'Excel' 검색 결과

Inspect unfamiliar Excel workbooks before building extraction scripts. Map sheets, headers, columns, and row patterns, then use those findings to distinguish actual records from summaries and blank rows when extracting data.

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• Inspecting Excel files received from external sources
• Extracting records from sheets with merged cells
• Investigating missing or unexpected extraction results

Handle merged cells before filling Excel templates with openpyxl, a Python library for spreadsheets. This skill shows how to inspect merged ranges, unmerge the required areas, write values, and save the workbook without merged-cell write errors.

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• Fill an Excel template containing merged cells
• Resolve AttributeError when writing cell values
• Unmerge ranges across multiple worksheets

Recover from failed Excel creation or editing by switching from execute_code_sandbox to shell_agent. It guides clear task descriptions so the agent can install missing libraries, run code, retry errors, and confirm file creation.

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• Continuing Excel creation after a sandbox import error
• Creating a sales report with formulas and sample data
• Building multiple sheets with conditional formatting

Extracts, converts, or edits selected parts of spreadsheets, Word documents, PDFs, and PowerPoint files. It creates a separate output file, checks that the selection still matches the source, and verifies the saved result without modifying the original.

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• Export an Excel range as CSV, Markdown, or XLSX
• Extract Word paragraphs or create an edited copy
• Save a selected PDF page as a separate file

Builds an Excel model to estimate a company’s equity value from future cash flows. It calculates financing costs, compares three business scenarios, and shows how changes in growth, margins, and other assumptions affect valuation.

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• Estimating a company’s value from future cash flows
• Comparing bear, base, and bull scenarios
• Testing how growth and financing costs affect valuation

Create, edit, and clean spreadsheet files, including Excel workbooks and CSV data. Add formulas, formatting, and charts, preserve existing template styles, and recalculate formulas to check for errors before delivering the spreadsheet.

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• Clean messy CSV rows and headers into a usable spreadsheet
• Add formulas and charts to an existing Excel workbook
• Build a financial model with editable assumptions

Gather web information and turn it into an Excel workbook with explicit checks. Handles search failures through delegated research, records sources and missing data, and verifies the saved workbook against requested requirements.

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• Compiling competitor prices into a verified Excel workbook
• Organizing market data with sources and collection times
• Continuing research after repeated search failures

Continue Excel file creation and editing when execute_code_sandbox repeatedly fails with openpyxl errors. Use run_shell to run Python directly, then check that the workbook was saved with the expected sheets and content.

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• Continuing Excel creation after sandbox errors
• Editing existing workbooks and adjusting column widths
• Checking saved workbook sheets and content

Excel 数据分析多步编排器。覆盖：(1) 读取多 Sheet Excel 文件并统计行数，(2) 大文件检测（≥10k 行自动 Parquet 优化），(3) 数据清洗（缺失值、文本标准化、无效字符），(4) 条件筛选与分类提取，(5) 跨 Sheet 统计聚合，(6) 导出 Excel/CSV 并提供下载链接。覆盖从数据读取到报告生成全流程，按步骤编排 capability 子 skill。**遇到以下任一情况就主动使用本 skill，不要自行写几行 pandas 就回答**：①用户出现触发词：Excel 分析 / 表格分析 / 数据分析 / 数据清洗 / 数据统计 / 数据筛选 / 数据可视化 / 数据导出 / 汇总统计 / 透视表 / 分组统计 / 交叉分析 / 趋势分析 / 对比分析 / 异常值检测 / 去重 / 缺失值处理 / Excel 报告 / 生成报表 / analyze Excel / data analysis / data cleaning / pivot table；②用户上传或指定了 .xlsx / .xls / .csv 文件并要求分析、清洗、统计或可视化；③任务涉及多 Sheet 读取、条件筛选、分类汇总、图表生成中的任意一项；④用户要求导出带格式的 Excel 报告或下载链接。仅不用于：不涉及表格数据的纯文本处理、图片分析（使用 sn-da-image-caption）、单个公式计算的简单问答。

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Create financial Excel workbooks with Python, using formulas, color-coded inputs, source comments, and consistency checks. Build models that reviewers can trace and users can adjust by changing assumptions.

