[Numpy] np.select

 美图欣赏2022/07/28

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np.select(condlist, choicelist, default=0) 

condlist：条件列表，元素是布尔型数组

choicelist：列表，数组元素

default：当所有条件都不满足时，用default值(默认值)填上

注意: condlist, choicelist的长度必须一致，每一个条件都要进行一次元素选择或者操作 

import pandas as pd
import numpy as np
 
df = pd.DataFrame(data={'语文':[50,90,70,78,60],
                        '数学':[59,80,60,75,69],
                        '英语':[61,95,65,80,59]},
                  index=['Harry','Andy','Rita','Lee','Jack'])
# 多条件判断,有多个条件可以使用np.select
conditions = [(df['语文']>=60)&(df['数学']>=60)&(df['英语']>=60),
              (df['语文']<60)&(df['数学']>=60)&(df['英语']>=60),
              (df['语文']>=60)&(df['数学']<60)&(df['英语']>=60),
              (df['语文']>=60)&(df['数学']>=60)&(df['英语']<60),
              (df['语文']>=60)&(df['数学']<60)&(df['英语']<60),
              (df['语文']<60)&(df['数学']>=60)&(df['英语']<60),
              (df['语文']<60)&(df['数学']<60)&(df['英语']>=60),
              (df['语文']<60)&(df['数学']<60)&(df['英语']<60)]
results = ['合格','不合格','不合格','不合格','不合格','不合格','不合格','不合格']
# 生成'评级'字段
df['评级'] = np.select(conditions,results,default='不合格')

df