根据另一个数据框中的值将列添加到数据框中

Question

I have two dataframes the first one:

df1 :

   product     price
0  apples      1.99
1  bananas     1.20 
2  oranges     1.49
3  lemons      0.5
4  Olive Oil   8.99

df2:

   product     product.1     product.2 
0  apples      bananas       Olive Oil
1  bananas     lemons        oranges
2  Olive Oil   bananas       oranges
3  lemons      apples        bananas

I want a column in the second dataframe to be the sum of the prices base on the price of each item in the first dataframe. So desired outcome would be:

   product     product.1     product.2     total_price 
0  apples      bananas       Olive Oil     12.18
1  bananas     lemons        oranges       3.19
2  Olive Oil   bananas       oranges       11.68
3  lemons      apples        bananas       3.69

What is the best way to accomplish this? I have tried merging the dataframes on the name for each of the columns in df2 but this seems time consuming especially as df1 gets more rows and df2 gets more columns.

df = pd.merge(df1, df2, how='right', left_on='product', right_on='product')
df = pd.merge(df1, df2, how='right', left_on='product', right_on='product.1')
df = pd.merge(df1, df2, how='right', left_on='product', right_on='product.2') 
df['Total_Price'] = df['price']+df['price.1']+df['price.2']

Answer 1

You can try something like below:

1. First, converting df1 to dictionary of keys and values
2. Using dictionary in above with applymap followed by sum

May be following snippet will do something similar:

dictionary_val = { k[0]: k[1] for k in df1.values }
df2['Total_Price'] = df2.applymap(lambda row: dictionary_val[row]).sum(axis=1) # Note not creating new dataframe but using existing one

Then result is df2 :

    product    product.1    product.2   Total_Price
0   apples      bananas     Olive Oil    12.18
1   bananas     lemons      oranges      3.19
2   Olive Oil   bananas     oranges      11.68
3   lemons      apples      bananas      3.69