Field处理

import pandas as pd
import os
from datetime import datetime

read_file = 'Yield原始(1).xlsx'
save_file = 'Yield处理结果.csv'


def fox(row):
    return row['gooddie_number'] / row['grossdie_number'] * 100


def ff(row):
    return datetime.strptime(str(row).split()[0], '%Y-%m-%d').strftime("%W")


df = pd.read_excel(read_file)

df['File_name'] = os.path.split(read_file)[-1]
df['Creat_time'] = ''
df['Shipping_date'] = df['出货日期']
df['Po_number'] = df['用户PO']
df['Wafer_id'] = df['WaferID']
df['gooddie_number'] = df['Gooddie'].map(lambda x: int(x))
df['grossdie_number'] = df['Grossdie'].map(lambda x: int(x))
df['Shipping_yield'] = df.apply(fox, axis=1)
df['Week'] = df['Shipping_date'].apply(ff)
df['Saic_prod_id'] = df['编号']
df['Units'] = df['库存单位']
df['Cp1_yield'] = ''
df['Delta_yield'] = ''

new_df = df[['File_name', 'Creat_time', 'Po_number', 'Shipping_date', 'Week',
          'Saic_prod_id', 'Wafer_id', 'gooddie_number', 'Units', 'grossdie_number',
          'Shipping_yield', 'Cp1_yield', 'Delta_yield']]

# for idx, row in new_df.iterrows():
#     print(row)
new_df.to_csv(save_file, index=False)