Python - Python 操作excel xlsxwriter xlrd

Python - Python 操作excel xlsxwriter xlrd

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1、下载模块

xlrd
xlwt
xlsxwriter

2、编写代码

import xlrd as rd
import xlsxwriter
import uuid

if __name__ == '__main__':
    file = 'C:/Users/A-PC/Desktop/123/123.xlsx'
    # 读取
    work_book = rd.open_workbook(file)
    print('表格总表数', len(work_book.sheet_names()))
    print('分别是', end=' ')
    for name in work_book.sheet_names():
        print(name, end=',')
    print('\b')
    sheet1 = work_book.sheet_by_name('Sheet10')
    print('表格总行数', sheet1.nrows)
    print('表格总列数', sheet1.ncols)
    for r in range(sheet1.nrows):
        for c in range(sheet1.ncols):
            value = sheet1.cell_value(r, c)
            if c + 1 != sheet1.ncols:
                print(value, end=' ' * (16 - len(str(value))))
            else:
                print(value)

    # 写入
    work_book = xlsxwriter.Workbook(file)
    work_sheet = work_book.add_worksheet('Sheet10')
    for i in range(10):
        for j in range(10):
            work_sheet.write(i, j, str(uuid.uuid4())[24:])
    work_book.close()

3、输出

表格总表数 1
分别是 Sheet10
表格总行数 10
表格总列数 10
a1d0b4664a03    d328e5585036    fe69035d8c37    837b71bee7d7    177f6171da8d    48dfd179bff7    99a94f35c24b    056b437796e8    9a69c0c11d0b    c017b22866b7
35c40c98acc0    26d5ca180995    d8e470780330    3fc2f0b7b998    03c1150d0809    a33ea34bc8bb    53769bef5cd8    f34e79299fcf    ddc22277f808    9f35312ae1f4
9ccc9b06f10d    ca06304228cd    d6ed680572b0    77998905f32f    94539c95fbc5    96af039877a6    a7222a4c4aba    41c4320e701f    81869dd2fe24    e66066aa2d53
458ad42939c4    e15eed1fe66f    bd8ce20c7614    cbb42edafc75    e7affb6dd529    fc5bbe6dad43    d2febfc5399c    8beb3c9ef61e    0e3f8cbdf10f    9c7fdf3c0ba4
d640022702e3    b3ffa1cda035    53c4100d7694    bcdea5527ea0    fe02aeee619b    1b95d8bd9818    18f896e04819    7a486a0b3130    843862afb634    3ef2281e9c39
45df518b8d9c    e71c6efefc66    db22feac4446    47124b5f5b49    31c53363bb69    3fa0cdd1b71e    1aa65af1bb85    4ce8da2f5b28    2da6c635fe6d    97192d84f886
bb81ac352b1a    48caac64e869    33f9f239681b    62358b0a3d89    6db810e1cf88    0d189c548641    662002f071ab    1d57ea2a0fdf    e301dce98355    34eff5464e6e
3bd6ff21bf00    45b67b04223a    e233b1ab1394    32157577b3ef    1e25169cdc38    512aedc706d3    922174afb099    54a7dcbc3984    3263faa31c3d    288ec03035ef
ffbc47ed8cac    e497faa969fc    7ba2c8479597    23656e44d616    87fe5a62d72a    30b645549c81    9f63d1a5945a    70381180820b    cd2ceb79b71d    5b01858fde34
7595383a0355    44fcc30302bc    06f60d6d4f88    e7be4f70de2e    30cc65222245    25490c5f321f    573f05a6f303    642626827376    7acdd35299e7    073fa536df29