ENH: Optimize nrows in read_excel

asv_bench/benchmarks/io/excel.py

@@ -11,7 +11,7 @@
 
 
 def _generate_dataframe():
-    N = 2000
+    N = 20000
     C = 5
     df = DataFrame(
         np.random.randn(N, C),
@@ -69,5 +69,9 @@ def time_read_excel(self, engine):
         fname = self.fname_odf if engine == "odf" else self.fname_excel
         read_excel(fname, engine=engine)
 
+    def time_read_excel_nrows(self, engine):
+        fname = self.fname_odf if engine == "odf" else self.fname_excel
+        read_excel(fname, engine=engine, nrows=1)
+
 
 from ..pandas_vb_common import setup  # noqa: F401 isort:skip

doc/source/whatsnew/v1.1.0.rst

@@ -775,6 +775,7 @@ Performance improvements
 - Performance improvement in :class:`pandas.core.groupby.RollingGroupby` (:issue:`34052`)
 - Performance improvement in arithmetic operations (sub, add, mul, div) for MultiIndex (:issue:`34297`)
 - Performance improvement in `DataFrame[bool_indexer]` when `bool_indexer` is a list (:issue:`33924`)
+- Performance improvement in `read_excel` for integer ``header``, ``skiprows``, and ``nrows`` (:issue:`33281`).
 
 .. ---------------------------------------------------------------------------
 

pandas/io/excel/_base.py

@@ -3,10 +3,12 @@
 from io import BytesIO
 import os
 from textwrap import fill
+from typing import List, Optional, Sequence
 
 from pandas._config import config
 
 from pandas._libs.parsers import STR_NA_VALUES
+from pandas._typing import Scalar, Union
 from pandas.errors import EmptyDataError
 from pandas.util._decorators import Appender, deprecate_nonkeyword_arguments
 
@@ -383,9 +385,46 @@ def get_sheet_by_index(self, index):
         pass
 
     @abc.abstractmethod
-    def get_sheet_data(self, sheet, convert_float):
+    def get_sheet_data(
+        self,
+        sheet,
+        convert_float: bool,
+        header: Optional[Union[int, Sequence[int]]],
+        skiprows: Optional[Union[int, Sequence[int]]],
+        nrows: Optional[int],
+    ) -> List[List[Scalar]]:
         pass
 
+    def should_skip_row(
+        self,
+        index: int,
+        header: Optional[Union[int, Sequence[int]]],
+        skiprows: Optional[Union[int, Sequence[int]]],
+        nrows: Optional[int],
+    ) -> bool:
+        """
+        Determines whether row should be read.
+
+        Parameters
+        ----------
+        index : int
+            Index of row.
+        header : int, list of int
+            Rows used as column labels.
+        skiprows : int, list of int
+            Rows to skip at the begining.
+        nrows : int
+            Number of rows to parse.
+
+        Returns
+        -------
+        Bool determining if row should be skipped.
+        """
+        if nrows is not None and isinstance(header, int) and isinstance(skiprows, int):
+            if index < header + skiprows - 1:
+                return True
+        return False
+
     def parse(
         self,
         sheet_name=0,
@@ -439,7 +478,16 @@ def parse(
             else:  # assume an integer if not a string
                 sheet = self.get_sheet_by_index(asheetname)
 
-            data = self.get_sheet_data(sheet, convert_float)
+            gsd_header = 0 if header is None else header
+            gsd_skiprows = 0 if skiprows is None else skiprows
+            gsd_nrows = nrows if isinstance(nrows, int) else None
+
+            if isinstance(gsd_header, list) or isinstance(gsd_skiprows, list):
+                gsd_nrows = None
+
+            data = self.get_sheet_data(
+                sheet, convert_float, gsd_header, gsd_skiprows, gsd_nrows
+            )
             usecols = _maybe_convert_usecols(usecols)
 
             if not data:

pandas/io/excel/_odfreader.py

@@ -1,6 +1,6 @@
-from typing import List
+from typing import List, Optional, Sequence
 
-from pandas._typing import FilePathOrBuffer, Scalar
+from pandas._typing import FilePathOrBuffer, Scalar, Union
 from pandas.compat._optional import import_optional_dependency
 
 import pandas as pd
@@ -63,7 +63,14 @@ def get_sheet_by_name(self, name: str):
 
         raise ValueError(f"sheet {name} not found")
 
-    def get_sheet_data(self, sheet, convert_float: bool) -> List[List[Scalar]]:
+    def get_sheet_data(
+        self,
+        sheet,
+        convert_float: bool,
+        header: Optional[Union[int, Sequence[int]]],
+        skiprows: Optional[Union[int, Sequence[int]]],
+        nrows: Optional[int],
+    ) -> List[List[Scalar]]:
         """
         Parse an ODF Table into a list of lists
         """
@@ -79,7 +86,15 @@ def get_sheet_data(self, sheet, convert_float: bool) -> List[List[Scalar]]:
 
         table: List[List[Scalar]] = []
 
