Python-OpenPyXl精讲

翻译自官方文档

开始在内存中使用

创建一个workbook

在刚开始使用openpyxl的时候,不需要直接在文件系统中创建一个文件,仅仅需要导入Workbook类并开始使用它:

>>> from openpyxl import Workbook
>>> wb = Workbook()

一个workbook总是会创建至少一个worksheet(工作表),可以通过openpyxl.workbook.Workbook.active()这个属性去获取:

>>> ws = wb.active

这个函数使用_active_sheet_index这个属性,默认设置的值是0,除非你指定一个值,否则总是获取到第一个worksheet。

你可以使用openpyxl.workbook.Workbook.create_sheet()来创建一个新的worksheet:

>>> ws1 = wb.create_sheet("Mysheet") # insert at the end (default)# or
>>> ws2 = wb.create_sheet("Mysheet", 0) # insert at first position

当创建脚标的时候会自动创建一个名字,按照(Sheet, Sheet1, Sheet2, …)这个列表名创建,你可以使用tiitle属性来修改这个名字:

>>> ws.title = "New Title"

一旦给了一个worksheet名字,就可以通过一个key去获取这个worksheet:

>>> ws3 = wb["New Title"]

你可以使用openpyxl.workbook.Workbook.sheetnames()这个属性获取所有的脚标的名字:

>>> print(wb.sheetnames)['Sheet2', 'New Title', 'Sheet1']

可以迭代所有的脚标:

>>> for sheet in wb:
...     print(sheet.title)

可以使用openpyxl.workbook.Workbook.copy_worksheet()这个属性复制一个worksheet:

>>> source = wb.active
>>> target = wb.copy_worksheet(source)

注意:只有cells 和 styles能够被复制,不能在workbooks之间复制worksheets,你可以在一个workbook中复制worksheets

玩数据

获取一个cell

现在我们已经知道怎么访问一个worksheet,我们可以开始修改cell的内容了。(一个cell就是一个单元格)
cell可以直接通过key来获取:

>>> c = ws['A4']

这将会返回一个cell或创建一个不存在的cell。cell 的值可以直接被赋值:

>>> ws['A4'] = 4

也可以使用另外一个方法openpyxl.worksheet.Worksheet.cell():

>>> d = ws.cell(row=4, column=2, value=10)

Note:当在内存当中创建一个worksheet的时候,它没有包含任何cell,当它们第一次被访问的时候被创建

Warning:因为excel表的滚动特性,滚动出来的cell也会被创建出来,即使没有访问那些cell,例如:

>>> for i in range(1,101):
...        for j in range(1,101):
...            ws.cell(row=i, column=j)

这将会创建100*100个空的cell

访问多个cell

使用切片可以访问多个cell

>>> cell_range = ws['A1':'C2']

行和列能够被轻松的获取到:

>>> colC = ws['C']
>>> col_range = ws['C:D']
>>> row10 = ws[10]
>>> row_range = ws[5:10]

也可以使用openpyxl.worksheet.Worksheet.iter_rows()这个方法:

>>> 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>

相似的方法openpyxl.worksheet.Worksheet.iter_cols()也可以:

>>> 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>

如果你想迭代一个文件的所有行或列,可以使用openpyxl.worksheet.Worksheet.rows()这个属性:

>>> 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>))

或者openpyxl.worksheet.Worksheet.columns()这个属性:

>>> 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>))

数据存储

一旦我们有了一个openpyxl.cell.Cell,我们就可以给它赋值:

>>> c.value = 'hello, world'
>>> print(c.value)'hello, world'
>>> d.value = 3.14
>>> print(d.value)3.14

也能使用类型和格式推断:

>>> wb = Workbook(guess_types=True)
>>> c.value = '12%'
>>> print(c.value)
0.12
>>> import datetime
>>> d.value = datetime.datetime.now()
>>> print d.valuedatetime.datetime(2010, 9, 10, 22, 25, 18)
>>> c.value = '31.50'
>>> print(c.value)
31.5
保存到文件

最简单和快速的保存一个workbook方法是使用openpyxl.workbook.Workbook模块的openpyxl.workbook.Workbook.save()这个方法:

