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: longitude,latitude,start_date,end_date,source,horizon_lower,horizon_upper,aluminium_extractable,boron_extractable,calcium_extractable\n35.50963,-13.41183,01/01/2008,31/12/2018,afsis_spectral,20,0,920.734,,1042.361\n34.22425,-11.65423,01/01/2008,31/12/2018,afsis_spectral,20,0,1339.417,,2882.606\n31.81264,-8.63489,01/01/2008,31/12/2018,afsis_spectral,20,0,668.024,,360.559\n36.487,-6.07697,01/01/2008,31/12/2018,afsis_spectral,20,0,677.402,,811.649\n35.46519,-7.72076,01/01/2008,31/12/2018,afsis_spectral,50,20,506.082,,395.229\n34.26721,-4.26873,01/01/2008,31/12/2018,afsis_spectral,50,20,849.618,,1295.836\n32.34213,-3.17727,01/01/2008,31/12/2018,afsis_spectral,50,20,844.028,,999.168\n31.06515,-6.21487,01/01/2008,31/12/2018,afsis_spectral,50,20,500.886,,292.74\n36.00592,-7.66049,01/01/2008,31/12/2018,afsis_spectral,50,20,795.988,,452.385\n-2.38906,7.39374,01/01/2008,31/12/2018,afsis_spectral,50,20,523.359,,2391.241\n \n CSV Table B: MkLAdzp+esw,+I7cBfMYFoQ,SeflMNbyB9c,6oYoa6ynUjM,+ppuhrWxZm0,UHgQMYIJ9TU,GlQankwBpC4,lGwUkVW6H7g\nafsis_spectral,15.6466,Weak,708.277,0,,0,20\nafsis_spectral,15.6466,Weak,682.892,1,,0,20\nafsis_spectral,15.6466,Weak,1036.355,2,,20,50\nafsis_spectral,15.6466,New,1264.034,3,,20,50\nafsis_spectral,15.6466,Weak,597.63,4,,20,50\nafsis_spectral,15.6466,New,772.719,5,,20,50\nafsis_spectral,15.6466,New,588.3375,6,,0,20\nafsis_spectral,15.6466,New,913.833,7,,20,50\nafsis_spectral,15.6466,Weak,778.952,8,,20,50\nafsis_spectral,15.6466,New,581.775,9,,20,50\nafsis_spectral,15.6466,New,518.874,10,,0,20\n \n Output: \n

答案

模型 模型答案 正确答案
金声玉亮2.0 ```python
{
"source": "MkLAdzp+esw",
"horizon_lower": "UHgQMYIJ9TU",
"horizon_upper": "GlQankwBpC4",
"aluminium_extractable": "6oYoa6ynUjM",
"boron_extractable": "SeflMNbyB9c",
"calcium_extractable": "lGwUkVW6H7g"
}
```		 {"horizon_upper": "GlQankwBpC4", "horizon_lower": "lGwUkVW6H7g", "aluminium_extractable": "6oYoa6ynUjM", "boron_extractable": "UHgQMYIJ9TU", "source": "MkLAdzp+esw"}
deepseek-r1

{'source': 'MkLAdzp+esw', 'horizon_lower': 'lGwUkVW6H7g', 'horizon_upper': 'GlQankwBpC4', 'aluminium_extractable': '6oYoa6ynUjM'}		 {"horizon_upper": "GlQankwBpC4", "horizon_lower": "lGwUkVW6H7g", "aluminium_extractable": "6oYoa6ynUjM", "boron_extractable": "UHgQMYIJ9TU", "source": "MkLAdzp+esw"}
gpto1 ```python
{
'longitude': None,
'latitude': None,
'start_date': None,
'end_date': None,
'source': 'MkLAdzp+esw',
'horizon_lower': 'lGwUkVW6H7g',
'horizon_upper': 'GlQankwBpC4',
'aluminium_extractable': '6oYoa6ynUjM',
'boron_extractable': None,
'calcium_extractable': None
}
```		 {"horizon_upper": "GlQankwBpC4", "horizon_lower": "lGwUkVW6H7g", "aluminium_extractable": "6oYoa6ynUjM", "boron_extractable": "UHgQMYIJ9TU", "source": "MkLAdzp+esw"}
gpt-4o-2024-08-06 ```python
{
"longitude": None,
"latitude": None,
"start_date": None,
"end_date": None,
"source": "MkLAdzp+esw",
"horizon_lower": "lGwUkVW6H7g",
"horizon_upper": "UHgQMYIJ9TU",
"aluminium_extractable": None,
"boron_extractable": None,
"calcium_extractable": None
}
```		 {"horizon_upper": "GlQankwBpC4", "horizon_lower": "lGwUkVW6H7g", "aluminium_extractable": "6oYoa6ynUjM", "boron_extractable": "UHgQMYIJ9TU", "source": "MkLAdzp+esw"}
DeepSeek-Coder-V2-Lite-Instruct ```python
{
"longitude": "MkLAdzp+esw",
"latitude": "+I7cBfMYFoQ",
"start_date": "SeflMNbyB9c",
"end_date": "6oYoa6ynUjM",
"source": "+ppuhrWxZm0",
"horizon_lower": "UHgQMYIJ9TU",
"horizon_upper": "GlQankwBpC4",
"aluminium_extractable": "lGwUkVW6H7g"
}
```		 {"horizon_upper": "GlQankwBpC4", "horizon_lower": "lGwUkVW6H7g", "aluminium_extractable": "6oYoa6ynUjM", "boron_extractable": "UHgQMYIJ9TU", "source": "MkLAdzp+esw"}
Meta-Llama-3.1-405B-Instruct-Turbo {'source': 'MkLAdzp+esw', 'horizon_lower': 'GlQankwBpC4', 'horizon_upper': 'lGwUkVW6H7g'} {"horizon_upper": "GlQankwBpC4", "horizon_lower": "lGwUkVW6H7g", "aluminium_extractable": "6oYoa6ynUjM", "boron_extractable": "UHgQMYIJ9TU", "source": "MkLAdzp+esw"}
Meta-Llama-3.1-70B-Instruct-Turbo {'source': '+I7cBfMYFoQ', 'horizon_lower': 'UHgQMYIJ9TU', 'horizon_upper': 'GlQankwBpC4'} {"horizon_upper": "GlQankwBpC4", "horizon_lower": "lGwUkVW6H7g", "aluminium_extractable": "6oYoa6ynUjM", "boron_extractable": "UHgQMYIJ9TU", "source": "MkLAdzp+esw"}
Qwen2-72B-Instruct {'source': 'source', 'horizon_lower': '+I7cBfMYFoQ', 'horizon_upper': 'SeflMNbyB9c'} {"horizon_upper": "GlQankwBpC4", "horizon_lower": "lGwUkVW6H7g", "aluminium_extractable": "6oYoa6ynUjM", "boron_extractable": "UHgQMYIJ9TU", "source": "MkLAdzp+esw"}
baichuan4 Based on the provided CSV tables, it seems that there is no direct one-to-one mapping between the columns of Table A and Table B. However, I can infer some potential relationships based on the data provided.