+        if nrows is not None and isinstance(header, int) and isinstance(skiprows, int):
+            sheet_rows = sheet_rows[0 : header + skiprows + nrows + 1]
+
         for i, sheet_row in enumerate(sheet_rows):
+
+            if self.should_skip_row(i, header, skiprows, nrows):
+                table.append([])
+                continue
+
             sheet_cells = [x for x in sheet_row.childNodes if x.qname in cell_names]
             empty_cells = 0
             table_row: List[Scalar] = []

pandas/io/excel/_openpyxl.py

@@ -1,8 +1,8 @@
-from typing import List
+from typing import List, Optional, Sequence
 
 import numpy as np
 
-from pandas._typing import FilePathOrBuffer, Scalar
+from pandas._typing import FilePathOrBuffer, Scalar, Union
 from pandas.compat._optional import import_optional_dependency
 
 from pandas.io.excel._base import ExcelWriter, _BaseExcelReader
@@ -529,9 +529,18 @@ def _convert_cell(self, cell, convert_float: bool) -> Scalar:
 
         return cell.value
 
-    def get_sheet_data(self, sheet, convert_float: bool) -> List[List[Scalar]]:
+    def get_sheet_data(
+        self,
+        sheet,
+        convert_float: bool,
+        header: Optional[Union[int, Sequence[int]]],
+        skiprows: Optional[Union[int, Sequence[int]]],
+        nrows: Optional[int],
+    ) -> List[List[Scalar]]:
         data: List[List[Scalar]] = []
+
         for row in sheet.rows:
+
             data.append([self._convert_cell(cell, convert_float) for cell in row])
 
         return data

pandas/io/excel/_pyxlsb.py

@@ -1,6 +1,6 @@
-from typing import List
+from typing import List, Optional, Sequence
 
-from pandas._typing import FilePathOrBuffer, Scalar
+from pandas._typing import FilePathOrBuffer, Scalar, Union
 from pandas.compat._optional import import_optional_dependency
 
 from pandas.io.excel._base import _BaseExcelReader
@@ -62,7 +62,14 @@ def _convert_cell(self, cell, convert_float: bool) -> Scalar:
 
         return cell.v
 
-    def get_sheet_data(self, sheet, convert_float: bool) -> List[List[Scalar]]:
+    def get_sheet_data(
+        self,
+        sheet,
+        convert_float: bool,
+        header: Optional[Union[int, Sequence[int]]],
+        skiprows: Optional[Union[int, Sequence[int]]],
+        nrows: Optional[int],
+    ) -> List[List[Scalar]]:
         return [
             [self._convert_cell(c, convert_float) for c in r]
             for r in sheet.rows(sparse=False)

pandas/io/excel/_xlrd.py

@@ -1,7 +1,9 @@
 from datetime import time
+from typing import List, Optional, Sequence
 
 import numpy as np
 
+from pandas._typing import Scalar, Union
 from pandas.compat._optional import import_optional_dependency
 
 from pandas.io.excel._base import _BaseExcelReader
@@ -46,7 +48,14 @@ def get_sheet_by_name(self, name):
     def get_sheet_by_index(self, index):
         return self.book.sheet_by_index(index)
 
-    def get_sheet_data(self, sheet, convert_float):
+    def get_sheet_data(
+        self,
+        sheet,
+        convert_float: bool,
+        header: Optional[Union[int, Sequence[int]]],
+        skiprows: Optional[Union[int, Sequence[int]]],
+        nrows: Optional[int],
+    ) -> List[List[Scalar]]:
         from xlrd import (
             xldate,
             XL_CELL_DATE,
@@ -95,9 +104,18 @@ def _parse_cell(cell_contents, cell_typ):
                     cell_contents = val
             return cell_contents
 
-        data = []
+        data: List[List[Scalar]] = []
+
+        sheet_nrows = sheet.nrows
+        if nrows is not None and isinstance(header, int) and isinstance(skiprows, int):
+            sheet_nrows = min(header + skiprows + nrows + 1, sheet_nrows)
+
+        for i in range(sheet_nrows):
+
+            if self.should_skip_row(i, header, skiprows, nrows):
+                data.append([])
+                continue
 
-        for i in range(sheet.nrows):
             row = [
                 _parse_cell(value, typ)
                 for value, typ in zip(sheet.row_values(i), sheet.row_types(i))

pandas/tests/io/excel/test_readers.py

@@ -1143,3 +1143,18 @@ def test_header_with_index_col(self, engine, filename):
             filename, sheet_name="Sheet1", index_col=0, header=[0, 1]
         )
         tm.assert_frame_equal(expected, result)
+
+    @pytest.mark.parametrize("header, skiprows", [(1, 2), (0, 3)])
+    @td.check_file_leaks
+    def test_header_skiprows_nrows(self, engine, read_ext, header, skiprows):
+        # GH 32727
+        data = pd.read_excel("test1" + read_ext, engine=engine)
+        expected = (
+            DataFrame(data.iloc[3:6])
+            .reset_index(drop=True)
+            .rename(columns=data.iloc[2].rename(None))
+        )
+        actual = pd.read_excel(
+            "test1" + read_ext, engine=engine, header=header, skiprows=skiprows, nrows=3
+        )
+        tm.assert_frame_equal(expected, actual)