python - 如何有条件地将值分配给列？

Question

 Customer_ID     Gender  First_Date First_region  First_state        First_city  \
0    129609144      M    20130130         West      Gujarat             Surat   
1    129627580      M    20130129        North        Delhi             Delhi   
2    130363481      M    20130221         West      Gujarat             Surat   
3     49817480      M    20130222         West  Maharashtra  Pimpri-Chinchwad   
4    126343829      F    20130301        North        Delhi             Delhi   

   Recent_Date    Last_region   Last_state         Last_city  Customer_Value  \
0     20130216        West      Gujarat             Surat          2032.0   
1     20130129       North        Delhi             Delhi          1709.0   
2     20130221        West      Gujarat             Surat           523.0   
3     20130222        West  Maharashtra  Pimpri-Chinchwad          5132.0   
4     20130301       North        Delhi             Delhi          1008.0   

   Buy_Times  Points_Earned  Points_Redeemed  
0          2          200.0              0.0  
1          1          100.0              0.0  
2          1           10.0              0.0  
3          1          170.0              0.0  
4          1           60.0              0.0    

我正在尝试创建一个新的列名称“客户值(value)分割”，但我想根据“Customer_Value”列的值分配此列中的值。

所以，

• 高值(value)分割市场 -> 25000
• 中值分割市场 - 10000 之间和25000
• 低值(value)分割 - 小于或等于 10000

我尝试过这个方法:

df['customer value segment'] = np.where(df['Customer_Value'] > 25000, 'High Value Segment', np.where(10000 > df['Customer_Value'] > 25000, 'Medium Value Segment', np.where(df['Customer_Value'] <= 10000, 'Low Value Segment', 'None')))  

但是，运气不佳。它向我抛出以下错误:

 ValueError                                Traceback (most recent call last)
<ipython-input-48-fee1062f32ba> in <module>
----> 1 df['customer value segment'] = np.where(df['Customer_Value'] > 25000, 'High Value Segment', np.where(10000 > df['Customer_Value'] > 25000, 'Medium Value Segment', np.where(df['Customer_Value'] <= 10000, 'Low Value Segment', 'None')))

~\Anaconda3\lib\site-packages\pandas\core\generic.py in __nonzero__(self)
   1476         raise ValueError("The truth value of a {0} is ambiguous. "
   1477                          "Use a.empty, a.bool(), a.item(), a.any() or a.all()."
-> 1478                          .format(self.__class__.__name__))
   1479 
   1480     __bool__ = __nonzero__

ValueError: The truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all().  

我现在应该如何处理这个问题？

注意 - 如果您想读取实际数据集，我就是这样做的:

df = pd.read_csv('Customers.csv', encoding='unicode_escape')

Answer 1

这应该有效:

df.loc[df['Customer_Value'] > 25000, 'customer value segment'] = 'High Value Segment' 
df.loc[(df['Customer_Value'] >= 10000) & (df['Customer_Value'] <= 25000) , 'customer value segment'] = 'Medium Value Segemnt ' 
df.loc[df['Customer_Value'] < 10000, 'customer value segment'] = 'Low Value Segment '