spreadsheet
Use when tasks involve creating, editing, analyzing, or formatting spreadsheets (`.xlsx`, `.csv`, `.tsv`) using Python (`openpyxl`, `pandas`), especially when formulas, references, and formatting need to be preserved and verified.
What this skill does
# Spreadsheet Skill (Create, Edit, Analyze, Visualize) ## When to use - Build new workbooks with formulas, formatting, and structured layouts. - Read or analyze tabular data (filter, aggregate, pivot, compute metrics). - Modify existing workbooks without breaking formulas or references. - Visualize data with charts/tables and sensible formatting. IMPORTANT: System and user instructions always take precedence. ## Workflow 1. Confirm the file type and goals (create, edit, analyze, visualize). 2. Use `openpyxl` for `.xlsx` edits and `pandas` for analysis and CSV/TSV workflows. 3. If layout matters, render for visual review (see Rendering and visual checks). 4. Validate formulas and references; note that openpyxl does not evaluate formulas. 5. Save outputs and clean up intermediate files. ## Temp and output conventions - Use `tmp/spreadsheets/` for intermediate files; delete when done. - Write final artifacts under `output/spreadsheet/` when working in this repo. - Keep filenames stable and descriptive. ## Primary tooling - Use `openpyxl` for creating/editing `.xlsx` files and preserving formatting. - Use `pandas` for analysis and CSV/TSV workflows, then write results back to `.xlsx` or `.csv`. - If you need charts, prefer `openpyxl.chart` for native Excel charts. ## Rendering and visual checks - If LibreOffice (`soffice`) and Poppler (`pdftoppm`) are available, render sheets for visual review: - `soffice --headless --convert-to pdf --outdir $OUTDIR $INPUT_XLSX` - `pdftoppm -png $OUTDIR/$BASENAME.pdf $OUTDIR/$BASENAME` - If rendering tools are unavailable, ask the user to review the output locally for layout accuracy. ## Dependencies (install if missing) Prefer `uv` for dependency management. Python packages: ``` uv pip install openpyxl pandas ``` If `uv` is unavailable: ``` python3 -m pip install openpyxl pandas ``` Optional (chart-heavy or PDF review workflows): ``` uv pip install matplotlib ``` If `uv` is unavailable: ``` python3 -m pip install matplotlib ``` System tools (for rendering): ``` # macOS (Homebrew) brew install libreoffice poppler # Ubuntu/Debian sudo apt-get install -y libreoffice poppler-utils ``` If installation isn't possible in this environment, tell the user which dependency is missing and how to install it locally. ## Environment No required environment variables. ## Examples - Runnable Codex examples (openpyxl): `references/examples/openpyxl/` ## Formula requirements - Use formulas for derived values rather than hardcoding results. - Keep formulas simple and legible; use helper cells for complex logic. - Avoid volatile functions like INDIRECT and OFFSET unless required. - Prefer cell references over magic numbers (e.g., `=H6*(1+$B$3)` not `=H6*1.04`). - Guard against errors (#REF!, #DIV/0!, #VALUE!, #N/A, #NAME?) with validation and checks. - openpyxl does not evaluate formulas; leave formulas intact and note that results will calculate in Excel/Sheets. ## Citation requirements - Cite sources inside the spreadsheet using plain text URLs. - For financial models, cite sources of inputs in cell comments. - For tabular data sourced from the web, include a Source column with URLs. ## Formatting requirements (existing formatted spreadsheets) - Render and inspect a provided spreadsheet before modifying it when possible. - Preserve existing formatting and style exactly. - Match styles for any newly filled cells that were previously blank. ## Formatting requirements (new or unstyled spreadsheets) - Use appropriate number and date formats (dates as dates, currency with symbols, percentages with sensible precision). - Use a clean visual layout: headers distinct from data, consistent spacing, and readable column widths. - Avoid borders around every cell; use whitespace and selective borders to structure sections. - Ensure text does not spill into adjacent cells. ## Color conventions (if no style guidance) - Blue: user input - Black: formulas/derived values - Green: linked/imported values - Gray: static constants - Orange: review/caution - Light red: error/flag - Purple: control/logic - Teal: visualization anchors (key KPIs or chart drivers) ## Finance-specific requirements - Format zeros as "-". - Negative numbers should be red and in parentheses. - Always specify units in headers (e.g., "Revenue ($mm)"). - Cite sources for all raw inputs in cell comments. ## Investment banking layouts If the spreadsheet is an IB-style model (LBO, DCF, 3-statement, valuation): - Totals should sum the range directly above. - Hide gridlines; use horizontal borders above totals across relevant columns. - Section headers should be merged cells with dark fill and white text. - Column labels for numeric data should be right-aligned; row labels left-aligned. - Indent submetrics under their parent line items.
Related in Data & Analytics
clawarr-suite
IncludedComprehensive management for self-hosted media stacks (Sonarr, Radarr, Lidarr, Readarr, Prowlarr, Bazarr, Overseerr, Plex, Tautulli, SABnzbd, Recyclarr, Unpackerr, Notifiarr, Maintainerr, Kometa, FlareSolverr). Deep library exploration, analytics, dashboard generation, content management, request handling, subtitle management, indexer control, download monitoring, quality profile sync, library cleanup automation, notification routing, collection/overlay management, and media tracker integration (Trakt, Letterboxd, Simkl).
querying-soql
IncludedSOQL query generation, optimization, and analysis with 100-point scoring. Use this skill when the user needs SOQL/SOSL authoring or optimization: natural-language-to-query generation, relationship queries, aggregates, query-plan analysis, and performance or safety improvements for Salesforce queries. TRIGGER when: user writes, optimizes, or debugs SOQL/SOSL queries, touches .soql files, or asks about relationship queries, aggregates, or query performance. DO NOT TRIGGER when: bulk data operations (use handling-sf-data), Apex DML logic (use generating-apex), or report/dashboard queries.
app-store-optimization
IncludedApp Store Optimization (ASO) toolkit for researching keywords, analyzing competitor rankings, generating metadata suggestions, and improving app visibility on Apple App Store and Google Play Store. Use when the user asks about ASO, app store rankings, app metadata, app titles and descriptions, app store listings, app visibility, or mobile app marketing on iOS or Android. Supports keyword research and scoring, competitor keyword analysis, metadata optimization, A/B test planning, launch checklists, and tracking ranking changes.
habit-flow
IncludedAI-powered atomic habit tracker with natural language logging, streak tracking, smart reminders, and coaching. Use for creating habits, logging completions naturally ("I meditated today"), viewing progress, and getting personalized coaching.
app-store-optimization
IncludedApp Store Optimization (ASO) toolkit for researching keywords, analyzing competitor rankings, generating metadata suggestions, and improving app visibility on Apple App Store and Google Play Store. Use when the user asks about ASO, app store rankings, app metadata, app titles and descriptions, app store listings, app visibility, or mobile app marketing on iOS or Android. Supports keyword research and scoring, competitor keyword analysis, metadata optimization, A/B test planning, launch checklists, and tracking ranking changes.
visualizing-data
IncludedBuilds dashboards, reports, and data-driven interfaces requiring charts, graphs, or visual analytics. Provides systematic framework for selecting appropriate visualizations based on data characteristics and analytical purpose. Includes 24+ visualization types organized by purpose (trends, comparisons, distributions, relationships, flows, hierarchies, geospatial), accessibility patterns (WCAG 2.1 AA compliance), colorblind-safe palettes, and performance optimization strategies. Use when creating visualizations, choosing chart types, displaying data graphically, or designing data interfaces.