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: DeviceTimeStamp,WL1,WL2,WL3,VAL1,VAL2,VAL3,RVAL1,RVAL2,RVAL3\n2019-07-25T08:01,15.5,10.9,16.3,15.9,11.3,17.3,3.7,2.7,0.0057\n2020-03-04T15:00,30.3,13.1,25.7,30.7,14.0,28.5,4.6,4.8,0.0122\n2020-03-24T21:00,15.2,9.7,21.3,15.3,10.1,21.7,2.1,2.7,0.004\n2019-10-30T04:10,13.8,8.0,15.7,13.8,8.2,16.1,1.0,1.6,0.0034\n2019-10-30T09:15,16.7,15.8,15.9,17.0,16.1,17.0,3.1,3.1,0.006\n2020-02-08T06:45,8.3,4.0,9.8,8.3,4.4,10.1,0.5,1.7,0.0025\n2019-12-08T17:20,14.4,11.9,23.1,14.4,12.4,23.5,0.2,3.3,0.0046\n2019-08-14T18:00,27.4,33.8,34.8,27.5,33.9,35.4,0.2,3.6,0.0065\n2019-09-10T19:45,34.0,40.3,39.5,34.2,40.3,39.7,3.9,1.6,0.0033\n2019-09-13T21:45,20.1,24.4,21.3,20.3,24.5,21.4,3.2,1.8,0.0023\n2019-11-24T16:45,13.2,11.0,15.5,13.2,11.4,15.9,0.4,3.1,0.0037\n2020-02-27T16:30,19.3,12.3,22.4,20.0,12.7,22.5,5.3,2.9,0.0021\n2019-08-28T10:00,14.6,14.3,22.6,14.6,15.1,23.2,0.3,4.8,0.005\n2019-08-18T02:45,11.0,8.4,14.8,11.0,8.6,15.1,0.0,1.7,0.0027\n2020-04-10T20:00,20.8,13.2,22.4,20.9,13.3,22.7,2.1,1.4,0.0036\n2019-08-18T03:55,8.4,8.2,13.5,8.4,8.5,13.6,1.0,1.9,0.002\n2019-08-18T10:30,15.9,11.1,14.4,16.0,11.3,15.0,1.0,1.8,0.0039\n2019-08-29T06:45,13.6,9.1,17.3,13.7,9.5,17.7,1.0,2.8,0.0036\n2019-10-08T04:30,15.4,11.3,25.3,15.7,11.7,25.4,2.8,3.1,0.0008\n \n CSV Table B: mlTxGdesaBg,6kQGdj2iXsU,hQKNy+86p+0,2xE2qVXr7UM,J92S/IDpPZA,eshSFvEUsMY,v3NEVV2Owbs\nNo,1.8,31.1,33.6,33.6,4.4,0\nNo,1.8,33.2,19.6,19.5,2.7,1\nNo,2.6,24.5,21.0,20.9,2.7,2\nNo,1.4,18.0,10.2,10.1,1.4,3\nNo,0.0,0.0,0.0,0.0,0.0,4\nSi,1.8,17.9,16.6,16.5,1.6,5\nSi,1.2,14.6,7.7,7.6,1.2,6\nSi,0.0,0.0,0.0,0.0,0.0,7\nNo,2.0,12.5,7.8,7.5,0.9,8\nNo,1.6,35.5,31.6,31.6,2.0,9\nSi,2.0,27.2,20.7,20.6,1.4,10\nNo,3.8,36.4,35.1,34.9,2.0,11\nSi,1.4,17.5,11.1,11.0,2.0,12\nSi,3.2,35.0,38.9,38.8,1.4,13\nNo,4.0,17.6,12.9,12.3,1.5,14\nNo,3.1,15.7,13.6,13.2,0.0,15\nNo,4.8,32.1,23.6,23.1,5.6,16\nNo,1.2,7.5,5.8,5.6,0.7,17\nNo,2.1,11.2,9.3,9.1,0.0,18\nNo,2.3,13.0,7.8,7.5,1.8,19\n \n Output: \n

答案

模型 模型答案 正确答案
金声玉亮2.0 ```python
{'VAL1': 'hQKNy+86p+0', 'VAL2': '2xE2qVXr7UM', 'VAL3': 'J92S/IDpPZA', 'RVAL1': 'eshSFvEUsMY', 'RVAL2': 'v3NEVV2Owbs'}
