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Python操作Excel终极指南:告别手动复制粘贴的噩梦

Python操作Excel终极指南:告别手动复制粘贴的噩梦

Python操作Excel终极指南:告别手动复制粘贴的噩梦

说实话,作为程序员,我最怕听到的不是"需求又改了",而是——

"帮我把这几十个Excel表的数据合并一下"
"把这两列数据提取出来做个汇总"
"给每个sheet加个格式,要好看的那种"

然后我就打开了Excel,开始Ctrl+C、Ctrl+V、拖拽、筛选、复制……半小时过去了,手都酸了,眼睛也花了。

停!你是程序员啊!这种重复性工作不应该交给代码吗?

今天这篇文章,就把 Python 操作 Excel 的全套技能给你讲透。看完你就能把这些脏活累活全甩给脚本,自己泡杯茶看着它跑就行。

为什么选 openpyxl?

Python 操作 Excel 的库不少,但真正好用的就这几个:

库名格式适用场景
openpyxl✅ 样式/图表/公式首选,.xlsx 文件全能选手
pandas❌ 弱数据分析,批量读写快
xlrd/xlwt老项目 .xls 格式
xlsxwriter只写不读,生成报表用
结论:日常办公自动化,openpyxl 一把手。

先装一下:

bash
pip install openpyxl

场景一:批量读取数据(再也不用手动翻表了)

基础读取

python
from openpyxl import load_workbook

# 打开已有的Excel文件
wb = load_workbook('数据表.xlsx')

# 查看所有sheet名称
print(wb.sheetnames)  # ['Sheet1', 'Sheet2', '汇总']

# 选择一个sheet
ws = wb['Sheet1']

# 读取单个单元格(三种方式)
print(ws['A1'].value)        # 用坐标
print(ws.cell(row=1, column=1).value)  # 用行列号

# 读取一行
for cell in ws[1]:
    print(cell.value, end=' ')
# 输出:姓名 年龄 部门 薪资

# 读取所有数据(常用!)
data = []
for row in ws.iter_rows(min_row=2, values_only=True):  # 从第2行开始,跳过表头
    data.append(row)

print(data)
# [('张三', 28, '研发部', 15000), ('李四', 32, '产品部', 18000), ...]

按条件筛选数据

python
from openpyxl import load_workbook

wb = load_workbook('员工表.xlsx')
ws = wb.active

# 筛选薪资大于15000的员工
high_salary = []
for row in ws.iter_rows(min_row=2, values_only=True):
    name, age, dept, salary = row
    if salary and salary > 15000:
        high_salary.append({
            '姓名': name,
            '部门': dept,
            '薪资': salary
        })

for emp in high_salary:
    print(f"{emp['姓名']} - {emp['部门']} - ¥{emp['薪资']}")
实际效果

:以前翻半小时的表,现在3行代码搞定。


场景二:创建和写入Excel(从零生成报表)

python
from openpyxl import Workbook
from openpyxl.styles import Font, Alignment, PatternFill, Border, Side

# 创建新的工作簿
wb = Workbook()
ws = wb.active
ws.title = '销售报表'

# ====== 写入数据 ======
headers = ['产品名称', '销量', '单价', '销售额']
data = [
    ['手机A', 1200, 2999],
    ['手机B', 800, 3999],
    ['耳机X', 3500, 299],
    ['充电宝Y', 2100, 89],
]

# 写入表头
for col, header in enumerate(headers, start=1):
    cell = ws.cell(row=1, column=col, value=header)

# 写入数据并计算销售额
for row_idx, row_data in enumerate(data, start=2):
    for col_idx, value in enumerate(row_data, start=1):
        ws.cell(row=row_idx, column=col_idx, value=value)
    # 销售额 = 销量 × 单价(写入公式)
    ws.cell(row=row_idx, column=4, value=f'=B{row_idx}*C{row_idx}')

# ====== 设置格式(让表格好看!)=====

# 表头样式:加粗、白色字、深蓝背景
header_font = Font(bold=True, color='FFFFFF', size=12)
header_fill = PatternFill(start_color='366092', end_color='366092', fill_type='solid')
header_align = Alignment(horizontal='center', vertical='center')

thin_border = Border(
    left=Side(style='thin'),
    right=Side(style='thin'),
    top=Side(style='thin'),
    bottom=Side(style='thin')
)

# 应用表头样式
for col in range(1, 5):
    cell = ws.cell(row=1, column=col)
    cell.font = header_font
    cell.fill = header_fill
    cell.alignment = header_align
    cell.border = thin_border

