All combinations of two dataframes





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Having two dataframes:



id  Country Channel Week    Value        

0   ES      Train   2018-48 1000

1   ES      Train   2018-49 1000

2   ES      Train   2018-50 1000

3   ES      Train   2018-51 1000

4   ES      Train   2018-52 1000


and 



Week        Product1    Product2    Product3

2018-48     25%         50%         25%

2018-49     25%         50%         25%

2018-50     25%         50%         25%

2018-51     25%         50%         25%

2018-52     25%         50%         25%


How can I create a combination of both where I add each product to every line of the first frame and use the value multiplied by the product itself?



E.g. for the first two weeks, this would result in:



id  Country Channel Week    Value   Product        

0   ES      Train   2018-48 250     Product1

1   ES      Train   2018-48 500     Product2

2   ES      Train   2018-48 250     Product3

3   ES      Train   2018-49 250     Product1

4   ES      Train   2018-49 500     Product2

5   ES      Train   2018-49 250     Product3

6   ...





python pandas







share|improve this question





























    2















    Having two dataframes:



    id  Country Channel Week    Value        
    
0   ES      Train   2018-48 1000
    
1   ES      Train   2018-49 1000
    
2   ES      Train   2018-50 1000
    
3   ES      Train   2018-51 1000
    
4   ES      Train   2018-52 1000


    and 



    Week        Product1    Product2    Product3
    
2018-48     25%         50%         25%
    
2018-49     25%         50%         25%
    
2018-50     25%         50%         25%
    
2018-51     25%         50%         25%
    
2018-52     25%         50%         25%


    How can I create a combination of both where I add each product to every line of the first frame and use the value multiplied by the product itself?



    E.g. for the first two weeks, this would result in:



    id  Country Channel Week    Value   Product        
    
0   ES      Train   2018-48 250     Product1
    
1   ES      Train   2018-48 500     Product2
    
2   ES      Train   2018-48 250     Product3
    
3   ES      Train   2018-49 250     Product1
    
4   ES      Train   2018-49 500     Product2
    
5   ES      Train   2018-49 250     Product3
    
6   ...





    python pandas







    share|improve this question

























      2












      2








      2








      Having two dataframes:



      id  Country Channel Week    Value        
      
0   ES      Train   2018-48 1000
      
1   ES      Train   2018-49 1000
      
2   ES      Train   2018-50 1000
      
3   ES      Train   2018-51 1000
      
4   ES      Train   2018-52 1000


      and 



      Week        Product1    Product2    Product3
      
2018-48     25%         50%         25%
      
2018-49     25%         50%         25%
      
2018-50     25%         50%         25%
      
2018-51     25%         50%         25%
      
2018-52     25%         50%         25%


      How can I create a combination of both where I add each product to every line of the first frame and use the value multiplied by the product itself?



      E.g. for the first two weeks, this would result in:



      id  Country Channel Week    Value   Product        
      
0   ES      Train   2018-48 250     Product1
      
1   ES      Train   2018-48 500     Product2
      
2   ES      Train   2018-48 250     Product3
      
3   ES      Train   2018-49 250     Product1
      
4   ES      Train   2018-49 500     Product2
      
5   ES      Train   2018-49 250     Product3
      
6   ...





      python pandas







      share|improve this question














      Having two dataframes:



      id  Country Channel Week    Value        
      
0   ES      Train   2018-48 1000
      
1   ES      Train   2018-49 1000
      
2   ES      Train   2018-50 1000
      
3   ES      Train   2018-51 1000
      
4   ES      Train   2018-52 1000


      and 



      Week        Product1    Product2    Product3
      
2018-48     25%         50%         25%
      
2018-49     25%         50%         25%
      
2018-50     25%         50%         25%
      
2018-51     25%         50%         25%
      
2018-52     25%         50%         25%


      How can I create a combination of both where I add each product to every line of the first frame and use the value multiplied by the product itself?



