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    excel-analyzer

    by Ikerg

    Professional Excel auditor for multi-sheet workbooks featuring structural trap detection and Pandas fix generation.

    Updated Jun 2026
    Security scanned

    $5

    · or 25 credits

    30-day refund guarantee

    Secure checkout via Stripe

    Included in download

    • Detect hidden sheets and merged cell ranges that break data pipelines
    • Map cross-sheet relationships with validated 1-to-many join snippets
    • terminal, file_write, file_read automation included
    • Instant install

    Sample input

    Analyze sales_data_2024.xlsx, check for data quality issues across all sheets, and suggest how to join the customer and order data.

    Sample output

    Audit Summary

    • Warnings: 1 Hidden Sheet ('Dev_Backlog'), Merged Cells in 'Q3_Report' (A1:C1).
    • Join Suggestion: 'Orders' & 'Customers' share cust_id (1-to-many).
    • Validation: 98% overlap. 12 orphaned orders found.
    • Fix: df.merge(customers, on='cust_id', validate='m:1')

    About This Skill

    What it does

    Excel Analyzer is a developer-centric tool designed to profile and audit complex multi-sheet .xlsx workbooks. Unlike basic data profilers, it performs a structural deep-dive to detect "spreadsheet traps" like hidden sheets containing sensitive data or merged cells that silently break data ingestion. It provides automated data quality findings with ready-to-use Pandas fix snippets.

    Why use this skill

    Manually auditing a large Excel file is error-prone. This skill automates the drudgery by identifying column relationships across sheets (1-to-1, 1-to-many), detecting schema inconsistencies, and generating interactive Plotly HTML reports. It is significantly more reliable than manual prompting because it uses deterministic analysis to calculate exact null counts, outlier thresholds, and primary key candidates before providing reasoning.

    Supported Tools

    • Pandas & Openpyxl: Robust data manipulation and Excel engine.
    • Plotly: Interactive data visualization and reporting.
    • Automated Join Logic: Proposes validated merge snippets for cross-sheet analysis.

    Output

    You receive a comprehensive audit including structural warnings, per-sheet data statistics (dtypes, uniques, outliers), severity-ranked quality issues, and runnable Python code to fix identified data debt.

    Use Cases

    • Detect hidden sheets and merged cell ranges that break data pipelines
    • Map cross-sheet relationships with validated 1-to-many join snippets
    • Generate interactive Plotly HTML reports for stakeholder data reviews
    • Identify data debt like numeric-text pollution and date-format inconsistencies

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    Security Scanned

    Passed automated security review

    Permissions

    Terminal / Shell
    Write Files
    Read Files

    File Scopes

    scripts/**

    Tags

    excel
    data-analysis
    pandas
    data-cleaning
    python

    Creator

    Ikerg

    Lead Data Engineer with 11 years of experience designing and delivering scalable data platforms across Databricks, AWS, and Azure ecosystems. Proven track record of building high-performance data solutions for large-scale, data-intensive organizations in industries including healthcare and robotics. Extensive experience working in highly regulated environments, managing complex data pipelines and large volumes of structured and unstructured data.

    Frequently Asked Questions

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