# 数据区域样式:居中、边框
data_align = Alignment(horizontal='center', vertical='center')
alt_fill = PatternFill(start_color='F0F8FF', end_color='F0F8FF', fill_type='solid')  # 隔行变色

for row in range(2, len(data) + 2):
    for col in range(1, 5):
        cell = ws.cell(row=row, column=col)
        cell.alignment = data_align
        cell.border = thin_border
        if row % 2 == 0:
            cell.fill = alt_fill

# 数字格式化:货币
for row in range(2, len(data) + 2):
    ws.cell(row=row, column=3).number_format = '¥#,##0'   # 单价
    ws.cell(row=row, column=4).number_format = '¥#,##0'   # 销售额

# ====== 冻结首行 + 列宽自适应 ======
ws.freeze_panes = 'A2'  # 冻结第一行,滚动时表头不动
ws.column_dimensions['A'].width = 15
ws.column_dimensions['B'].width = 10
ws.column_dimensions['C'].width = 10
ws.column_dimensions['D'].width = 12

# 保存
wb.save('销售报表.xlsx')
print('✅ 报表已生成:销售报表.xlsx')
运行结果

:一个带样式、有公式、能直接发给老板看的Excel报表。


场景三:合并多个Excel文件(HR和财务最爱)

这个需求太常见了——每个月各部门交上来的表格,你要合并成一张总表。

python
from openpyxl import load_workbook, Workbook
import os
import glob

def merge_excels(file_pattern, output_file, has_header=True):
    """
    合并多个Excel文件到一个工作簿
    :param file_pattern: 文件通配符,如 'sales/*.xlsx'
    :param output_file: 输出文件名
    :param has_header: 是否保留表头(只保留第一个文件的)
    """
    files = glob.glob(file_pattern)
    
    if not files:
        print(f'❌ 没有找到匹配的文件: {file_pattern}')
        return
    
    wb_out = Workbook()
    ws_out = wb_out.active
    ws_out.title = '合并结果'
    
    header_written = False
    
    for idx, file_path in enumerate(files):
        print(f'📂 正在处理: {os.path.basename(file_path)}')
        
        try:
            wb_in = load_workbook(file_path)
            ws_in = wb_in.active
            
            # 决定是否跳过表头
            start_row = 1 if (not header_written or not has_header) else 2
            
            for row in ws_in.iter_rows(min_row=start_row, values_only=True):
                ws_out.append(list(row))
            
            if has_header and not header_written:
                header_written = True
            
            wb_in.close()
            
        except Exception as e:
            print(f'⚠️ 处理 {os.path.basename(file_path)} 出错: {e}')
    
    wb_out.save(output_file)
    print(f'\n✅ 合并完成!共 {len(files)} 个文件 → {output_file}')
    print(f'📊 总计 {ws_out.max_row - 1} 条数据(不含表头)')


# 使用示例
merge_excels(
    file_pattern='月报/*.xlsx',
    output_file='月报汇总.xlsx',
    has_header=True
)
效果

:50个部门的Excel,30秒合并完毕。


场景四:拆分大表为多个小表

反过来,有时候你需要把一个大表按某个字段拆分成多个小文件:

python
from openpyxl import load_workbook, Workbook
from collections import defaultdict

def split_by_column(input_file, column_index, output_dir):
    """
    按指定列拆分Excel
    :param input_file: 输入文件
    :param column_index: 拆分依据的列号(从1开始)
    :param output_dir: 输出目录
    """
    os.makedirs(output_dir, exist_ok=True)
    
    wb_in = load_workbook(input_file)
    ws_in = wb_in.active
    
    # 按列值分组
    groups = defaultdict(list)
    headers = None
    
    for row_idx, row in enumerate(ws_in.iter_rows(values_only=True)):
        if row_idx == 0:
            headers = list(row)
            continue
        
        key = str(row[column_index - 1]) if row[column_index - 1] else '未分类'
        groups[key].append(list(row))
    
    # 每个分组保存为一个文件
    for key, rows in groups.items():
        wb_out = Workbook()
        ws_out = wb_out.active
        ws_out.title = key[:31]  # sheet名最长31字符
        
        if headers:
            ws_out.append(headers)
        
        for row in rows:
            ws_out.append(row)
        
        safe_name = ''.join(c for c in key if c.isalnum() or c in '_-') or 'unknown'
        output_path = os.path.join(output_dir, f'{safe_name}.xlsx')
        wb_out.save(output_path)
        print(f'✅ {key}: {len(rows)}条 → {output_path}')
    
    print(f'\n📊 共拆分出 {len(groups)} 个文件')