Here's a possible mapping based on the assumption that the 'source' column in Table A corresponds to the first column in Table B, which contains the same value 'afsis_spectral'. Additionally, I'm assuming that the 'horizon_lower' and 'horizon_upper' columns in Table A might correspond to the last two columns in Table B, which contain numeric values that could potentially match the lower and upper bounds.

Please note that this mapping is speculative and based on the limited information provided. A more accurate mapping would require additional context or specific instructions on how the columns should be matched.

```python
{
'source': 'MkLAdzp+esw',
'horizon_lower': 'GlQankwBpC4',
'horizon_upper': 'lGwUkVW6H7g'
}
```		 {"horizon_upper": "GlQankwBpC4", "horizon_lower": "lGwUkVW6H7g", "aluminium_extractable": "6oYoa6ynUjM", "boron_extractable": "UHgQMYIJ9TU", "source": "MkLAdzp+esw"}
doubao {"source": "MkLAdzp+esw"} {"horizon_upper": "GlQankwBpC4", "horizon_lower": "lGwUkVW6H7g", "aluminium_extractable": "6oYoa6ynUjM", "boron_extractable": "UHgQMYIJ9TU", "source": "MkLAdzp+esw"}
gpto1 ```python
{
'longitude': None,
'latitude': None,
'start_date': None,
'end_date': None,
'source': 'MkLAdzp+esw',
'horizon_lower': 'lGwUkVW6H7g',
'horizon_upper': 'GlQankwBpC4',
'aluminium_extractable': '6oYoa6ynUjM',
'boron_extractable': None,
'calcium_extractable': None
}
```		 {"horizon_upper": "GlQankwBpC4", "horizon_lower": "lGwUkVW6H7g", "aluminium_extractable": "6oYoa6ynUjM", "boron_extractable": "UHgQMYIJ9TU", "source": "MkLAdzp+esw"}
kimi {'source': 'MkLAdzp+esw', 'horizon_lower': 'SeflMNbyB9c', 'horizon_upper': '6oYoa6ynUjM'} {"horizon_upper": "GlQankwBpC4", "horizon_lower": "lGwUkVW6H7g", "aluminium_extractable": "6oYoa6ynUjM", "boron_extractable": "UHgQMYIJ9TU", "source": "MkLAdzp+esw"}
minimax ```python
{
"longitude": "",
"latitude": "",
"start_date": "",
"end_date": "",
"source": "source",
"horizon_lower": "",
"horizon_upper": "",
"aluminium_extractable": "",
"boron_extractable": "",
"calcium_extractable": ""
}
```		 {"horizon_upper": "GlQankwBpC4", "horizon_lower": "lGwUkVW6H7g", "aluminium_extractable": "6oYoa6ynUjM", "boron_extractable": "UHgQMYIJ9TU", "source": "MkLAdzp+esw"}
wenxinyiyan ```python
{'source': '+I7cBfMYFoQ'}
```		 {"horizon_upper": "GlQankwBpC4", "horizon_lower": "lGwUkVW6H7g", "aluminium_extractable": "6oYoa6ynUjM", "boron_extractable": "UHgQMYIJ9TU", "source": "MkLAdzp+esw"}
zhipu ```python
{
"source": "MkLAdzp+esw",
"horizon_lower": "GlQankwBpC4",
"horizon_upper": "lGwUkVW6H7g"
}
```		 {"horizon_upper": "GlQankwBpC4", "horizon_lower": "lGwUkVW6H7g", "aluminium_extractable": "6oYoa6ynUjM", "boron_extractable": "UHgQMYIJ9TU", "source": "MkLAdzp+esw"}
deepseek-v3 {'source': 'MkLAdzp+esw', 'aluminium_extractable': '+I7cBfMYFoQ', 'horizon_lower': 'lGwUkVW6H7g', 'horizon_upper': 'UHgQMYIJ9TU'} {"horizon_upper": "GlQankwBpC4", "horizon_lower": "lGwUkVW6H7g", "aluminium_extractable": "6oYoa6ynUjM", "boron_extractable": "UHgQMYIJ9TU", "source": "MkLAdzp+esw"}