```		 {"RVAL1": "eshSFvEUsMY", "RVAL2": "6kQGdj2iXsU", "WL2": "J92S/IDpPZA", "VAL2": "2xE2qVXr7UM", "VAL1": "hQKNy+86p+0"}
deepseek-r1

{"VAL1": "hQKNy+86p+0", "VAL2": "2xE2qVXr7UM", "VAL3": "J92S/IDpPZA", "RVAL1": "eshSFvEUsMY", "RVAL2": "6kQGdj2iXsU"}		 {"RVAL1": "eshSFvEUsMY", "RVAL2": "6kQGdj2iXsU", "WL2": "J92S/IDpPZA", "VAL2": "2xE2qVXr7UM", "VAL1": "hQKNy+86p+0"}
gpto1 {} {"RVAL1": "eshSFvEUsMY", "RVAL2": "6kQGdj2iXsU", "WL2": "J92S/IDpPZA", "VAL2": "2xE2qVXr7UM", "VAL1": "hQKNy+86p+0"}
gpt-4o-2024-08-06 ```python
{
"DeviceTimeStamp": None,
"WL1": None,
"WL2": None,
"WL3": None,
"VAL1": None,
"VAL2": None,
"VAL3": None,
"RVAL1": None,
"RVAL2": None,
"RVAL3": None
}
```		 {"RVAL1": "eshSFvEUsMY", "RVAL2": "6kQGdj2iXsU", "WL2": "J92S/IDpPZA", "VAL2": "2xE2qVXr7UM", "VAL1": "hQKNy+86p+0"}
DeepSeek-Coder-V2-Lite-Instruct ```python
{
"DeviceTimeStamp": "mlTxGdesaBg",
"WL1": "6kQGdj2iXsU",
"WL2": "hQKNy+86p+0",
"WL3": "2xE2qVXr7UM",
"VAL1": "J92S/IDpPZA",
"VAL2": "eshSFvEUsMY",
"VAL3": "v3NEVV2Owbs"
}
```		 {"RVAL1": "eshSFvEUsMY", "RVAL2": "6kQGdj2iXsU", "WL2": "J92S/IDpPZA", "VAL2": "2xE2qVXr7UM", "VAL1": "hQKNy+86p+0"}
Meta-Llama-3.1-405B-Instruct-Turbo {'VAL1': 'hQKNy+86p+0', 'VAL2': '2xE2qVXr7UM', 'VAL3': 'J92S/IDpPZA', 'RVAL1': 'eshSFvEUsMY', 'RVAL2': 'v3NEVV2Owbs'} {"RVAL1": "eshSFvEUsMY", "RVAL2": "6kQGdj2iXsU", "WL2": "J92S/IDpPZA", "VAL2": "2xE2qVXr7UM", "VAL1": "hQKNy+86p+0"}
Meta-Llama-3.1-70B-Instruct-Turbo {'WL1': '2xE2qVXr7UM', 'WL2': 'hQKNy+86p+0', 'WL3': '6kQGdj2iXsU'} {"RVAL1": "eshSFvEUsMY", "RVAL2": "6kQGdj2iXsU", "WL2": "J92S/IDpPZA", "VAL2": "2xE2qVXr7UM", "VAL1": "hQKNy+86p+0"}
Qwen2-72B-Instruct ```python
{}
```

Based on the provided information, there are no common columns between CSV Table A and CSV Table B that can be used for a join operation. Therefore, the output is an empty dictionary. However, if you intended to map specific columns or if there's additional context that could enable a join, please provide further details.		 {"RVAL1": "eshSFvEUsMY", "RVAL2": "6kQGdj2iXsU", "WL2": "J92S/IDpPZA", "VAL2": "2xE2qVXr7UM", "VAL1": "hQKNy+86p+0"}
baichuan4 {
'DeviceTimeStamp': 'mlTxGdesaBg',
'WL1': '6kQGdj2iXsU',