# 使用示例:按部门拆分员工表
split_by_column('全员名单.xlsx', column_index=3, output_dir='按部门/')

场景五:对比两个表的差异

财务对账、版本对比,这个功能救过我不止一次命:

python
from openpyxl import load_workbook
from openpyxl.styles import PatternFill

RED = PatternFill(start_color='FFCCCC', end_color='FFCCCC', fill_type='solid')
GREEN = PatternFill(start_color='CCFFCC', end_color='CCFFCC', fill_type='solid')
YELLOW = PatternFill(start_color='FFFFCC', end_color='FFFFCC', fill_type='solid')

def compare_excels(file_a, file_b, key_col, compare_cols, output_file):
    """
    对比两个Excel的差异
    :param key_col: 主键列号(用于匹配同一行记录)
    :param compare_cols: 要比较的列号列表
    """
    wb_a = load_workbook(file_a)
    wb_b = load_workbook(file_b)
    
    ws_a = wb_a.active
    ws_b = wb_b.active
    
    # 构建字典以便对比
    def build_map(ws, key_col):
        data_map = {}
        for row in ws.iter_rows(min_row=2, values_only=True):
            key = str(row[key_col - 1])
            data_map[key] = row
        return data_map
    
    map_a = build_map(ws_a, key_col)
    map_b = build_map(ws_b, key_col)
    
    keys_all = set(map_a.keys()) | set(map_b.keys())
    
    # 新建差异报告
    from openpyxl import Workbook
    wb_out = Workbook()
    ws_out = wb_out.active
    ws_out.title = '差异报告'
    
    # 写入表头
    headers = ['主键', '状态'] + [f'列{c}' for c in compare_cols]
    ws_out.append(headers)
    
    only_in_a = 0
    only_in_b = 0
    diff_count = 0
    
    for key in sorted(keys_all):
        if key not in map_a:
            row_data = ['仅在新表中', key] + [map_b[key][c-1] if c <= len(map_b[key]) else '' for c in compare_cols]
            ws_out.append(row_data)
            for col in range(1, len(row_data)+1):
                ws_out.cell(row=ws_out.max_row, column=col).fill = RED
            only_in_b += 1
        elif key not in map_b:
            row_data = ['仅在旧表中', key] + [map_a[key][c-1] if c <= len(map_a[key]) else '' for c in compare_cols]
            ws_out.append(row_data)
            for col in range(1, len(row_data)+1):
                ws_out.cell(row=ws_out.max_row, column=col).fill = YELLOW
            only_in_a += 1
        else:
            differences = []
            for c in compare_cols:
                val_a = map_a[key][c-1] if c < len(map_a[key]) else ''
                val_b = map_b[key][c-1] if c < len(map_b[key]) else ''
                if val_a != val_b:
                    differences.append(f'{val_a}→{val_b}')
            
            if differences:
                row_data = ['有变化', key] + differences
                ws_out.append(row_data)
                ws_out.cell(row=ws_out.max_row, column=1).fill = GREEN
                diff_count += 1
    
    wb_out.save(output_file)
    
    print(f'📊 对比完成!')
    print(f'   🟡 仅在旧表: {only_in_a} 条')
    print(f'   🔴 仅在新表: {only_in_b} 条')  
    print(f'   🟢 有变化:   {diff_count} 条')
    print(f'   📄 报告已保存到: {output_file}')

# 使用示例:对比本月和上月工资表
compare_excels(
    file_a='工资表-上月.xlsx',
    file_b='工资表-本月.xlsx',
    key_col=1,          # 以姓名为主键
    compare_cols=[4],    # 对比薪资列
    output_file='工资变动报告.xlsx'
)

输出结果一目了然,红色新增、黄色删除、绿色变化。


场景六:批量修改格式(一次性搞定所有丑表格)

python
from openpyxl import load_workbook
from openpyxl.styles import Font, Alignment, PatternFill, Border, Side

def beautify_excel(file_path, output_path=None):
    """一键美化Excel表格"""
    if output_path is None:
        output_path = file_path
    
    wb = load_workbook(file_path)
    ws = wb.active
    
    # 定义样式
    title_font = Font(bold=True, size=14, color='1F4E79')
    header_font = Font(bold=True, color='FFFFFF', size=11)
    header_fill = PatternFill(start_color='2E75B6', end_color='2E75B6', fill_type='solid')
    
    border = Border(
        left=Side(style='thin', color='D9D9D9'),
        right=Side(style='thin', color='D9D9D9'),
        top=Side(style='thin', color='D9D9D9'),
        bottom=Side(style='thin', color='D9D9D9')
    )
    
    center = Alignment(horizontal='center', vertical='center', wrap_text=True)
    
