问题

Please create a valid join mapping between CSV Table A and CSV Table B. Each column in A maps to 0 or 1 columns in B. Return your response as a Python dictionary, formatted as {col_name_in_df_a : col_name_in_df_b}. Please return only the dictionary. \n CSV Table A: id,dept_name,program_name,org_number,measure_name,measure_id,active,priority_measure,budget_book,fiscal_year\n2,Department of Public,Public Works Adminis,4510B,Percent rating exper,5,YES,YES,NO,FY 2012-13\n41,Department of Public,Public Works Adminis,4510B,Percent rating exper,5,YES,YES,NO,FY 2019-20\n4,Department of Public,Public Works Adminis,4510B,Percent rating exper,5,YES,YES,NO,FY 2014-15\n21,Department of Public,Public Works Adminis,4510B,Percent rating exper,5,YES,YES,NO,FY 2015-16\n2,Department of Public,Public Works Adminis,4510B,Percent rating exper,5,YES,YES,NO,FY 2012-13\n3,Department of Public,Public Works Adminis,4510B,Percent rating exper,5,YES,YES,NO,FY 2013-14\n2,Department of Public,Public Works Adminis,4510B,Percent rating exper,5,YES,YES,NO,FY 2012-13\n4,Department of Public,Public Works Adminis,4510B,Percent rating exper,5,YES,YES,NO,FY 2014-15\n41,Department of Public,Public Works Adminis,4510B,Percent rating exper,5,YES,YES,NO,FY 2019-20\n21,Department of Public,Public Works Adminis,4510B,Percent rating exper,5,YES,YES,NO,FY 2015-16\n \n CSV Table B: aWH6IJ5IjF4,hMlFRB3b0OU,6TBG45I7TLk,UCUt++OaxnM,Gu1a6Jx2RSE,0dfsuiTLoSQ,tTar7XACrwc,53NiJOr4DrA,T2n+8bg76ww\nDepartment of Public,NO,2024-04-23T05:00:01.,FY 2015-16,0,4510B,5,YES,No\nDepartment of Public,NO,2024-04-23T05:00:01.,FY 2013-14,1,4510B,5,YES,No\nDepartment of Public,NO,2024-04-23T05:00:01.,FY 2013-14,2,4510B,5,YES,No\nDepartment of Public,NO,2024-04-23T05:00:01.,FY 2013-14,3,4510B,5,YES,No\nDepartment of Public,NO,2024-04-23T05:00:01.,FY 2018-19,4,4510B,5,YES,No\nDepartment of Public,NO,2024-04-23T05:00:01.,FY 2011-12,5,4510B,5,YES,Si\nDepartment of Public,NO,2024-04-23T05:00:01.,FY 2011-12,6,4510B,5,YES,Si\nDepartment of Public,NO,2024-04-23T05:00:01.,FY 2018-19,7,4510B,5,YES,Si\nDepartment of Public,NO,2024-04-23T05:00:01.,FY 2019-20,8,4510B,5,YES,No\nDepartment of Public,NO,2024-04-23T05:00:01.,FY 2013-14,9,4510B,5,YES,No\n \n Output: \n