'WL2': 'hQKNy+86p+0',
'WL3': '2xE2qVXr7UM',
'VAL1': 'J92S/IDpPZA',
'VAL2': 'eshSFvEUsMY',
'VAL3': 'v3NEVV2Owbs'
}		 {"RVAL1": "eshSFvEUsMY", "RVAL2": "6kQGdj2iXsU", "WL2": "J92S/IDpPZA", "VAL2": "2xE2qVXr7UM", "VAL1": "hQKNy+86p+0"}
doubao {DeviceTimeStamp: mlTxGdesaBg} {"RVAL1": "eshSFvEUsMY", "RVAL2": "6kQGdj2iXsU", "WL2": "J92S/IDpPZA", "VAL2": "2xE2qVXr7UM", "VAL1": "hQKNy+86p+0"}
gpto1 {} {"RVAL1": "eshSFvEUsMY", "RVAL2": "6kQGdj2iXsU", "WL2": "J92S/IDpPZA", "VAL2": "2xE2qVXr7UM", "VAL1": "hQKNy+86p+0"}
kimi {'DeviceTimeStamp': 'mlTxGdesaBg', 'WL1': '6kQGdj2iXsU', 'WL2': 'hQKNy+86p+0', 'WL3': '2xE2qVXr7UM', 'VAL1': 'J92S/IDpPZA', 'VAL2': 'eshSFvEUsMY', 'VAL3': 'v3NEVV2Owbs', 'RVAL1': None, 'RVAL2': None, 'RVAL3': None} {"RVAL1": "eshSFvEUsMY", "RVAL2": "6kQGdj2iXsU", "WL2": "J92S/IDpPZA", "VAL2": "2xE2qVXr7UM", "VAL1": "hQKNy+86p+0"}
minimax ```python
{
"DeviceTimeStamp": None,
"WL1": "6kQGdj2iXsU",
"WL2": "hQKNy+86p+0",
"WL3": "2xE2qVXr7UM",
"VAL1": "J92S/IDpPZA",
"VAL2": "eshSFvEUsMY",
"VAL3": "v3NEVV2Owbs",
"RVAL1": None,
"RVAL2": None,
"RVAL3": None
}
```		 {"RVAL1": "eshSFvEUsMY", "RVAL2": "6kQGdj2iXsU", "WL2": "J92S/IDpPZA", "VAL2": "2xE2qVXr7UM", "VAL1": "hQKNy+86p+0"}
wenxinyiyan ```python
{'DeviceTimeStamp': 'mlTxGdesaBg', 'WL1': '6kQGdj2iXsU', 'WL2': 'hQKNy+86p+0', 'WL3': '2xE2qVXr7UM', 'VAL1': 'J92S/IDpPZA', 'VAL2': 'eshSFvEUsMY', 'VAL3': 'v3NEVV2Owbs'}
```		 {"RVAL1": "eshSFvEUsMY", "RVAL2": "6kQGdj2iXsU", "WL2": "J92S/IDpPZA", "VAL2": "2xE2qVXr7UM", "VAL1": "hQKNy+86p+0"}
zhipu ```python
{
"DeviceTimeStamp": None,
"WL1": "6kQGdj2iXsU",
"WL2": "hQKNy+86p+0",
"WL3": "2xE2qVXr7UM",
"VAL1": "J92S/IDpPZA",
"VAL2": "eshSFvEUsMY",
"VAL3": "v3NEVV2Owbs",
"RVAL1": None,
"RVAL2": None,
"RVAL3": None
}
```		 {"RVAL1": "eshSFvEUsMY", "RVAL2": "6kQGdj2iXsU", "WL2": "J92S/IDpPZA", "VAL2": "2xE2qVXr7UM", "VAL1": "hQKNy+86p+0"}
deepseek-v3 {"DeviceTimeStamp": "mlTxGdesaBg", "WL1": "6kQGdj2iXsU", "WL2": "hQKNy+86p+0", "WL3": "2xE2qVXr7UM", "VAL1": "J92S/IDpPZA", "VAL2": "eshSFvEUsMY", "VAL3": "v3NEVV2Owbs"} {"RVAL1": "eshSFvEUsMY", "RVAL2": "6kQGdj2iXsU", "WL2": "J92S/IDpPZA", "VAL2": "2xE2qVXr7UM", "VAL1": "hQKNy+86p+0"}