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28 lines
1.2 KiB
Python
28 lines
1.2 KiB
Python
import pandas as pd
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# 读取特征
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features = pd.read_excel('feature.xlsx')
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# 计算权重数字化值
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features['权重数字化值'] = features['强迫症状数字化'] * 0.135 + features['人际关系敏感数字化'] * 0.085 + features['抑郁数字化'] * 0.08 + features['多因子症状'] * 0.2 + features['母亲教养方式数字化'] * 0.09 + features['父亲教养方式数字化'] * 0.09 + features['自评家庭经济条件数字化'] * 0.06 + features['有无心理治疗（咨询）史数字化'] * 0.06 + features['学业情况数字化'] * 0.08 + features['出勤情况数字化'] * 0.12
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# 定义SCL-90的10个因子
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scl_90_factors = ["躯体化", "强迫症状", "人际关系敏感", "抑郁", "焦虑", "敌对", "恐怖", "偏执", "精神病性", "其他"]
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# 计算预警等级
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def calculate_warning_level(row):
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factors = row[scl_90_factors]
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if (factors >= 4).sum() >= 1 or (factors >= 3).sum() >= 8:
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return 1
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elif (factors >= 3).sum() >= 1:
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return 2
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elif (factors >= 2).sum() >= 1:
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return 3
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else:
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return 4
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features['label'] = features.apply(calculate_warning_level, axis=1)
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# 保存带有预警等级的数据
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features.to_excel('feature_label.xlsx', index=False)
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