HaHafeng
74cf346453
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
54 lines
1.3 KiB
Python
54 lines
1.3 KiB
Python
"""简单的代码执行测试"""
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import requests
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import json
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# 测试数据
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test_data = [
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{"patient_id": "P001", "age": 25, "gender": "男"},
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{"patient_id": "P002", "age": 65, "gender": "女"},
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{"patient_id": "P003", "age": 45, "gender": "男"},
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]
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# 测试代码
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test_code = """
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df['age_group'] = df['age'].apply(lambda x: '老年' if x > 60 else '非老年')
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print(f"处理完成，共 {len(df)} 行")
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"""
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print("=" * 60)
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print("测试: Pandas代码执行")
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print("=" * 60)
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try:
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response = requests.post(
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"http://localhost:8000/api/dc/execute",
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json={"data": test_data, "code": test_code},
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timeout=10
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)
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print(f"\n状态码: {response.status_code}")
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result = response.json()
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print(json.dumps(result, indent=2, ensure_ascii=False))
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if result.get("success"):
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print("\n✅ 代码执行成功！")
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print(f"结果数据: {len(result.get('result_data', []))} 行")
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print(f"执行时间: {result.get('execution_time', 0):.3f}秒")
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print(f"\n打印输出:\n{result.get('output', '')}")
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print(f"\n结果数据示例:")
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for row in result.get('result_data', [])[:3]:
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print(f" {row}")
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else:
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print(f"\n❌ 代码执行失败: {result.get('error')}")
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except Exception as e:
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print(f"\n❌ 测试异常: {str(e)}")
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