答案

模型 模型答案 正确答案
金声玉亮2.0 ```python
{'dept_name': 'aWH6IJ5IjF4', 'org_number': '6TBG45I7TLk', 'measure_id': '0dfsuiTLoSQ', 'fiscal_year': 'hMlFRB3b0OU'}
```		 {"dept_name": "aWH6IJ5IjF4", "fiscal_year": "UCUt++OaxnM", "measure_id": "tTar7XACrwc", "priority_measure": "53NiJOr4DrA", "budget_book": "hMlFRB3b0OU", "org_number": "0dfsuiTLoSQ"}
deepseek-r1

{"dept_name": "aWH6IJ5IjF4", "org_number": "0dfsuiTLoSQ", "measure_id": "tTar7XACrwc", "active": "53NiJOr4DrA", "fiscal_year": "UCUt++OaxnM", "budget_book": "T2n+8bg76ww"}		 {"dept_name": "aWH6IJ5IjF4", "fiscal_year": "UCUt++OaxnM", "measure_id": "tTar7XACrwc", "priority_measure": "53NiJOr4DrA", "budget_book": "hMlFRB3b0OU", "org_number": "0dfsuiTLoSQ"}
gpto1 ```python
{'dept_name': 'aWH6IJ5IjF4', 'org_number': '0dfsuiTLoSQ', 'measure_id': 'tTar7XACrwc', 'active': '53NiJOr4DrA', 'fiscal_year': 'UCUt++OaxnM', 'budget_book': 'hMlFRB3b0OU'}
```		 {"dept_name": "aWH6IJ5IjF4", "fiscal_year": "UCUt++OaxnM", "measure_id": "tTar7XACrwc", "priority_measure": "53NiJOr4DrA", "budget_book": "hMlFRB3b0OU", "org_number": "0dfsuiTLoSQ"}
gpt-4o-2024-08-06 ```python
{
"dept_name": "aWH6IJ5IjF4",
"org_number": "0dfsuiTLoSQ",
"measure_id": "tTar7XACrwc",
"fiscal_year": "UCUt++OaxnM"
}
```		 {"dept_name": "aWH6IJ5IjF4", "fiscal_year": "UCUt++OaxnM", "measure_id": "tTar7XACrwc", "priority_measure": "53NiJOr4DrA", "budget_book": "hMlFRB3b0OU", "org_number": "0dfsuiTLoSQ"}
DeepSeek-Coder-V2-Lite-Instruct ```python
{
"id": "aWH6IJ5IjF4",
"dept_name": "Department of Public",
"program_name": "NO",
"org_number": "2024-04-23T05:00:01.",
"measure_name": "FY 2015-16",
"measure_id": "0",
"active": "4510B",
"priority_measure": "5",
"budget_book": "YES",
"fiscal_year": "No"
}
```		 {"dept_name": "aWH6IJ5IjF4", "fiscal_year": "UCUt++OaxnM", "measure_id": "tTar7XACrwc", "priority_measure": "53NiJOr4DrA", "budget_book": "hMlFRB3b0OU", "org_number": "0dfsuiTLoSQ"}
Meta-Llama-3.1-405B-Instruct-Turbo {'dept_name': 'aWH6IJ5IjF4', 'org_number': '6TBG45I7TLk', 'measure_id': '0dfsuiTLoSQ', 'fiscal_year': 'hMlFRB3b0OU'} {"dept_name": "aWH6IJ5IjF4", "fiscal_year": "UCUt++OaxnM", "measure_id": "tTar7XACrwc", "priority_measure": "53NiJOr4DrA", "budget_book": "hMlFRB3b0OU", "org_number": "0dfsuiTLoSQ"}
Meta-Llama-3.1-70B-Instruct-Turbo {'dept_name': 'aWH6IJ5IjF4', 'org_number': '6TBG45I7TLk', 'measure_id': 'tTar7XACrwc', 'fiscal_year': 'UCUt++OaxnM'} {"dept_name": "aWH6IJ5IjF4", "fiscal_year": "UCUt++OaxnM", "measure_id": "tTar7XACrwc", "priority_measure": "53NiJOr4DrA", "budget_book": "hMlFRB3b0OU", "org_number": "0dfsuiTLoSQ"}
Qwen2-72B-Instruct {'id': 'tTar7XACrwc', 'dept_name': 'aWH6IJ5IjF4', 'program_name': '', 'org_number': '6TBG45I7TLk', 'measure_name': '0dfsuiTLoSQ', 'measure_id': 'Gu1a6Jx2RSE', 'active': '', 'priority_measure': 'UCUt++OaxnM', 'budget_book': '', 'fiscal_year': 'hMlFRB3b0OU'}

Note: In this case, not all columns from Table A can be mapped to Table B because some columns in Table B do not have corresponding data in Table A. Specifically, 'program_name' and 'budget_book' cannot be mapped. The 'active' and 'priority_measure' columns in Table A do not map directly to columns in Table B, but rather to values within certain rows of Table B. Therefore, they cannot be included in this mapping.		 {"dept_name": "aWH6IJ5IjF4", "fiscal_year": "UCUt++OaxnM", "measure_id": "tTar7XACrwc", "priority_measure": "53NiJOr4DrA", "budget_book": "hMlFRB3b0OU", "org_number": "0dfsuiTLoSQ"}
baichuan4 Based on the provided CSV tables, it seems that there are no direct one-to-one relationships between the columns in Table A and Table B. However, I can infer some potential mappings based on the data provided. Here's a possible join mapping dictionary:

```python
{
"dept_name": "Department of Public",
"fiscal_year": "FY 2015-16", # This is an example, you may need to adjust based on actual join logic
"org_number": "4510B",
"measure_id": "5"
}
```

