feat: make missing ratio warning threshold configurable#9
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codeMaestro78 merged 3 commits intomasterfrom Jan 20, 2026
Merged
feat: make missing ratio warning threshold configurable#9codeMaestro78 merged 3 commits intomasterfrom
codeMaestro78 merged 3 commits intomasterfrom
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codeMaestro78
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Jan 20, 2026
codeMaestro78
commented
- Add MISSING_RATIO_WARNING_THRESHOLD constant (default 0.5)
- Add missing_ratio_warning_threshold parameter to DataAnalyzer constructor
- Replace magic number 0.5 with configurable parameter
- Make warning message dynamic to show actual threshold percentage
- Fix linting issues: line length, variable naming, and formatting
- Add MISSING_RATIO_WARNING_THRESHOLD constant (default 0.5) - Add missing_ratio_warning_threshold parameter to DataAnalyzer constructor - Replace magic number 0.5 with configurable parameter - Make warning message dynamic to show actual threshold percentage - Fix linting issues: line length, variable naming, and formatting
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>> >> - Add MISSING_RATIO_WARNING_THRESHOLD constant (default 0.5) >> - Add missing_ratio_warning_threshold parameter to DataAnalyzer constructor >> - Replace magic number 0.5 with configurable parameter >> - Make warning message dynamic to show actual threshold percentage >> - Fix linting issues: line length, variable naming, and formatting
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Pull request overview
This pull request adds a configurable threshold for missing ratio warnings while also introducing several other changes that extend beyond the stated scope. The main feature allows users to customize when warnings are generated for columns with high missing value ratios (default 50%).
Changes:
- Added configurable missing_ratio_warning_threshold parameter to DataAnalyzer constructor
- Added comprehensive input validation for the analyze() method
- Changed class_distribution structure from dict to list format (breaking API change)
- Enhanced docstrings for multiple methods
- Modified categorical type inference logic for numeric columns
- Simplified null/NaN detection using pandas.isna()
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The issue has been resolved. |
- Document that class_distribution is a list of dicts with label/count/ratio keys - Address API consistency concerns by clearly specifying the data structure - No functional changes, only documentation improvement
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