如何为python中不同的兴趣类别应用一个模型？

Question

我有一个每日销售数据集的4个项目，这是在4个不同的专营权销售。你知道吗

我必须建立一个模型来预测所有加盟店这4个项目的周销售额。你知道吗

我计划使用一个基本模型进行预测

reg = linear_model.Ridge(alpha=1)

我的问题是，我如何编写代码，以便在所有4种产品和特许经营中应用该模型。你知道吗

我将感谢你的时间和努力来帮助我。谢谢

我的桌子在下面

DepotName    Product    Date        SalesUnits  
    A           A1      2015-01-23  2.0 
    A           A2      2015-01-23  225.0   
    A           A3      2015-01-23  120.0   
    A           A4      2015-01-23  72.0    
    B           A1      2015-01-23  90.0    
    B           A2      2015-01-23  2.0 
    B           A3      2015-01-23  1.0 
    B           A4      2015-01-23  2.0 
    C           A1      2015-01-23  1.0 
    C           A2      2015-01-23  1.0 
    C           A3      2015-01-23  4.0 
    C           A4      2015-01-23  8040.0  
    D           A1      2015-01-23  1590.0  
    D           A2      2015-01-23  1.0     
    D           A3      2015-01-23  1590.0  
    D           A4      2015-01-23  1.0
    A           A1      2015-01-24  2.0 
    A           A2      2015-01-24  225.0   
    A           A3      2015-01-24  120.0   
    A           A4      2015-01-24  72.0    
    B           A1      2015-01-24  90.0    
    B           A2      2015-01-24  2.0 
    B           A3      2015-01-24  1.0 
    B           A4      2015-01-24  2.0 
    C           A1      2015-01-24  1.0 
    C           A2      2015-01-24  1.0 
    C           A3      2015-01-24  4.0 
    C           A4      2015-01-24  8040.0  
    D           A1      2015-01-24  1590.0  
    D           A2      2015-01-24  1.0     
    D           A3      2015-01-24  1590.0  
    D           A4      2015-01-24  1.0

Answer 1

只需在指示器上运行groupby操作：

for g in data.groupby(['DepotName', 'Product']):
   # g[0]: TUPLE OF CURRENT GROUP NAMES
   # g[1]: DATAFRAME OF CURRENT GROUP

   predictors = [... list of column names ...]

   reg = linear_model.Ridge(alpha=1)
   reg.fit(g[1][predictors], g[1]['SalesUnits'])

   y_pred = reg.predict(g[1][predictors])
   # ...