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• Build a financial model with traceable inputs
• Compare valuations under different assumptions
• Prepare a workbook for another person's review

Build an Excel workbook linking the income statement, balance sheet, and cash flow statement. Populate historical figures, create formula-based forecasts, compare scenarios, and check that balances and cash totals agree across all three statements.

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• Populating a financial model template with historical data
• Building linked forecasts across three financial statements
• Comparing base, upside, and downside scenarios

Create, edit, and clean spreadsheet files, convert table formats, and add formulas, formatting, or charts. The workflow includes recalculating formulas and checking errors before delivering a spreadsheet that updates when its inputs change.

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• Clean messy CSV data into a spreadsheet
• Add formulas and charts to an Excel workbook
• Create a spreadsheet template for data entry

Analyze Excel and CSV files to summarize statistics, filter records, compare groups, and join data across sheets or files. Export results as CSV, JSON, or Markdown tables for further work or sharing.

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• Compare monthly sales and top-selling products
• Combine order records with customer data
• Check missing values and statistical summaries

Turn company documents, public filings, and other sources into structured Excel workbooks for investment review. Organize financial statements and operating metrics, document sources and adjustments, and check that calculations and statements reconcile.

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• Preparing financial data for M&A due diligence
• Building materials for investment committee review
• Standardizing reporting across portfolio companies

Complete Excel templates for leveraged buyouts, acquisitions financed partly with debt. Add linked formulas for funding, operations, debt repayment, and investment returns, then check calculations and formatting while reviewing each major section with the user.

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• Completing an existing Excel buyout model template
• Checking funding totals and debt repayment priorities
• Calculating investment returns for committee materials

Prepare raw credit data for pre-loan modeling by checking data quality and screening variables. Review missing values, predictive usefulness, stability, noise, and correlation, then export an Excel report with organization-level statistics and cleaning results.

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• Prepare credit data before building a model
• Compare missing values and bad-sample rates across organizations
• Screen variables for usefulness, stability, and redundancy

Extract text from PDFs, Office documents, images, spreadsheets, and text files through one tool. Results share a common JSON structure, supporting document summaries, contract checks, and spreadsheet previews, with optical character recognition for scanned content.

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• Summarizing papers and reports
• Checking key clauses in Word contracts
• Previewing every sheet in an Excel workbook

Examine suspicious Word, Excel, and PowerPoint documents by extracting macros and untangling code designed to hide its purpose. Identify download addresses, execution triggers, and attack steps, then document findings and indicators for detecting related threats.

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• Investigating suspicious email attachments
• Finding download addresses hidden in VBA code
• Examining legacy Excel 4.0 macros

Create and edit Excel workbooks for data analysis, reports, and financial models. Build formulas that update with inputs, organize sheets, add charts and interactive pivot tables, and recalculate the workbook to check for formula errors.

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• Create an Excel report with charts
• Build a financial model with adjustable assumptions
• Summarize data in interactive pivot tables

Create and edit spreadsheet files, clean messy tables, and convert tabular formats. Add formulas, formatting, and charts while following existing template styles, then recalculate formulas and check for errors before delivering the spreadsheet.

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• Clean messy CSV data into a spreadsheet
• Add formulas and charts to an Excel workbook
• Update a workbook using its existing formatting

Process Excel workbooks and generate PDF reports by running Python scripts directly. Covers multiple sheets, data transformations, formatting, and error handling, with scripts saved as files for complex tasks.

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• Transform data across multiple Excel sheets
• Apply consistent formatting to spreadsheet reports
• Generate PDF reports from spreadsheet data

Validate spreadsheet sources before running Python scripts to transform data, update multiple sheets, or apply formatting. Check required data first, try backup sources when needed, and report errors clearly if processing cannot proceed.

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• Checking required columns before processing Excel files
• Transforming data and saving a new workbook
• Updating formatting across multiple sheets

Audit an Excel workbook before editing, then verify the saved file with Python and openpyxl. Each requested requirement receives an explicit status, so completion depends on checks of the actual file.

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• Verify exact sheet names and row counts
• Check sample size and category coverage
• Confirm required source sheets remain after editing

Process Excel files with Python after checking that input files and source URLs are accessible. The workflow covers data transformations, formulas, and formatting, with alternative sources and error logs when access fails.

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• Transforming Excel data after checking input files
• Applying formulas and formatting across multiple sheets
• Trying backup sources when a data URL is unavailable