      E.g. for the first two weeks, this would result in:



      id  Country Channel Week    Value   Product        
      
0   ES      Train   2018-48 250     Product1
      
1   ES      Train   2018-48 500     Product2
      
2   ES      Train   2018-48 250     Product3
      
3   ES      Train   2018-49 250     Product1
      
4   ES      Train   2018-49 500     Product2
      
5   ES      Train   2018-49 250     Product3
      
6   ...





      python pandas




      python pandas






      share|improve this question













      share|improve this question











      share|improve this question




      share|improve this question










      asked Nov 21 '18 at 23:18









      Bishonen_PLBishonen_PL

      13910




      13910
























          1 Answer
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          1














          Assuming you start with dataframes df1 and df2, first melt df2 (wide-to-long), convert your percentages to numeric, then merge with df1:



          df2 = pd.melt(df2, id_vars='Week', value_vars=['Product1', 'Product2', 'Product3'])
          
df2['value'] = pd.to_numeric(df2['value'].str[:-1])
          

          
res = df1.merge(df2)
          
         .eval('Value = Value * value / 100')
          
         .drop('value', 1)
          

          
print(res)
          

          
    id Country Channel     Week  Value  variable
          
0    0      ES   Train  2018-48  250.0  Product1
          
1    0      ES   Train  2018-48  500.0  Product2
          
2    0      ES   Train  2018-48  250.0  Product3
          
3    1      ES   Train  2018-49  250.0  Product1
          
4    1      ES   Train  2018-49  500.0  Product2
          
5    1      ES   Train  2018-49  250.0  Product3
          
6    2      ES   Train  2018-50  250.0  Product1
          
7    2      ES   Train  2018-50  500.0  Product2
          
8    2      ES   Train  2018-50  250.0  Product3
          
9    3      ES   Train  2018-51  250.0  Product1
          
10   3      ES   Train  2018-51  500.0  Product2
          
11   3      ES   Train  2018-51  250.0  Product3
          
12   4      ES   Train  2018-52  250.0  Product1
          
13   4      ES   Train  2018-52  500.0  Product2
          
14   4      ES   Train  2018-52  250.0  Product3





          share|improve this answer
























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            1 Answer
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            1 Answer
            1






            active

            oldest

            votes









            active

            oldest

            votes






            active

            oldest

            votes









            1














            Assuming you start with dataframes df1 and df2, first melt df2 (wide-to-long), convert your percentages to numeric, then merge with df1:



            df2 = pd.melt(df2, id_vars='Week', value_vars=['Product1', 'Product2', 'Product3'])
            
df2['value'] = pd.to_numeric(df2['value'].str[:-1])
            

            
res = df1.merge(df2)
            
         .eval('Value = Value * value / 100')
            
         .drop('value', 1)
            

            
print(res)
            

            
    id Country Channel     Week  Value  variable
            
0    0      ES   Train  2018-48  250.0  Product1
            
1    0      ES   Train  2018-48  500.0  Product2
            
2    0      ES   Train  2018-48  250.0  Product3
            
3    1      ES   Train  2018-49  250.0  Product1
            
4    1      ES   Train  2018-49  500.0  Product2
            
5    1      ES   Train  2018-49  250.0  Product3
            
6    2      ES   Train  2018-50  250.0  Product1
            
7    2      ES   Train  2018-50  500.0  Product2
            
8    2      ES   Train  2018-50  250.0  Product3
            
9    3      ES   Train  2018-51  250.0  Product1
            
10   3      ES   Train  2018-51  500.0  Product2
            
11   3      ES   Train  2018-51  250.0  Product3
            
12   4      ES   Train  2018-52  250.0  Product1
            
13   4      ES   Train  2018-52  500.0  Product2
            
14   4      ES   Train  2018-52  250.0  Product3





            share|improve this answer




























              1














              Assuming you start with dataframes df1 and df2, first melt df2 (wide-to-long), convert your percentages to numeric, then merge with df1:



              df2 = pd.melt(df2, id_vars='Week', value_vars=['Product1', 'Product2', 'Product3'])
              
df2['value'] = pd.to_numeric(df2['value'].str[:-1])
              

              
res = df1.merge(df2)
              
         .eval('Value = Value * value / 100')
              
