如何通过使用实际数据帧中两列中的值索引另一个数据帧来在实际数据帧中创建列

Question

Good day. I have two dataset (df1,df2). I am trying to fill the column 'values' in df2 by using the column 'site_before' as the row index in df1 and the column 'site' as the column index in df1.

The dataset df1:

      ANA01  PHO01  ATL  BAL12  BOS07   
ANA01   0     0      3     3     3
PHO01   0     0      3     3     3
ATL    -3    -3      0     0     0 
BAL12   -3   -3      0     0     0 
BOS07   -3    -3     0     0     0

"The first column is the indexes of the rows"

The dataset df2:

    Game_ID     site_before  site   values
1   ANA199804010    ANA01   ANA01   
3   ANA199804020    ANA01   ATL 
5   ANA199804030    ANA01   BAL12   
7   ANA199804040    ANA01   BOS07   
9   ANA199804050    ANA01   ANA01   
674 BOS199804300    BOS07   BOS07   
31  ANA199805010    BOS07   ANA01   
33  ANA199805020    PHO01   ANA01   
35  ANA199805030    PHO01   PHO01   
37  ANA199805040    PHO01   ATL 
39  ANA199805050    PHO01   BAL12

I tried to do:

df2['values'] = df1.loc[df2['site_before'], df2['site']].values

but I got an error as ValueError: Wrong number of items passed 4864, placement implies 1

The result I am expecting is:

    Game_ID     site_before site    values
1   ANA199804010    ANA01   ANA01   0
3   ANA199804020    ANA01   ATL     3
5   ANA199804030    ANA01   BAL12   3
7   ANA199804040    ANA01   BOS07   3
9   ANA199804050    ANA01   ANA01   0
674 BOS199804300    BOS07   BOS07   0
31  ANA199805010    BOS07   ANA01   -3
33  ANA199805020    PHO01   ANA01   0
35  ANA199805030    PHO01   PHO01   0
37  ANA199805040    PHO01   ATL     3
39  ANA199805050    PHO01   BAL12   3

Answer 1

Use DataFrame.join with new MultiIndex Series created by DataFrame.stack :

df2 = df2.join(df1.stack().rename('new').rename_axis(('site_before','site')), 
               on=['site_before','site'])
print (df2)
          Game_ID site_before   site  new
1    ANA199804010       ANA01  ANA01    0
3    ANA199804020       ANA01    ATL    3
5    ANA199804030       ANA01  BAL12    3
7    ANA199804040       ANA01  BOS07    3
9    ANA199804050       ANA01  ANA01    0
674  BOS199804300       BOS07  BOS07    0
31   ANA199805010       BOS07  ANA01   -3
33   ANA199805020       PHO01  ANA01    0
35   ANA199805030       PHO01  PHO01    0
37   ANA199805040       PHO01    ATL    3
39   ANA199805050       PHO01  BAL12    3

Alternative is use DataFrame.melt with DataFrame.merge and left join:

df3 = df1.rename_axis('site_before').reset_index().melt('site_before', var_name='site')

---

df2 = df2.merge(df3, how='left')
print (df2)
         Game_ID site_before   site  new
0   ANA199804010       ANA01  ANA01    0
1   ANA199804020       ANA01    ATL    3
2   ANA199804030       ANA01  BAL12    3
3   ANA199804040       ANA01  BOS07    3
4   ANA199804050       ANA01  ANA01    0
5   BOS199804300       BOS07  BOS07    0
6   ANA199805010       BOS07  ANA01   -3
7   ANA199805020       PHO01  ANA01    0
8   ANA199805030       PHO01  PHO01    0
9   ANA199805040       PHO01    ATL    3
10  ANA199805050       PHO01  BAL12    3