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feat(dc/tool-c): Add missing value imputation feature with 6 methods and MICE

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Major features:
1. Missing value imputation (6 simple methods + MICE):
   - Mean/Median/Mode/Constant imputation
   - Forward fill (ffill) and Backward fill (bfill) for time series
   - MICE multivariate imputation (in progress, shape issue to fix)

2. Auto precision detection:
   - Automatically match decimal places of original data
   - Prevent false precision (e.g. 13.57 instead of 13.566716417910449)

3. Categorical variable detection:
   - Auto-detect and skip categorical columns in MICE
   - Show warnings for unsuitable columns
   - Suggest mode imputation for categorical data

4. UI improvements:
   - Rename button: "Delete Missing" to "Missing Value Handling"
   - Remove standalone "Dedup" and "MICE" buttons
   - 3-tab dialog: Delete / Fill / Advanced Fill
   - Display column statistics and recommended methods
   - Extended warning messages (8 seconds for skipped columns)

5. Bug fixes:
   - Fix sessionService.updateSessionData -> saveProcessedData
   - Fix OperationResult interface (add message and stats)
   - Fix Toolbar button labels and removal

Modified files:
Python: operations/fillna.py (new, 556 lines), main.py (3 new endpoints)
Backend: QuickActionService.ts, QuickActionController.ts, routes/index.ts
Frontend: MissingValueDialog.tsx (new, 437 lines), Toolbar.tsx, index.tsx
Tests: test_fillna_operations.py (774 lines), test scripts and docs
Docs: 5 documentation files updated

Known issues:
- MICE imputation has DataFrame shape mismatch issue (under debugging)
- Workaround: Use 6 simple imputation methods first

Status: Development complete, MICE debugging in progress
Lines added: ~2000 lines across 3 tiers
This commit is contained in:
HaHafeng
2025-12-10 13:06:00 +08:00
parent f4f1d09837
commit 74cf346453
102 changed files with 3806 additions and 181 deletions
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commit_fillna_feature.txt Normal file
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feat(dc/tool-c): Add missing value imputation feature with 6 methods and MICE
Major features:
1. Missing value imputation (6 simple methods + MICE):
- Mean/Median/Mode/Constant imputation
- Forward fill (ffill) and Backward fill (bfill) for time series
- MICE multivariate imputation (in progress, shape issue to fix)
2. Auto precision detection:
- Automatically match decimal places of original data
- Prevent false precision (e.g. 13.57 instead of 13.566716417910449)
3. Categorical variable detection:
- Auto-detect and skip categorical columns in MICE
- Show warnings for unsuitable columns
- Suggest mode imputation for categorical data
4. UI improvements:
- Rename button: "Delete Missing" to "Missing Value Handling"
- Remove standalone "Dedup" and "MICE" buttons
- 3-tab dialog: Delete / Fill / Advanced Fill
- Display column statistics and recommended methods
- Extended warning messages (8 seconds for skipped columns)
5. Bug fixes:
- Fix sessionService.updateSessionData -> saveProcessedData
- Fix OperationResult interface (add message and stats)
- Fix Toolbar button labels and removal
Modified files:
Python: operations/fillna.py (new, 556 lines), main.py (3 new endpoints)
Backend: QuickActionService.ts, QuickActionController.ts, routes/index.ts
Frontend: MissingValueDialog.tsx (new, 437 lines), Toolbar.tsx, index.tsx
Tests: test_fillna_operations.py (774 lines), test scripts and docs
Docs: 5 documentation files updated
Known issues:
- MICE imputation has DataFrame shape mismatch issue (under debugging)
- Workaround: Use 6 simple imputation methods first
Status: Development complete, MICE debugging in progress
Lines added: ~2000 lines across 3 tiers