Xlsx

作者 bobmatnyc718070a7d622无许可证77 个星标收录于 2026年10月8日更新于 2026年10月8日仓库2个月前更新

Working with Excel files programmatically.

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AI 生成的概览

提供使用 Python 和 JavaScript 库读取、写入、格式化及转换 Excel XLSX 文件的参考说明。

功能: 提供以编程方式处理 Excel 电子表格的代码模式，涵盖单元格与行的读写、表头样式与数字格式设置、公式添加，以及 CSV 与 XLSX 之间的转换。内容同时展示 Python 的 openpyxl 与 pandas 用法和 JavaScript 的 xlsx 库用法，并包含合并多个工作簿、数据透视等操作。产出的是指导说明与代码片段，而非可直接运行的工具。
适用场景: 适用于智能体需要创建、编辑、格式化或提取 Excel 工作簿数据，或在电子表格与 CSV 之间转换的场景。也适用于合并多个 Excel 文件，或应用公式与单元格格式的情况。
运行要求: 运行 Python 示例需要安装 openpyxl 和 pandas 的 Python 环境；运行 JavaScript 示例需要包含 xlsx 包的 JavaScript 环境。该技能不附带脚本，仅包含说明与代码示例。

Excel/XLSX Manipulation

Working with Excel files programmatically.

Python (openpyxl)

Reading Excel

python

from openpyxl import load_workbook
wb = load_workbook('data.xlsx')ws = wb.active  # Get active sheet
# Read cellvalue = ws['A1'].value
# Iterate rowsfor row in ws.iter_rows(min_row=2, values_only=True):    print(row)

from openpyxl import load_workbook
wb = load_workbook('data.xlsx')ws = wb.active  # Get active sheet
# Read cellvalue = ws['A1'].value
# Iterate rowsfor row in ws.iter_rows(min_row=2, values_only=True):    print(row)

Writing Excel

python

from openpyxl import Workbook
wb = Workbook()ws = wb.activews.title = "Data"
# Write dataws['A1'] = 'Name'ws['B1'] = 'Age'ws.append(['John', 30])ws.append(['Jane', 25])
wb.save('output.xlsx')

from openpyxl import Workbook
wb = Workbook()ws = wb.activews.title = "Data"
# Write dataws['A1'] = 'Name'ws['B1'] = 'Age'ws.append(['John', 30])ws.append(['Jane', 25])
wb.save('output.xlsx')

Formatting

python

from openpyxl.styles import Font, PatternFill
# Bold headerws['A1'].font = Font(bold=True)
# Background colorws['A1'].fill = PatternFill(start_color="FFFF00", fill_type="solid")
# Number formatws['B2'].number_format = '0.00'  # Two decimals

from openpyxl.styles import Font, PatternFill
# Bold headerws['A1'].font = Font(bold=True)
# Background colorws['A1'].fill = PatternFill(start_color="FFFF00", fill_type="solid")
# Number formatws['B2'].number_format = '0.00'  # Two decimals

Formulas

Python (pandas)

Reading Excel

python

import pandas as pd
# Read sheetdf = pd.read_excel('data.xlsx', sheet_name='Sheet1')
# Read multiple sheetsdfs = pd.read_excel('data.xlsx', sheet_name=None)

import pandas as pd
# Read sheetdf = pd.read_excel('data.xlsx', sheet_name='Sheet1')
# Read multiple sheetsdfs = pd.read_excel('data.xlsx', sheet_name=None)

Writing Excel

python

# Write DataFramedf.to_excel('output.xlsx', index=False)
# Multiple sheetswith pd.ExcelWriter('output.xlsx') as writer:    df1.to_excel(writer, sheet_name='Sheet1')    df2.to_excel(writer, sheet_name='Sheet2')

# Write DataFramedf.to_excel('output.xlsx', index=False)
# Multiple sheetswith pd.ExcelWriter('output.xlsx') as writer:    df1.to_excel(writer, sheet_name='Sheet1')    df2.to_excel(writer, sheet_name='Sheet2')

Data Transformation

python

# Filterfiltered = df[df['Age'] > 25]
# Group bygrouped = df.groupby('Department')['Salary'].mean()
# Pivotpivot = df.pivot_table(values='Sales', index='Region', columns='Product')

# Filterfiltered = df[df['Age'] > 25]
# Group bygrouped = df.groupby('Department')['Salary'].mean()
# Pivotpivot = df.pivot_table(values='Sales', index='Region', columns='Product')

JavaScript (xlsx)

javascript

import XLSX from 'xlsx';
// Read fileconst workbook = XLSX.readFile('data.xlsx');const sheetName = workbook.SheetNames[0];const worksheet = workbook.Sheets[sheetName];
// Convert to JSONconst data = XLSX.utils.sheet_to_json(worksheet);
// Write fileconst newWorksheet = XLSX.utils.json_to_sheet(data);const newWorkbook = XLSX.utils.book_new();XLSX.utils.book_append_sheet(newWorkbook, newWorksheet, 'Data');XLSX.writeFile(newWorkbook, 'output.xlsx');

import XLSX from 'xlsx';
// Read fileconst workbook = XLSX.readFile('data.xlsx');const sheetName = workbook.SheetNames[0];const worksheet = workbook.Sheets[sheetName];
// Convert to JSONconst data = XLSX.utils.sheet_to_json(worksheet);
// Write fileconst newWorksheet = XLSX.utils.json_to_sheet(data);const newWorkbook = XLSX.utils.book_new();XLSX.utils.book_append_sheet(newWorkbook, newWorksheet, 'Data');XLSX.writeFile(newWorkbook, 'output.xlsx');

Common Operations

CSV to Excel

Excel to CSV

Merging Excel Files

python

dfs = []for file in ['file1.xlsx', 'file2.xlsx', 'file3.xlsx']:    df = pd.read_excel(file)    dfs.append(df)
combined = pd.concat(dfs, ignore_index=True)combined.to_excel('merged.xlsx', index=False)

dfs = []for file in ['file1.xlsx', 'file2.xlsx', 'file3.xlsx']:    df = pd.read_excel(file)    dfs.append(df)
combined = pd.concat(dfs, ignore_index=True)combined.to_excel('merged.xlsx', index=False)

Remember

Close workbooks after use
Handle large files in chunks
Validate data before writing
Use pandas for data analysis, openpyxl for formatting

来源与署名

来源：bobmatnyc/claude-mpm-skills位于universal/data/xlsx提交718070a

许可证：无许可证

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Xlsx

Excel/XLSX Manipulation

Python (openpyxl)

Reading Excel

Writing Excel

Formatting

Formulas

Python (pandas)

Reading Excel

Writing Excel

Data Transformation

JavaScript (xlsx)

Common Operations

CSV to Excel

Excel to CSV

Merging Excel Files

Remember

来源与署名

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