合并和覆盖 pandas df 中的值

Question

I have two df's containing that I'm hoping to merge and overwrite specific values. Using below, df1 and df2 will be merged and I'm hoping to overwrite the values in Group for certain rows. Specifically, where Group is == Y , I want to use the values in df2 . I've got a way but I don't think it's very efficient.

df1 = pd.DataFrame({      
    'Time' : [1,1,1,1,2,2,2,2,2],
    'Label' : ['A','B','C','D','A','B','C','D','E'],    
    'Group' : ['X','X','X','Y','X','Y','X','Y','X'],            
   })

df2 = pd.DataFrame({  
    'Time' : [1,2,2],        
    'Label' : ['D','B','D'],  
    'Group2' : ['Y1','Y3','Y2'],                                            
    })

df_out = pd.merge(df1,df2, how = 'outer')

out:

   Time Label Group Group2
0     1     A     X    NaN
1     1     B     X    NaN
2     1     C     X    NaN
3     1     D     Y     Y1
4     2     A     X    NaN
5     2     B     Y     Y3
6     2     C     X    NaN
7     2     D     Y     Y2
8     2     E     X    NaN

I could then copy Group2 to Group excluding the NaN values and then drop Group2 but is there a more efficient method

Answer 1

If I understand you right, you want to update df1['Group'] with df2['Group2'] values:

df1["Group"].update(df1.merge(df2, on=["Time", "Label"], how="outer")["Group2"])
print(df1)

Prints:

   Time Label Group
0     1     A     X
1     1     B     X
2     1     C     X
3     1     D    Y1
4     2     A     X
5     2     B    Y3
6     2     C     X
7     2     D    Y2
8     2     E     X