Python 根据RFM分数细分客户并创建数据框架

我对一个采购历史数据进行了RFM分析

根据RFM类别，我对客户进行了细分，因为我的一些客户属于多个类别，所以我必须将客户细分为他们所属的类别，并添加到RFM表中（添加一个单独的列“segment”）

CardNo最近频率货币R_四分位数F_四分位数M_四分位数RFMClass段

除了要添加到rfm表中的“segment”列之外，我的rfmtable列与上面的列类似

到目前为止，我所做的是

for card_no in rfmSegmentation['CardNo']:
>     for num in rfmSegmentation['RFMClass']:
>         num = str(num)
>         if int(num[0])==1 and int(num[1])==1 and int(num[2])==1:
>             print("RFM_class",num,"cardno",card_no,"Best Customer")
>         elif int(num[1])==1:
>             print("RFM_class",num,"cardno",card_no,"Loyal Customer")
>         elif int(num[2])==1:
>             print("RFM_class",num,"cardno",card_no,"Big Spender")
>         elif int(num[0])==3 and int(num[1])==1 and int(num[2])==1:  
>             print("RFM_class",num,"cardno",card_no,"Almost Lost")        
>         elif int(num[0])==4 and int(num[1])==1 and int(num[2])==1:   
>             print("RFM_class",num,"cardno",card_no,"Lost Customer")
>         elif int(num[0])==4 and int(num[1])==4 and int(num[2])==4:  
>             print("RFM_class",num,"cardno",card_no,"Lost Cheap Customer")

它打印每个客户的细分，但我想将其作为单独的列添加到rfmtable中，并将其转换为csv文件

---

任何帮助都将不胜感激

这实际上是一个

pandas

和

dataframe

问题，与

机器学习无关（标签已移除）；还可以考虑改变标题来描述实际问题………………你能用期望的输出发布你的数据的例子吗？请不要使用图片。您可以使用应用功能进行此操作。
 > I think I found a solution
    > 
    > segment = []
    > 
    >  for row in rfmSegmentation['RFMClass']:
    >     row = str(row)
    >     if int(row[0])==1 and int(row[1])==1 and int(row[2])==1:
    >         segment.append('Best Customer')
    >     elif int(row[1])==1:
    >         segment.append('Loyal Customer')
    >     elif int(row[2])==1:
    >         segment.append('Big Spender')
    >     elif int(row[0])==3 and int(row[1])==1 and int(row[2])==1:
    >         segment.append('Almost Lost')
    >     elif int(row[0])==4 and int(row[1])==1 and int(row[2])==1: 
    >         segment.append('Lost Customer')
    >     elif int(row[0])==4 and int(row[1])==4 and int(row[2])==4:
    >         segment.append('Lost Cheap Customer')
    >     else:
    >         segment.append('Failed')
    >         
    >  rfmSegmentation['segment'] = segment