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Create and process Excel files, PDF checklists, and structured reports by running Python scripts directly. The skill covers multiple sheets, formulas, formatting, data transformations, and error handling for document workflows with several steps.
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Create or edit Excel workbooks with checks for sheet names, row counts, formulas, and merged cells. Reopen the saved file and verify each requirement, recording explicit results rather than relying on a completion summary.
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Create and edit Excel workbooks by running a complete Python script through the shell. Covers multiple sheets, data entry, formatting, formulas, and saving files when other file-reading or code-execution tools fail.
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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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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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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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Audit generated Excel reports by reopening saved workbooks, listing populated rows and formulas, and comparing subtotal references with independently identified detail rows. Detect missing or extra rows in totals and preserve an inspection log.
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Clean Excel data and group records with similar numerical features. Produce a combined view of indicator trends, value distributions, category shares, and grouped data, then export the charts as an image and cleaned records as Excel.
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Filter Excel data using candidate column names, RGB color values, text prefixes, and regular expressions, which match text patterns. Calculate totals and averages, then export results to Excel with highlighted rows and a download link.
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Analyze Excel data using custom categories, count distributions, and compare groups with charts. Score text using its length, technical terms, numbers, and selected complex concepts, then visualize difficulty levels and the relationship between text length and scores.
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Extract coefficients associated with a chosen label across Excel sheets and check them against a standard value. Create a comparison workbook showing each value, its source sheet, and red highlighting for rows that fail the check.
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以Excel财务模型为依据，生成PowerPoint文件，为幻灯片中的数值标注来源工作表和单元格，并可使用公司模板及原工作簿的图表图片。
生成Excel文件，估算企业收购对每股收益的影响。整理收购价格、融资和协同效应假设，制作不同条件的比较表，以及用于说明收购影响的摘要。
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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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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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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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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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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Turn research results into figures and tables for papers using pubfig and pubtab. Choose an appropriate presentation, convert Excel tables to LaTeX, export assets, and check readability, labels, and consistency before submission.
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Analyze Excel data by classifying items, calculating counts and percentages, and comparing categories across groups. Identify values above related limits, then produce a pie chart and an Excel statistics file with download links.
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Clean numeric columns in Excel, filter records above a chosen threshold, and count matching rows. The skill also covers checking row totals across sheets and marking qualifying cells with formatting for export.
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Clean category data in Excel, group entries, and calculate counts, totals, and shares. Create a summary spreadsheet with a total row and highlighted maximum values, alongside a bar chart for comparing groups.
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Extract key metrics from spreadsheet data, check whether recorded values match calculations after unit conversion, and rank selected metrics from highest to lowest. Export the ranking or validation results to an Excel file for download.
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Combine selected data from multiple Excel sheets, clean numeric values, and extract the highest entries for a chosen metric. Create a ranked Excel report with highlighted columns, borders, column widths, and number formats for easier comparison.
中文简介正在准备中。当前显示英语简介。