Python实现Excel报表自动化的实践教程

# 安装必要的库
pip install pandas openpyxl matplotlib

import pandas as pd

def read_sales_data(file_path):
    """读取销售数据"""
    # 读取多个 sheet
    excel_file = pd.ExcelFile(file_path)
    
    data = {}
    for sheet_name in excel_file.sheet_names:
        data[sheet_name] = pd.read_excel(file_path, sheet_name=sheet_name)
    
    return data

# 使用示例
data = read_sales_data('sales_data.xlsx')
orders = data['订单表']
print(orders.head())

def generate_summary(orders_df):
    """生成销售汇总"""
    summary = {
        '总销售额': orders_df['金额'].sum(),
        '订单数量': len(orders_df),
        '平均订单金额': orders_df['金额'].mean(),
        '最大订单': orders_df['金额'].max(),
        '最小订单': orders_df['金额'].min()
    }
    return summary

# 产品销量排行
def product_ranking(orders_df):
    """产品销量排行"""
    ranking = orders_df.groupby('产品名称').agg({
        '数量': 'sum',
        '金额': 'sum'
    }).sort_values('金额', ascending=False)
    
    return ranking

def create_report(data, output_path):
    """生成报表文件"""
    with pd.ExcelWriter(output_path, engine='openpyxl') as writer:
        # 写入汇总数据
        summary_df = pd.DataFrame([generate_summary(data['订单表'])])
        summary_df.to_excel(writer, sheet_name='汇总', index=False)
        
        # 写入产品排行
        ranking = product_ranking(data['订单表'])
        ranking.to_excel(writer, sheet_name='产品排行')
        
        # 写入原始数据
        for sheet_name, df in data.items():
            df.to_excel(writer, sheet_name=sheet_name, index=False)
    
    print(f"报表已生成：{output_path}")

# 使用
create_report(data, '月度销售报表.xlsx')

import matplotlib.pyplot as plt
from openpyxl.drawing.image import Image as XLImage

def add_charts(excel_path):
    """为报表添加图表"""
    from openpyxl import load_workbook
    
    wb = load_workbook(excel_path)
    
    # 创建图表数据
    ranking = pd.read_excel(excel_path, sheet_name='产品排行')
    
    # 生成柱状图
    plt.figure(figsize=(10, 6))
    ranking['金额'].head(10).plot(kind='bar')
    plt.title('Top 10 产品销售额')
    plt.tight_layout()
    plt.savefig('chart.png')
    plt.close()
    
    # 插入到 Excel
    ws = wb.create_sheet('图表')
    img = XLImage('chart.png')
    ws.add_image(img, 'A1')
    
    wb.save(excel_path)
    print("图表已添加")

import pandas as pd
import matplotlib.pyplot as plt
from openpyxl import load_workbook
from openpyxl.drawing.image import Image as XLImage
import os
from datetime import datetime

def auto_generate_report(input_folder, output_folder):
    """自动生成月度报表"""
    
    # 确保输出文件夹存在
    os.makedirs(output_folder, exist_ok=True)
    
    # 获取当前月份
    current_month = datetime.now().strftime('%Y年%m月')
    output_file = f"{output_folder}/{current_month}销售报表.xlsx"
    
    # 读取所有数据文件
    all_data = []
    for file in os.listdir(input_folder):
        if file.endswith('.xlsx'):
            file_path = os.path.join(input_folder, file)
            data = read_sales_data(file_path)
            all_data.append(data['订单表'])
    
    # 合并数据
    combined_data = pd.concat(all_data, ignore_index=True)
    
    # 生成报表
    create_report({'订单表': combined_data}, output_file)
    
    # 添加图表
    add_charts(output_file)
    
    print(f"✅ 报表生成完成：{output_file}")
    return output_file

# 每月自动执行
if __name__ == '__main__':
    auto_generate_report('./raw_data', './reports')

# 处理缺失值
orders_df['金额'].fillna(0, inplace=True)

# 数据类型转换
orders_df['日期'] = pd.to_datetime(orders_df['日期'])

# 异常值处理
orders_df = orders_df[orders_df['金额'] > 0]

from openpyxl.styles import PatternFill

def highlight_top10(excel_path):
    """高亮显示前10名"""
    wb = load_workbook(excel_path)
    ws = wb['产品排行']
    
    # 红色填充
    red_fill = PatternFill(start_color='FF0000', end_color='FF0000', fill_type='solid')
    
    # 高亮前10行
    for row in range(2, 12):
        for col in range(1, 4):
            ws.cell(row=row, column=col).fill = red_fill
    
    wb.save(excel_path)

# 添加到 crontab，每月1号凌晨执行
0 0 1 * * /usr/bin/python3 /path/to/auto_generate_report.py