数据框示例-先前清理过的pandas.read_excel的结果:
import pandas as pd import numpy as np raw_data = {'ref': ['409075', '405168', '035751', '039374', '331949', '331951', '307128'], 'description': ['Product 7 (12X)', 'Product 6 (8X)', 'Product 2', 'Product 1', 'Product 2', 'Product 3', 'Product 3'], 'maker': [np.nan, np.nan, 'Companyname1', 'Comp.2', 'Company3', 'Company name 4', 'Maker 5'], 'type': [np.nan, np.nan, 'Rev. 0', np.nan, np.nan, np.nan, 'Type 5'], 'qty': [6, 4, 4, 2, 12, 12, 12], 'val': [np.nan, np.nan, np.nan, np.nan, np.nan, np.nan, np.nan], 'serial': [np.nan, np.nan, np.nan, 58690, 900078, 69402, 900078]} df = pd.DataFrame(raw_data, columns = ['ref_maker', 'description', 'serial', 'maker', 'type', 'val, ''qty'])
下面是所需的输出(在列中):
条件:结果级联的描述列不得超过30个字符,并且不应剪切导入的单元格。
(部分涵盖在Prepare Pandas DataFrame for excel write中)
| ref | description (max 30 ch.) | qty | |-------- |---------------------------- |----- | | 409075 | Product 7 (12X) | 6 | | 405168 | Product 6 (8X) | 4 | | 35751 | Product 2 | 4 | | | MKR: Companyname1 | | | | Type: Rev. 0 | | | 39374 | Product 1 | 2 | | | MKR: Comp.2; SRL: 58690 | | | 331949 | Product 2 | 12 | | | MKR: Company3; SRL: 900078 | | | 331951 | Product 3 | 12 | | | MKR: Company name 4 | | | | SRL: 69402 | | | 307128 | Product 3 | 12 | | | MKR: Maker 5; Type: Type 5 | | | | SRL: 900078 | |
我试图找到解决方案,但是由于不了解(正确)解决方案,因此无法成功将其更改为我的需求。希望能满足要求。
感谢您的帮助和提示。