Python 如何根据Pandas中的多个条件从其他行获取值？

我有以下几点-

    +--------+--------+--------------------+------------+--------------------+----------+----------+
    | GameID | TeamID | Team               | OpponentID | Opponent           | Location | score    |
    +--------+--------+--------------------+------------+--------------------+----------+----------+
    | 1      | 1      | Alabama            | 2          | Jacksonville State | H        | 1.098633 |
    +--------+--------+--------------------+------------+--------------------+----------+----------+
    | 1      | 2      | Jacksonville State | 1          | Alabama            | V        | 0.756562 |
    +--------+--------+--------------------+------------+--------------------+----------+----------+
    | 2      | 3      | UAB                | 4          | Alcorn State       | H        | 1.270638 |
    +--------+--------+--------------------+------------+--------------------+----------+----------+
    | 2      | 4      | Alcorn State       | 3          | UAB                | V        | 0.682791 |
    +--------+--------+--------------------+------------+--------------------+----------+----------+

每行代表一个不同的GameID产生的两个团队结果中的一个。我的目标是有一个最终的df，看起来像这样

+--------+--------+--------------------+------------+--------------------+----------+----------+-----------------+
| GameID | TeamID | Team               | OpponentID | Opponent           | Location | score    | opponents score |
+--------+--------+--------------------+------------+--------------------+----------+----------+-----------------+
| 1      | 1      | Alabama            | 2          | Jacksonville State | H        | 1.098633 | 0.756562        |
+--------+--------+--------------------+------------+--------------------+----------+----------+-----------------+
| 1      | 2      | Jacksonville State | 1          | Alabama            | V        | 0.756562 | 1.098633        |
+--------+--------+--------------------+------------+--------------------+----------+----------+-----------------+
| 2      | 3      | UAB                | 4          | Alcorn State       | H        | 1.270638 | 0.682791        |
+--------+--------+--------------------+------------+--------------------+----------+----------+-----------------+
| 2      | 4      | Alcorn State       | 3          | UAB                | V        | 0.682791 | 1.270638        |
+--------+--------+--------------------+------------+--------------------+----------+----------+-----------------+

---

我被困在如何查找与具有不同列名的条件匹配的值上。谢谢

您可以使用

merge（）

方法：

resultdf=df.merge(df[['GameID','OpponentID','score']], left_on=['GameID','TeamID'], right_on=['GameID','OpponentID'], how='left')

现在使用

drop（）

方法：

result.drop(columns=['OpponentID_y'])

result=result.rename(columns={'OpponentID_x':'OpponentID','score_x':'score','score_y':'opponents score'})

最后使用

rename（）

方法：

result.drop(columns=['OpponentID_y'])

result=result.rename(columns={'OpponentID_x':'OpponentID','score_x':'score','score_y':'opponents score'})

现在，如果您打印

结果

，您将很容易获得所需的输出

。您可以使用以下代码实现所需的结果：

df_merge = df.merge(df, on=['GameID','TeamID'], how='outer', suffixes=(None, '_y'))
#print("Merged Dataset")
#display(df_merge)
df_merge.drop(['Team_y', 'OpponentID_y', 'Opponent_y', 'Location_y'], axis=1, inplace=True)
df_merge.rename( columns={'Score_y':'Opponent Score'}, inplace=True)
#print("Final Dataset")
#display(df_merge)

作品输出：

df.merge（df，左上=['GameID'，'TeamID'，右上=['GameID'，'OpponentID'，'how'left'）

并相应重命名。