请原谅标题-我不确定如何最好地描述我的问题。我相信我所追求的可能是某种类似于条件外连接/合并的东西。我认为要么在开始时设置条件,要么合并所有内容,然后删除不必要的信息。我有一个例子,希望能帮助解释我的情况。你知道吗
我从以下数据帧开始:
数据帧1
+--------+------------+
| GlobID | Issue |
+--------+------------+
| 1 | Building M |
+--------+------------+
| 2 | Building V |
+--------+------------+
| 3 | Building H |
+--------+------------+
数据帧2
+----+---------+---------+------------+---------+---------+------------+
| ID | Issue_A | Note_A | Location_A | Issue_B | Note_B | Location_B |
+----+---------+---------+------------+---------+---------+------------+
| 1 | Y | broken | bathroom | N | | |
+----+---------+---------+------------+---------+---------+------------+
| 2 | Y | stained | bedroom | Y | rusty | basement |
+----+---------+---------+------------+---------+---------+------------+
| 3 | Y | missing | kitchen | Y | cracked | attic |
+----+---------+---------+------------+---------+---------+------------+
期望结果:
+--------+------------+---------+----------+
| GlobID | Name | Issue | Location |
+--------+------------+---------+----------+
| 1 | Building M | broken | bathroom |
+--------+------------+---------+----------+
| 2 | Building V | stained | bedroom |
+--------+------------+---------+----------+
| 2 | Building V | rusty | basement |
+--------+------------+---------+----------+
| 3 | Building H | missing | kitchen |
+--------+------------+---------+----------+
| 3 | Building H | cracked | attic |
+--------+------------+---------+----------+
正如我所提到的,我不确定外部连接是否是我想要在这里与ffill一起填写id的东西?任何帮助都将不胜感激。你知道吗
编辑:
忘了提一下,这是我现在的代码:
pd.merge(df1, df2.set_index('ID'), left_on='GlobID', right_index=True)
这只会让我加入df1和df2。我还是要把问题说清楚,让他们各自为政。你知道吗
您可以使用这样的算法:
它给你:
然后你可以做一个简单的合并:
这是解决问题的简单方法:
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