         .drop('value', 1)
              

              
print(res)
              

              
    id Country Channel     Week  Value  variable
              
0    0      ES   Train  2018-48  250.0  Product1
              
1    0      ES   Train  2018-48  500.0  Product2
              
2    0      ES   Train  2018-48  250.0  Product3
              
3    1      ES   Train  2018-49  250.0  Product1
              
4    1      ES   Train  2018-49  500.0  Product2
              
5    1      ES   Train  2018-49  250.0  Product3
              
6    2      ES   Train  2018-50  250.0  Product1
              
7    2      ES   Train  2018-50  500.0  Product2
              
8    2      ES   Train  2018-50  250.0  Product3
              
9    3      ES   Train  2018-51  250.0  Product1
              
10   3      ES   Train  2018-51  500.0  Product2
              
11   3      ES   Train  2018-51  250.0  Product3
              
12   4      ES   Train  2018-52  250.0  Product1
              
13   4      ES   Train  2018-52  500.0  Product2
              
14   4      ES   Train  2018-52  250.0  Product3





              share|improve this answer


























                1












                1








                1







                Assuming you start with dataframes df1 and df2, first melt df2 (wide-to-long), convert your percentages to numeric, then merge with df1:



                df2 = pd.melt(df2, id_vars='Week', value_vars=['Product1', 'Product2', 'Product3'])
                
df2['value'] = pd.to_numeric(df2['value'].str[:-1])
                

                
res = df1.merge(df2)
                
         .eval('Value = Value * value / 100')
                
         .drop('value', 1)
                

                
print(res)
                

                
    id Country Channel     Week  Value  variable
                
0    0      ES   Train  2018-48  250.0  Product1
                
1    0      ES   Train  2018-48  500.0  Product2
                
2    0      ES   Train  2018-48  250.0  Product3
                
3    1      ES   Train  2018-49  250.0  Product1
                
4    1      ES   Train  2018-49  500.0  Product2
                
5    1      ES   Train  2018-49  250.0  Product3
                
6    2      ES   Train  2018-50  250.0  Product1
                
7    2      ES   Train  2018-50  500.0  Product2
                
8    2      ES   Train  2018-50  250.0  Product3
                
9    3      ES   Train  2018-51  250.0  Product1
                
10   3      ES   Train  2018-51  500.0  Product2
                
11   3      ES   Train  2018-51  250.0  Product3
                
12   4      ES   Train  2018-52  250.0  Product1
                
13   4      ES   Train  2018-52  500.0  Product2
                
14   4      ES   Train  2018-52  250.0  Product3





                share|improve this answer













                Assuming you start with dataframes df1 and df2, first melt df2 (wide-to-long), convert your percentages to numeric, then merge with df1:



                df2 = pd.melt(df2, id_vars='Week', value_vars=['Product1', 'Product2', 'Product3'])
                
df2['value'] = pd.to_numeric(df2['value'].str[:-1])
                

                
res = df1.merge(df2)
                
         .eval('Value = Value * value / 100')
                
         .drop('value', 1)
                

                
print(res)
                

                
    id Country Channel     Week  Value  variable
                
0    0      ES   Train  2018-48  250.0  Product1
                
1    0      ES   Train  2018-48  500.0  Product2
                
2    0      ES   Train  2018-48  250.0  Product3
                
3    1      ES   Train  2018-49  250.0  Product1
                
4    1      ES   Train  2018-49  500.0  Product2
                
5    1      ES   Train  2018-49  250.0  Product3
                
6    2      ES   Train  2018-50  250.0  Product1
                
7    2      ES   Train  2018-50  500.0  Product2
                
8    2      ES   Train  2018-50  250.0  Product3
                
9    3      ES   Train  2018-51  250.0  Product1
                
10   3      ES   Train  2018-51  500.0  Product2
                
11   3      ES   Train  2018-51  250.0  Product3
                
12   4      ES   Train  2018-52  250.0  Product1
                
13   4      ES   Train  2018-52  500.0  Product2
                
14   4      ES   Train  2018-52  250.0  Product3






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                answered Nov 21 '18 at 23:25









                jppjpp

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