Python的大熊猫删除UserWarning，有效地循环

Question

可以说我有类似的代码如下：

import pandas as pd 

df=pd.DataFrame({'Name': [ 'Jay Leno', 'JayLin', 'Jay-Jameson', 'LinLeno', 'Lin Jameson', 'Python Leno', 'Python Lin', 'Python Jameson', 'Lin Jay', 'Python Monte'], 
       'Class': ['Rat','L','H','L','L','H', 'H','L','L','Circus']}) 
df['status']='' 

pattern1=['^Jay(\s|-)?(Leno|Lin|Jameson)$','^Python(\s|-)?(Jay|Leno|Lin|Jameson|Monte)$','^Lin(\s|-)?(Leno|Jay|Jameson|Monte)$' ] 
pattern2=['^Python(\s|-)?(Jay|Leno|Lin|Jameson|Monte)$' ] 
pattern3=['^Lin(\s|-)?(Leno|Jay|Jameson|Monte)$' ] 

for i in range(len(pattern1)): 
    df.loc[df.Name.str.contains(pattern1[i]),'status'] = 'A' 

for i in range(len(pattern2)): 
    df.loc[df.Name.str.contains(pattern2[i]),'status'] = 'B' 

for i in range(len(pattern3)): 
    df.loc[df.Name.str.contains(pattern3[i]),'status'] = 'C' 

print (df) 

它打印：

C:\Python33\lib\site-packages\pandas\core\strings.py:184: UserWarning: This pattern has match groups. To actually get the groups, use str.extract. 
    " groups, use str.extract.", UserWarning) 
    Class   Name status 
0  Rat  Jay Leno  A 
1  L   JayLin  A 
2  H  Jay-Jameson  A 
3  L   LinLeno  C 
4  L  Lin Jameson  C 
5  H  Python Leno  B 
6  H  Python Lin  B 
7  L Python Jameson  B 
8  L   Lin Jay  C 
9 Circus Python Monte  B 

[10 rows x 3 columns] 

我的问题是我怎么删除错误和是否有办法用更少的代码更有效地循环？我知道有些东西叫做列表解析，但我对如何使用它们感到困惑。

我知道错误可能

pd.options.mode.chained_assignment = None 

Answer 1

抑制使用non-capturing parentheses(?:...)：

pattern1=['^Jay(?:\s|-)?(?:Leno|Lin|Jameson)$','^Python(?:\s|-)?(?:Jay|Leno|Lin|Jameson|Monte)$','^Lin(?:\s|-)?(?:Leno|Jay|Jameson|Monte)$' ] 
pattern2=['^Python(?:\s|-)?(?:Jay|Leno|Lin|Jameson|Monte)$' ] 
pattern3=['^Lin(?:\s|-)?(?:Leno|Jay|Jameson|Monte)$' ] 

的警告来自this code：

if regex.groups > 0: 
     warnings.warn("This pattern has match groups. To actually get the" 
         " groups, use str.extract.", UserWarning) 

所以只要没有团体，没有任何警告。