Please note that this mapping is based on the assumption that the department name, fiscal year, organization number, and measure ID are common between the two tables. The actual join logic may vary depending on the specific requirements and the context of the data.		 {"dept_name": "aWH6IJ5IjF4", "fiscal_year": "UCUt++OaxnM", "measure_id": "tTar7XACrwc", "priority_measure": "53NiJOr4DrA", "budget_book": "hMlFRB3b0OU", "org_number": "0dfsuiTLoSQ"}
doubao {"dept_name": "Department of Public", "org_number": "4510B", "fiscal_year": "FY 2015-16"} {"dept_name": "aWH6IJ5IjF4", "fiscal_year": "UCUt++OaxnM", "measure_id": "tTar7XACrwc", "priority_measure": "53NiJOr4DrA", "budget_book": "hMlFRB3b0OU", "org_number": "0dfsuiTLoSQ"}
gpto1 ```python
{'dept_name': 'aWH6IJ5IjF4', 'org_number': '0dfsuiTLoSQ', 'measure_id': 'tTar7XACrwc', 'active': '53NiJOr4DrA', 'fiscal_year': 'UCUt++OaxnM', 'budget_book': 'hMlFRB3b0OU'}
```		 {"dept_name": "aWH6IJ5IjF4", "fiscal_year": "UCUt++OaxnM", "measure_id": "tTar7XACrwc", "priority_measure": "53NiJOr4DrA", "budget_book": "hMlFRB3b0OU", "org_number": "0dfsuiTLoSQ"}
kimi ```python
{'id': 'aWH6IJ5IjF4', 'dept_name': 'Department of Public', 'org_number': '4510B', 'measure_id': '5', 'fiscal_year': 'FY 2015-16'}
```		 {"dept_name": "aWH6IJ5IjF4", "fiscal_year": "UCUt++OaxnM", "measure_id": "tTar7XACrwc", "priority_measure": "53NiJOr4DrA", "budget_book": "hMlFRB3b0OU", "org_number": "0dfsuiTLoSQ"}
minimax ```python
{
"dept_name": "Department of Public",
"org_number": "4510B",
"measure_id": "5",
"active": "YES",
"fiscal_year": "FY 2015-16"
}
```		 {"dept_name": "aWH6IJ5IjF4", "fiscal_year": "UCUt++OaxnM", "measure_id": "tTar7XACrwc", "priority_measure": "53NiJOr4DrA", "budget_book": "hMlFRB3b0OU", "org_number": "0dfsuiTLoSQ"}
wenxinyiyan ```python
{
'dept_name': 'aWH6IJ5IjF4',
'fiscal_year': 'T2n+8bg76ww',
'org_number': 'Gu1a6Jx2RSE',
'measure_id': '0dfsuiTLoSQ',
'active': 'tTar7XACrwc'
}
```		 {"dept_name": "aWH6IJ5IjF4", "fiscal_year": "UCUt++OaxnM", "measure_id": "tTar7XACrwc", "priority_measure": "53NiJOr4DrA", "budget_book": "hMlFRB3b0OU", "org_number": "0dfsuiTLoSQ"}
zhipu ```python
{
"dept_name": "aWH6IJ5IjF4",
"active": "tTar7XACrwc",
"measure_id": "0dfsuiTLoSQ",
"org_number": "Gu1a6Jx2RSE",
"fiscal_year": "T2n+8bg76ww"
}
```		 {"dept_name": "aWH6IJ5IjF4", "fiscal_year": "UCUt++OaxnM", "measure_id": "tTar7XACrwc", "priority_measure": "53NiJOr4DrA", "budget_book": "hMlFRB3b0OU", "org_number": "0dfsuiTLoSQ"}
deepseek-v3 {'dept_name': 'Department of Public', 'org_number': '4510B', 'measure_id': '5', 'active': 'YES', 'fiscal_year': 'FY 2015-16'} {"dept_name": "aWH6IJ5IjF4", "fiscal_year": "UCUt++OaxnM", "measure_id": "tTar7XACrwc", "priority_measure": "53NiJOr4DrA", "budget_book": "hMlFRB3b0OU", "org_number": "0dfsuiTLoSQ"}