根据 Pandas 中的 id 将列值从一个数据帧复制到另一个数据帧

Question

I am trying to copy Name from df2 into df1 where ID is common between both dataframes.

df1:

ID    Name 

1     A
2     B
4     C
16    D
7     E

df2:

ID    Name 

1     X
2     Y
7     Z

Expected Output:

ID    Name 

1     X
2     Y
4     C
16    D
7     Z

I have tried like this, but it didn't worked. I am not able to understand how to assign value here. I am assigning =df2['Name'] which is wrong.

for i in df2["ID"].tolist():
    df1['Name'].loc[(df1['ID'] == i)] = df2['Name']

Answer 1

Try with update

df1 = df1.set_index('ID')
df1.update(df2.set_index('ID'))
df1 = df1.reset_index()
df1
Out[476]: 
   ID Name
0   1    X
1   2    Y
2   4    C
3  16    D
4   7    Z

Answer 2

如果行的顺序无关紧要，那么连接两个 dfs 和 drop_duplicates 将达到结果，

df2.append(df1).drop_duplicates(subset='ID')

Answer 3

another solution would be,

s = df1["Name"]
df1.loc[:,"Name"]=df1["ID"].map(df2.set_index("ID")["Name"].to_dict()).fillna(s)

o/P:

   ID Name
0   1    X
1   2    Y
2   4    C
3  16    D
4   7    Z

Answer 4

One more for consideration

df,dg = df1,df2
df = df.set_index('ID')
dg = dg.set_index('ID')
df.loc[dg.index,:] = dg               # All columns
#df.loc[dg.index,'Name'] = dg.Name    # Single column
df = df.reset_index()

>>> df
   ID Name
0   1    X
1   2    Y
2   4    C
3  16    D
4   7    Z

Or for a single column (index for both is 'ID'