>>> wb = Workbook()
>>> wb.save('balances.xlsx')

Warning:这个方法将会在没有警告提示下覆盖已经有的内容
可以使用template=True将一个workbook保存成一个模版:

>>> wb = load_workbook('document.xlsx')
>>> wb.template = True
>>> wb.save('document_template.xltx')

或者设置这个属性为false(默认)来保存为一个文件:

>>> wb = load_workbook('document_template.xltx')
>>> wb.template = False
>>> wb.save('document.xlsx', as_template=False)

*Warning:当保存文档的时候在模版文档中你应该注意文档的扩展名(后缀名)和数据描述,否则可能会导致文档不能被再次打开,如下错误式例:

>>> wb = load_workbook('document.xlsx')
>>> # 应该保存成扩展名为*.xlsx
>>> wb.save('new_document.xlsm')
>>> # Excel软件不能再次打开此文件
>>>
>>> # 或者
>>>
>>> # 应该指定属性keep_vba=True
>>> wb = load_workbook('document.xlsm')
>>> wb.save('new_document.xlsm')
>>> #  Excel软件不能再次打开此文件
>>>
>>> # 或者
>>>
>>> wb = load_workbook('document.xltm', keep_vba=True)
>>> # 如果我们需要一个模版文件,就必须指定扩展名为 *.xltm.
>>> wb.save('new_document.xlsm')
>>> #  Excel软件不能再次打开此文件

加载一个文件

类似于写文件,可以导入openpyxl.load_workbook()来打开一个已经存在的workbook:

>>> from openpyxl import load_workbook
>>> wb2 = load_workbook('test.xlsx')
>>> print wb2.get_sheet_names()
['Sheet2', 'New Title', 'Sheet1']

基本教程已经完了。接下来是一些使用例子:


写一个workbook

>>> from openpyxl import Workbook
>>> from openpyxl.compat import range
>>> from openpyxl.utils import get_column_letter
>>>
>>> wb = Workbook()
>>>
>>> dest_filename = 'empty_book.xlsx'
>>>
>>> ws1 = wb.active
>>> ws1.title = "range names"
>>>
>>> for row in range(1, 40):
...     ws1.append(range(600))
>>>
>>> ws2 = wb.create_sheet(title="Pi")
>>>
>>> ws2['F5'] = 3.14
>>>
>>> ws3 = wb.create_sheet(title="Data")
>>> 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)))
>>> print(ws3['AA10'].value)
AA
>>> wb.save(filename = dest_filename)

读取一个已经存在的文件

>>> from openpyxl import load_workbook
>>> wb = load_workbook(filename = 'empty_book.xlsx')
>>> sheet_ranges = wb['range names']
>>> print(sheet_ranges['D18'].value)

警告:openpyxl不能读取Excle中所有的对象,当打开和保存相同名字的文件的时候,图片和图表将会丢失

使用数字格式:

>>> import datetime
>>> from openpyxl import Workbook
>>> wb = Workbook()
>>> ws = wb.active
>>> # set date using a Python datetime
>>> ws['A1'] = datetime.datetime(2010, 7, 21)
>>>
>>> ws['A1'].number_format
'yyyy-mm-dd h:mm:ss'
>>> # You can enable type inference on a case-by-case basis
>>> wb.guess_types = True
>>> # set percentage using a string followed by the percent sign
>>> ws['B1'] = '3.14%'
>>> wb.guess_types = False
>>> ws['B1'].value
0.031400000000000004
>>>
>>> ws['B1'].number_format
'0%'

使用公式:

>>> from openpyxl import Workbook
>>> wb = Workbook()
>>> ws = wb.active
>>> # add a simple formula
>>> ws["A1"] = "=SUM(1, 1)"
>>> wb.save("formula.xlsx")

警告:公式必须使用英文名,并且公式的参数必须使用逗号分隔,不能使用其他的符号如分号

openpyxl从不评估公式,但是可以检查公式的名字:

>>> from openpyxl.utils import FORMULAE
>>> "HEX2DEC" in FORMULAE
True

如果你想使用一个不知道的公式,这可能是因为你使用的公式,没有包括在初始规范。 这样的公式必须以xlfn作为前缀。

合并/取消合并单元格:

>>> from openpyxl.workbook import Workbook
>>>
>>> wb = Workbook()
>>> ws = wb.active
>>>
>>> ws.merge_cells('A1:B1')
>>> ws.unmerge_cells('A1:B1')
>>>
>>> # or
>>> ws.merge_cells(start_row=2,start_column=1,end_row=2,end_column=4)
>>> ws.unmerge_cells(start_row=2,start_column=1,end_row=2,end_column=4)

插入图片:

>>> from openpyxl import Workbook
>>> from openpyxl.drawing.image import Image
>>>
>>> wb = Workbook()
>>> ws = wb.active
>>> ws['A1'] = 'You should see three logos below'
>>> # create an image
>>> img = Image('logo.png')
>>> # add to worksheet and anchor next to cells
>>> ws.add_image(img, 'A1')
>>> wb.save('logo.xlsx')

折叠列:

>>> import openpyxl
>>> wb = openpyxl.Workbook()
>>> ws = wb.create_sheet()
>>> ws.column_dimensions.group('A','D', hidden=True)
>>> wb.save('group.xlsx')

使用Pandas 和 NumPy

openpyxl可以配合使用PandasNumPy这两个很受欢迎的库

NumPy Support
openpyxl已内置支持NumPy类型float,integer和boolean。 DateTimes支持使用Pandas的时间戳类型。

openpyxl.utils.dataframe.dataframe_to_rows()方法提供简单的方式使用Pandas 的Dataframes:

from openpyxl import Workbook
from openpyxl.utils.dataframe import dataframe_to_rows
wb = Workbook()
ws = wb.active

for r in dataframe_to_rows(df, index=True, header=True):
    ws.append(r)

要将数据框转换为突出显示的标题和索引:

wb = Workbook()
ws = wb.active

for r in dataframe_to_rows(df, index=True, header=True):
    ws.append(r)

for cell in ws['A'] + ws[1]:
    cell.style = 'Pandas'

wb.save("pandas_openpyxl.xlsx")

如果你只是想转换数据,可以使用只写模式:

from openpyxl.cell.cell import WriteOnlyCell
wb = Workbook(write_only=True)
ws = wb.create_sheet()

cell = WriteOnlyCell(ws)
cell.style = 'Pandas'

 def format_first_row(row, cell):

    for c in row:
        cell.value = c
        yield cell

rows = dataframe_to_rows(df)
first_row = format_first_row(next(rows), cell)
ws.append(first_row)

for row in rows:
    row = list(row)
    cell.value = row[0]
    row[0] = cell
    ws.append(row)

wb.save("openpyxl_stream.xlsx")

将工作表转换为Dataframe

要将工作表转换为Dataframe,您可以使用values属性。 如果工作表没有标题或索引,这很容易:

df = DataFrame(ws.values)

如果工作表有标题或索引,例如Pandas创建的那个,那么需要做更多的工作:

data = ws.values
cols = next(data)[1:]
data = list(data)
idx = [r[0] for r in data]
data = (islice(r, 1, None) for r in data)
df = DataFrame(data, index=idx, columns=cols)

使用过滤和排序

要添加过滤器,请定义范围,然后添加列和排序条件:

from openpyxl import Workbook

wb = Workbook()
ws = wb.active

data = [
    ["Fruit", "Quantity"],
    ["Kiwi", 3],
    ["Grape", 15],
    ["Apple", 3],
    ["Peach", 3],
    ["Pomegranate", 3],
    ["Pear", 3],
    ["Tangerine", 3],
    ["Blueberry", 3],
    ["Mango", 3],
    ["Watermelon", 3],
    ["Blackberry", 3],
    ["Orange", 3],
    ["Raspberry", 3],
    ["Banana", 3]
]

for r in data:
    ws.append(r)

ws.auto_filter.ref = "A1:B15"
ws.auto_filter.add_filter_column(0, ["Kiwi", "Apple", "Mango"])
ws.auto_filter.add_sort_condition("B2:B15")

wb.save("filtered.xlsx")

这将添加相关的指令到文件,但不会实际过滤或排序。

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