    # 处理每一行
    for row_idx, row in enumerate(ws.iter_rows(), start=1):
        for col_idx, cell in enumerate(row, start=1):
            cell.border = border
            
            if row_idx == 1:  # 表头
                cell.font = header_font
                cell.fill = header_fill
                cell.alignment = center
            else:  # 数据区
                cell.alignment = Alignment(vertical='center')
                
                # 自动识别数字格式
                if isinstance(cell.value, (int, float)):
                    cell.number_format = '#,##0.00' if isinstance(cell.value, float) else '#,##0'
                    cell.alignment = Alignment(horizontal='right', vertical='center')
                
                # 隔行变色
                if row_idx % 2 == 0:
                    cell.fill = PatternFill(start_color='F2F2F2', end_color='F2F2F2', fill_type='solid')
    
    # 自适应列宽(简单版)
    for col_cells in ws.columns:
        max_length = 0
        column = col_cells[0].column_letter
        for cell in col_cells:
            try:
                if cell.value:
                    max_length = max(max_length, len(str(cell.value)))
            except:
                pass
        ws.column_dimensions[column].width = min(max_length + 3, 40)
    
    # 冻结首行
    ws.freeze_panes = 'A2'
    
    # 设置打印区域和页面方向
    ws.print_title_rows = '1:1'  # 每页重复打印表头
    
    wb.save(output_path)
    print(f'✅ 美化完成: {output_path}')

# 批量美化目录下所有xlsx
import glob
for f in glob.glob('待处理/*.xlsx'):
    beautify_excel(f, f'已美化/{f.split("/")[-1]}')

高级技巧速查卡

图表生成

python
from openpyxl.chart import BarChart, Reference

# 基于已有数据创建柱状图
chart = BarChart()
chart.type = "col"
chart.grouping = "clustered"
chart.title = "各产品销售对比"
chart.y_axis.title = '销售额'
chart.x_axis.title = '产品'

data = Reference(ws, min_col=4, min_row=1, max_row=5, max_col=4)
categories = Reference(ws, min_col=1, min_row=2, max_row=5)
chart.add_data(data, titles_from_data=True)
chart.set_categories(categories)
chart.shape = 4
ws.add_chart(chart, "F2")

数据验证(下拉框)

python
from openpyxl.worksheet.datavalidation import DataValidation

# 创建下拉选项
dv = DataValidation(
    type="list",
    formula1='"研发部,产品部,市场部,财务部,人事部"',
    allow_blank=True
)
dv.error = '请从下拉列表中选择部门'
dv.errorTitle = '无效输入'

# 应用到某列
dv.add('C2:C100')
ws.add_data_validation(dv)

条件格式

python
from openpyxl.formatting.rule import CellIsRule
from openpyxl.styles import PatternFill

# 大于10000的单元格标红
red_fill = PatternFill(start_color='FF0000', end_color='FF0000', fill_type='solid')
rule = CellIsRule(operator='greaterThan', formula=['10000'], fill=red_fill)
ws.conditional_formatting.add('D2:D100', rule)

性能优化:大数据量怎么办?

当数据量超过几万行时,openpyxl 默认模式会比较慢。这时候要用只写模式

python
# 只写模式(超快!适合大批量导出)
from openpyxl import Workbook

wb = Workbook(write_only=True)
ws = wb.create_sheet()

# 写入10万行数据测试
for i in range(100000):
    ws.append([f'数据{i}', i * 100, '分类A' if i % 2 == 0 else '分类B'])

wb.save('大量数据.xlsx')  # 秒级完成
数据量普通模式只写模式
1000行<1秒<1秒
1万行~5秒~1秒
10万行~60秒~3秒
50万行内存爆炸~15秒
记住:写大文件用 write_only=True,读大文件用 read_only=True

总结

场景核心函数代码量
读取数据load_workbook + iter_rows~10行
创建报表Workbook + 样式设置~40行
合并多表glob + 循环 append~25行
拆分大表defaultdict 分组~20行
对比差异字典比对 + 颜色标记~45行
批量美化遍历单元格设样式~30行

说到底,程序员的核心竞争力不是手速快,而是能把重复劳动自动化

下次再有人让你"帮忙弄一下Excel",别傻乎乎地打开鼠标点来点去了。花10分钟写个脚本,以后同类需求一键搞定,省下的时间去摸鱼不香吗?


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