142 lines
5.8 KiB
Python
142 lines
5.8 KiB
Python
import pandas as pd
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from tqdm import tqdm
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import openpyxl
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from openpyxl.styles import PatternFill
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# 读取Excel文件
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df = pd.read_excel(r"D:\Idea Project\F6+宜搭+其它(1)\new\竞品系统数据导出\爱车店数据导出.xlsx")
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# 初始化一个新的列表来存储结果
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result_list = []
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# 定义一个函数来安全地拆分字符串
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def safe_split(value, delimiter='\n'):
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if pd.notna(value):
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return value.split(delimiter)
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return ['']
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# 获取需要拆分的列名
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columns_to_split = {
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'产品名称组': ['产品名称', '型号', '单价', '数量', '总价', '销售人员', '销售时间'],
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'服务名称组': ['服务名称', '施工人员', '应付金额', '施工时间', '完工时间', '服务评分'],
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'支付方式组': ['支付方式', '账号', '金额', '时间', '备注']
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}
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# 获取需要保留的列名
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columns_to_keep = ['订单号', '开单时间', '入账时间', '车辆', '车主', '订单详情']
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# 使用 tqdm 包装 iterrows() 以显示进度条
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for index, row in tqdm(df.iterrows(), total=len(df), desc="处理数据"):
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# 存储每个组的拆分数据
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split_data_groups = {}
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# 拆分每个组的数据
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for group_name, cols in columns_to_split.items():
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split_data = {col: safe_split(row[col]) for col in cols}
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max_length = max(len(split_data[col]) for col in cols)
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for col in cols:
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split_data[col] += [''] * (max_length - len(split_data[col]))
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split_data_groups[group_name] = split_data
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# 检查是否有数据
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has_product_data = any(any(item.strip() != '' for item in split_data_groups['产品名称组'][col]) for col in
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columns_to_split['产品名称组'])
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has_service_data = any(any(item.strip() != '' for item in split_data_groups['服务名称组'][col]) for col in
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columns_to_split['服务名称组'])
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has_payment_data = any(any(item.strip() != '' for item in split_data_groups['支付方式组'][col]) for col in
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columns_to_split['支付方式组'])
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if not (has_product_data or has_service_data or has_payment_data):
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continue
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# 获取最大长度
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max_length = max(
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len(split_data_groups['产品名称组'][col][0]) for col in columns_to_split['产品名称组']
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) + max(
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len(split_data_groups['服务名称组'][col][0]) for col in columns_to_split['服务名称组']
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) + max(
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len(split_data_groups['支付方式组'][col][0]) for col in columns_to_split['支付方式组']
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)
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# 创建新的行
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for i in range(max_length):
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new_row = {}
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# 添加需要保留的列的数据（开单时间组放在最前面）
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for col in columns_to_keep:
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new_row[col] = row[col]
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# 添加产品名称组的数据
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for col in columns_to_split['产品名称组']:
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if i < len(split_data_groups['产品名称组'][col]):
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new_row[col] = split_data_groups['产品名称组'][col][i].strip()
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else:
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new_row[col] = ''
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# 添加服务名称组的数据
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for col in columns_to_split['服务名称组']:
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if i < len(split_data_groups['服务名称组'][col]):
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new_row[col] = split_data_groups['服务名称组'][col][i].strip()
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else:
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new_row[col] = ''
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# 添加支付方式组的数据
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for col in columns_to_split['支付方式组']:
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if i < len(split_data_groups['支付方式组'][col]):
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new_row[col] = split_data_groups['支付方式组'][col][i].strip()
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else:
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new_row[col] = ''
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# 检查新行是否有数据
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has_data = any(new_row[col] != '' for col in columns_to_split['产品名称组']) or \
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any(new_row[col] != '' for col in columns_to_split['服务名称组']) or \
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any(new_row[col] != '' for col in columns_to_split['支付方式组'])
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if has_data:
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# 将新行添加到结果列表中
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result_list.append(new_row)
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# 将结果列表转换为DataFrame
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result_df = pd.DataFrame(result_list)
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# 保存结果到新的Excel文件
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file_path = 'result.xlsx'
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result_df.to_excel(file_path, index=False)
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# 加载Excel文件并设置背景颜色
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wb = openpyxl.load_workbook(file_path)
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ws = wb.active
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# 定义背景颜色
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color_dict = {
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'开单时间': 'FFFFFF', # 白色
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'产品名称': 'FFFF00', # 黄色
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'服务名称': '00FF00', # 绿色
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'支付方式': '0000FF' # 蓝色
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}
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# 设置背景颜色
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for row in ws.iter_rows(min_row=2, max_row=ws.max_row, min_col=1, max_col=ws.max_column):
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for cell in row:
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if cell.column_letter in [ws[1][i].column_letter for i, col in enumerate(columns_to_keep)]:
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cell.fill = PatternFill(start_color=color_dict['开单时间'], end_color=color_dict['开单时间'],
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fill_type='solid')
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elif cell.column_letter in [ws[1][i].column_letter for i, col in enumerate(columns_to_split['产品名称组'])]:
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cell.fill = PatternFill(start_color=color_dict['产品名称'], end_color=color_dict['产品名称'],
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fill_type='solid')
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elif cell.column_letter in [ws[1][i].column_letter for i, col in enumerate(columns_to_split['服务名称组'])]:
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cell.fill = PatternFill(start_color=color_dict['服务名称'], end_color=color_dict['服务名称'],
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fill_type='solid')
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elif cell.column_letter in [ws[1][i].column_letter for i, col in enumerate(columns_to_split['支付方式组'])]:
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cell.fill = PatternFill(start_color=color_dict['支付方式'], end_color=color_dict['支付方式'],
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fill_type='solid')
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# 保存Excel文件
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wb.save(file_path)
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wb.close()
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print("数据拆分完成，已保存到result.xlsx")
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