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Find missing-value counts and percentages by CSV column, then optionally fill values or drop affected rows after explicit review.
Your selected file is processed locally in your browser. ScholarTool does not upload the file to a third-party calculation or data-analysis API.
Selecting a file only records file details. Click Load CSV to parse and preview input.
Drag and drop is optional; the normal file chooser is the primary accessible control.
Results, visuals, downloads, and copy actions remain hidden until Analyze Missing Values succeeds.
Load a CSV file to enable processing options.
Missing-value analysis identifies absent or placeholder entries and measures how they are distributed across rows and columns. Empty strings, whitespace, NA-style tokens, and domain-specific codes may need different treatment, and simple filling or row deletion can change the meaning and bias of a dataset.
Missing Value Analyzer applies this concept to its defined inputs and workflow. It separates CSV loading from missing-value processing.
After the user explicitly loads local data, the tool applies the selected workflow to local CSV file and returns missing summary, missing distribution visual, filled CSV, and filtered CSV. Input structure, labels, missing values, and selected options must match the intended workflow. The output should be compared with the source file and the assumptions of the intended analysis before any transformation is accepted. Mean and median filling are simple imputation helpers, not a full missing-data modeling method.
The Missing Value Analyzer separates CSV loading from missing-value processing. After loading, you choose missing tokens, selected columns, and an optional fill or drop strategy before clicking Analyze Missing Values.
Configured missing tokens are matched before processing. Counts and percentages are calculated per selected column. Fill strategies are explicit and do not run automatically when options change.
Load a clinical or sensor CSV, select numeric measurement columns, review missing percentages, then export a median-filled copy only after deciding that median filling is appropriate.
This tool is intended for educational, estimation, and preliminary data-preparation use. Always verify critical data-processing decisions with validated workflows and qualified professional judgment before using results in real research, compliance, or engineering decisions.
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