如何在熊猫中标记具有多个条件的列？答案

【问题标题】：How to flag columns with multiple conditions in pandas?如何在熊猫中标记具有多个条件的列？
【发布时间】：2019-02-07 17:27:09
【问题描述】：

我在熊猫中有以下数据框

 ID    Date         Weekday     Public_holiday      
 1     01-01-2018   Monday      0
 2     02-01-2018   Tuesday     0
 3     03-01-2018   Wednesday   1
 4     04-01-2018   Thursday    0
 5     05-01-2018   Friday      0
 6     06-01-2018   Saturday    1
 7     07-01-2018   Sunday      0

如果工作日是周一、周二、周三、周四，我想将其标记为0，但如果有公共假期，则应将其标记为3， 1 如果工作日是Friday 但如果有公共假期则应标记为3, 2 如果有周末，但如果周末有公共假期，则应标记为 2 only

我正在关注熊猫

 m1 = df['Weekday'].isin(['Monday','Tuesday','Wednesday','Thursday'])
 m2 = df['Weekday'] == 'Friday'
 m3 = df['Public_Holiday'] == 1
 df['Flag'] = np.select([m1, m2, m3], ['0','1','2'],'3')

我想要的数据框是

ID    Date         Weekday     Public_holiday   Flag   
 1     01-01-2018   Monday      0               0
 2     02-01-2018   Tuesday     0               0  
 3     03-01-2018   Wednesday   1               3 
 4     04-01-2018   Thursday    0               0
 5     05-01-2018   Friday      0               1
 6     06-01-2018   Saturday    1               2
 7     07-01-2018   Sunday      0               2

【问题讨论】：

标签： python pandas

【解决方案1】：

这里有必要为过滤器添加条件，而不是AND链接的Public_holiday和3与OR链接的过滤器，也没有指定周末的默认值，因此添加到默认值：

m1 = df['Weekday'].isin(['Monday','Tuesday','Wednesday','Thursday'])
m2 = df['Weekday'] == 'Friday'
m3 = df['Public_holiday'] == 1

df['Flag'] = np.select([m1 & ~m3, m2 & ~m3, (m1 | m2) & m3], ['0','1','3'], default='2')

print (df)
   ID        Date    Weekday  Public_holiday Flag
0   1  01-01-2018     Monday               0    0
1   2  02-01-2018    Tuesday               0    0
2   3  03-01-2018  Wednesday               1    3
3   4  04-01-2018   Thursday               0    0
4   5  05-01-2018     Friday               0    1
5   6  06-01-2018   Saturday               1    2
6   7  07-01-2018     Sunday               0    2

您还可以定义所有不带默认值的条件：

m1 = df['Weekday'].isin(['Monday','Tuesday','Wednesday','Thursday'])
m2 = df['Weekday'] == 'Friday'
m3 = df['Public_holiday'] == 1
m4 = df['Weekday'].isin(['Saturday','Sunday'])

df['Flag'] = np.select([m1 & ~m3, (m1 | m2) & m3, m4, m2 & ~m3], ['0','3','2','1'])

【讨论】：