今天给大家分享一篇用openpyxl操作Excel的文章。
各种数据需要导入Excel？多个Excel要合并？目前，Python处理Excel文件有很多库，openpyxl算是其中功能和性能做的比较好的一个。接下来我将为大家介绍各种Excel操作。
1、打开Excel文件
新建一个Excel文件
>>> from openpyxl import Workbook
>>> wb = Workbook()打开现有Excel文件
>>> from openpyxl import load_workbook
>>> wb2 = load_workbook('test.xlsx')打开大文件时，根据需求使用只读或只写模式减少内存消耗。
wb = load_workbook(filename='large_file.xlsx', read_only=True)
wb = Workbook(write_only=True)2、获取、创建工作表
获取当前活动工作表：
>>> ws = wb.active创建新的工作表：
>>> ws1 = wb.create_sheet("Mysheet") # insert at the end (default)
# or
>>> ws2 = wb.create_sheet("Mysheet", 0) # insert at first position
# or
>>> ws3 = wb.create_sheet("Mysheet", -1) # insert at the penultimate position使用工作表名字获取工作表：
>>> ws3 = wb["New Title"]获取所有的工作表名称：
>>> print(wb.sheetnames)
['Sheet2', 'New Title', 'Sheet1']
使用for循环遍历所有的工作表：
>>> for sheet in wb:
... print(sheet.title)3、保存
保存到流中在网络中使用：
>>> from tempfile import NamedTemporaryFile
>>> from openpyxl import Workbook
>>> wb = Workbook()
>>> with NamedTemporaryFile() as tmp:
wb.save(tmp.name)
tmp.seek(0)
stream = tmp.read()
保存到文件：
>>> wb = Workbook()
>>> wb.save('balances.xlsx')
保存为模板：
>>> wb = load_workbook('document.xlsx')
>>> wb.template = True
>>> wb.save('document_template.xltx')4、单元格
单元格位置作为工作表的键直接读取：
>>> c = ws['A4']为单元格赋值：
>>> ws['A4'] = 4
>>> c.value = 'hello, world'多个单元格 可以使用切片访问单元格区域：
>>> cell_range = ws['A1':'C2']使用数值格式：
>>> # set date using a Python datetime
>>> ws['A1'] = datetime.datetime(2010, 7, 21)
>>>
>>> ws['A1'].number_format
'yyyy-mm-dd h:mm:ss'使用公式：
>>> # add a simple formula
>>> ws["A1"] = "=SUM(1, 1)"合并单元格时，除左上角单元格外，所有单元格都将从工作表中删除：
>>> ws.merge_cells('A2:D2')
>>> ws.unmerge_cells('A2:D2')
>>>
>>> # or equivalently
>>> ws.merge_cells(start_row=2, start_column=1, end_row=4, end_column=4)
>>> ws.unmerge_cells(start_row=2, start_column=1, end_row=4, end_column=4)5、行、列
可以单独指定行、列、或者行列的范围：
>>> colC = ws['C']
>>> col_range = ws['C:D']
>>> row10 = ws[10]
>>> row_range = ws[5:10]可以使用Worksheet.iter_rows()方法遍历行：
>>> for row in ws.iter_rows(min_row=1, max_col=3, max_row=2):
... for cell in row:
... print(cell)
<Cell Sheet1.A1>
<Cell Sheet1.B1>
<Cell Sheet1.C1>
<Cell Sheet1.A2>
<Cell Sheet1.B2>
<Cell Sheet1.C2>同样的Worksheet.iter_cols()方法将遍历列：
>>> for col in ws.iter_cols(min_row=1, max_col=3, max_row=2):
... for cell in col:
... print(cell)
<Cell Sheet1.A1>
<Cell Sheet1.A2>
<Cell Sheet1.B1>
<Cell Sheet1.B2>
<Cell Sheet1.C1>
<Cell Sheet1.C2>遍历文件的所有行或列，可以使用Worksheet.rows属性：
>>> ws = wb.active
>>> ws['C9'] = 'hello world'
>>> tuple(ws.rows)
((<Cell Sheet.A1>, <Cell Sheet.B1>, <Cell Sheet.C1>),
(<Cell Sheet.A2>, <Cell Sheet.B2>, <Cell Sheet.C2>),
(<Cell Sheet.A3>, <Cell Sheet.B3>, <Cell Sheet.C3>),
(<Cell Sheet.A4>, <Cell Sheet.B4>, <Cell Sheet.C4>),
(<Cell Sheet.A5>, <Cell Sheet.B5>, <Cell Sheet.C5>),
(<Cell Sheet.A6>, <Cell Sheet.B6>, <Cell Sheet.C6>),
(<Cell Sheet.A7>, <Cell Sheet.B7>, <Cell Sheet.C7>),
(<Cell Sheet.A8>, <Cell Sheet.B8>, <Cell Sheet.C8>),
(<Cell Sheet.A9>, <Cell Sheet.B9>, <Cell Sheet.C9>))或Worksheet.columns属性：
>>> tuple(ws.columns)
((<Cell Sheet.A1>,
<Cell Sheet.A2>,
<Cell Sheet.A3>,
<Cell Sheet.A4>,
<Cell Sheet.A5>,
<Cell Sheet.A6>,
...
<Cell Sheet.B7>,
<Cell Sheet.B8>,
<Cell Sheet.B9>),
(<Cell Sheet.C1>,
<Cell Sheet.C2>,
<Cell Sheet.C3>,
<Cell Sheet.C4>,
<Cell Sheet.C5>,
<Cell Sheet.C6>,
<Cell Sheet.C7>,
<Cell Sheet.C8>,
<Cell Sheet.C9>))使用Worksheet.append()或者迭代使用Worksheet.cell()新增一行数据：
>>> for row in range(1, 40):
... ws1.append(range(600))
>>> for row in range(10, 20):
... for col in range(27, 54):
... _ = ws3.cell(column=col, row=row, value="{0}".format(get_column_letter(col)))插入操作比较麻烦。可以使用Worksheet.insert_rows()插入一行或几行：
>>> from openpyxl.utils import get_column_letter
>>> ws.insert_rows(7)
>>> row7 = ws[7]
>>> for col in range(27, 54):
... _ = ws3.cell(column=col, row=7, value="{0}".format(get_column_letter(col)))
Worksheet.insert_cols()操作类似。Worksheet.delete_rows()和Worksheet.delete_cols()用来批量删除行和列。6、只读取值
使用Worksheet.values属性遍历工作表中的所有行，但只返回单元格值：
for row in ws.values:
for value in row:
print(value)Worksheet.iter_rows()和Worksheet.iter_cols()可以设置values_only参数来仅返回单元格的值：
>>> for row in ws.iter_rows(min_row=1, max_col=3, max_row=2, values_only=True):
... print(row)
(None, None, None)
(None, None, None)
