df = _drop_null_data(
+        df, raise_if_empty=raise_if_empty, drop_empty_rows=drop_empty_rows
+    )
 
     # standardise on string dtype for null columns in empty frame
     if df.is_empty():
@@ -1008,6 +1037,7 @@ def _read_spreadsheet_xlsx2csv(
     schema_overrides: SchemaDict | None,
     columns: Sequence[int] | Sequence[str] | None,
     raise_if_empty: bool,
+    drop_empty_rows: bool,
 ) -> pl.DataFrame:
     """Use the 'xlsx2csv' library to read data from the given worksheet."""
     csv_buffer = StringIO()
@@ -1030,6 +1060,7 @@ def _read_spreadsheet_xlsx2csv(
         read_options=read_options,
         schema_overrides=schema_overrides,
         raise_if_empty=raise_if_empty,
+        drop_empty_rows=drop_empty_rows,
     )
     if cast_to_boolean:
         df = df.with_columns(*cast_to_boolean)

py-polars/tests/unit/io/test_spreadsheet.py

@@ -19,7 +19,7 @@
 if TYPE_CHECKING:
     from polars._typing import ExcelSpreadsheetEngine, SelectorType
 
-pytestmark = pytest.mark.slow()
+# pytestmark = pytest.mark.slow()
 
 
 @pytest.fixture()
@@ -81,6 +81,11 @@ def path_ods_mixed(io_files_path: Path) -> Path:
     return io_files_path / "mixed.ods"
 
 
+@pytest.fixture()
+def path_empty_rows_excel(io_files_path: Path) -> Path:
+    return io_files_path / "test_empty_rows.xlsx"
+
+
 @pytest.mark.parametrize(
     ("read_spreadsheet", "source", "engine_params"),
     [
@@ -1058,3 +1063,38 @@ def test_identify_workbook(
         bytesio_data = BytesIO(f.read())
         assert _identify_workbook(bytesio_data) == file_type
         assert isinstance(pl.read_excel(bytesio_data, engine="calamine"), pl.DataFrame)
+
+
+def test_drop_empty_rows(path_empty_rows_excel: Path) -> None:
+    df1 = pl.read_excel(source=path_empty_rows_excel, engine="xlsx2csv")
+    assert df1.shape == (8, 4)
+    df2 = pl.read_excel(
+        source=path_empty_rows_excel, engine="xlsx2csv", drop_empty_rows=True
+    )
+    assert df2.shape == (8, 4)
+    df3 = pl.read_excel(
+        source=path_empty_rows_excel, engine="xlsx2csv", drop_empty_rows=False
+    )
+    assert df3.shape == (10, 4)
+
+    df4 = pl.read_excel(source=path_empty_rows_excel, engine="openpyxl")
+    assert df4.shape == (8, 4)
+    df5 = pl.read_excel(
+        source=path_empty_rows_excel, engine="openpyxl", drop_empty_rows=True
+    )
+    assert df5.shape == (8, 4)
+    df6 = pl.read_excel(
+        source=path_empty_rows_excel, engine="openpyxl", drop_empty_rows=False
+    )
+    assert df6.shape == (10, 4)
+
+    df7 = pl.read_excel(source=path_empty_rows_excel, engine="calamine")
+    assert df7.shape == (8, 4)
+    df8 = pl.read_excel(
+        source=path_empty_rows_excel, engine="calamine", drop_empty_rows=True
+    )
+    assert df8.shape == (8, 4)
+    df9 = pl.read_excel(
+        source=path_empty_rows_excel, engine="calamine", drop_empty_rows=False
+    )
+    assert df9.shape == (10, 4)