Python中使用多个numpy where条件为DataFrame新增列并赋值

• 逻辑运算符优先级错误：Python中&优先级高于|，你原代码中(df['Employment']=='Salaried')|(df['Employment']=='Business')&其他条件的实际计算逻辑为就业类型为Salaried，或者（就业类型为Business且满足其他条件），和你需求中「就业类型为Salaried或Business，同时满足其他条件」的逻辑不符。
• 多次赋值覆盖结果：每一次执行df['Result']=np.where(...)都会重写整列数据，不满足当前条件的行都会被赋值为空字符串，前几次的匹配结果会被后续操作直接覆盖，所以最终只有最后一行的条件生效。

推荐使用numpy.select实现多条件分支赋值，逻辑更清晰，无需嵌套写法：

import numpy as np

# 按顺序定义所有匹配条件
cond_list = [
    # 条件1：返回No Issue
    (df['Employment'].isin(['Salaried', 'Business'])) & 
    (df['Annual income of policy owner'] == '<= 10 lakh') & 
    (df['STP flagging'] == 'NON STP'),
    # 条件2：返回No Issue
    (df['Employment'].isin(['Salaried', 'Business'])) & 
    (df['Annual income of policy owner'] == '>10 lakh') & 
    (df['STP flagging'] == 'STP'),
    # 条件3：返回Issue
    (df['Employment'].isin(['Salaried', 'Business'])) & 
    (df['Annual income of policy owner'] == '>10 lakh') & 
    (df['STP flagging'] == 'NON STP'),
    # 条件4：返回Issue
    (df['Employment'].isin(['Salaried', 'Business'])) & 
    (df['Annual income of policy owner'] == '<= 10 lakh') & 
    (df['STP flagging'] == 'STP')
]

# 定义条件对应返回值，顺序和上面的条件一一对应
result_list = ['No Issue', 'No Issue', 'Issue', 'Issue']

# 赋值，不满足所有条件的行默认填充Null
df['Result'] = np.select(cond_list, result_list, default='Null')

请确认字段取值拼写完全一致，比如业务规则里的年收入取值是<=10 lakhs，代码里写的是<= 10 lakh，如果实际数据和代码里的取值不匹配会导致匹配失败。

内容的提问来源于stack exchange，提问作者KReEd