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- from datetime import time
- import numpy as np
- from pandas.compat._optional import import_optional_dependency
- from pandas.io.excel._base import _BaseExcelReader
- class _XlrdReader(_BaseExcelReader):
- def __init__(self, filepath_or_buffer):
- """Reader using xlrd engine.
- Parameters
- ----------
- filepath_or_buffer : string, path object or Workbook
- Object to be parsed.
- """
- err_msg = "Install xlrd >= 1.0.0 for Excel support"
- import_optional_dependency("xlrd", extra=err_msg)
- super().__init__(filepath_or_buffer)
- @property
- def _workbook_class(self):
- from xlrd import Book
- return Book
- def load_workbook(self, filepath_or_buffer):
- from xlrd import open_workbook
- if hasattr(filepath_or_buffer, "read"):
- data = filepath_or_buffer.read()
- return open_workbook(file_contents=data)
- else:
- return open_workbook(filepath_or_buffer)
- @property
- def sheet_names(self):
- return self.book.sheet_names()
- def get_sheet_by_name(self, name):
- return self.book.sheet_by_name(name)
- def get_sheet_by_index(self, index):
- return self.book.sheet_by_index(index)
- def get_sheet_data(self, sheet, convert_float):
- from xlrd import (
- xldate,
- XL_CELL_DATE,
- XL_CELL_ERROR,
- XL_CELL_BOOLEAN,
- XL_CELL_NUMBER,
- )
- epoch1904 = self.book.datemode
- def _parse_cell(cell_contents, cell_typ):
- """converts the contents of the cell into a pandas
- appropriate object"""
- if cell_typ == XL_CELL_DATE:
- # Use the newer xlrd datetime handling.
- try:
- cell_contents = xldate.xldate_as_datetime(cell_contents, epoch1904)
- except OverflowError:
- return cell_contents
- # Excel doesn't distinguish between dates and time,
- # so we treat dates on the epoch as times only.
- # Also, Excel supports 1900 and 1904 epochs.
- year = (cell_contents.timetuple())[0:3]
- if (not epoch1904 and year == (1899, 12, 31)) or (
- epoch1904 and year == (1904, 1, 1)
- ):
- cell_contents = time(
- cell_contents.hour,
- cell_contents.minute,
- cell_contents.second,
- cell_contents.microsecond,
- )
- elif cell_typ == XL_CELL_ERROR:
- cell_contents = np.nan
- elif cell_typ == XL_CELL_BOOLEAN:
- cell_contents = bool(cell_contents)
- elif convert_float and cell_typ == XL_CELL_NUMBER:
- # GH5394 - Excel 'numbers' are always floats
- # it's a minimal perf hit and less surprising
- val = int(cell_contents)
- if val == cell_contents:
- cell_contents = val
- return cell_contents
- data = []
- for i in range(sheet.nrows):
- row = [
- _parse_cell(value, typ)
- for value, typ in zip(sheet.row_values(i), sheet.row_types(i))
- ]
- data.append(row)
- return data
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