python - 一列中每次出现的值在另一列中的总和

Question

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How do I Pandas group-by to get sum? (11 个回答)

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我似乎找不到谷歌搜索这个问题的正确措辞，因为我得到了非常相似但不是正确的答案。

我正忙于处理泰坦尼克号数据集，并且想要计算一个家庭中幸存成员的数量。所以数据集看起来像这样:

+-------------+----------+-----------+-------------+
| PassengerId | Survived | Surname | NumSurvived |
+-------------+----------+-----------+-------------+
| 1 | 0 | Braund | |
| 2 | 1 | Cumings | |
| 3 | 1 | Heikkinen | |
| 4 | 1 | Futrelle | |
| 5 | 0 | Braund | |
| 6 | 0 | Moran | |
| 7 | 0 | Futrelle | |
| 8 | 0 | Braund | |
| 9 | 1 | Cumings | |
+-------------+----------+-----------+-------------+

我需要对 NumSurvived 列中每个姓氏的 Survived 值求和，如下所示:

+-------------+----------+-----------+-------------+
| PassengerId | Survived | Surname | NumSurvived |
+-------------+----------+-----------+-------------+
| 1 | 0 | Braund | 0 |
| 2 | 1 | Cumings | 2 |
| 3 | 1 | Heikkinen | 1 |
| 4 | 1 | Futrelle | 1 |
| 5 | 0 | Braund | 0 |
| 6 | 0 | Moran | 0 |
| 7 | 0 | Futrelle | 1 |
| 8 | 0 | Braund | 0 |
| 9 | 1 | Cumings | 2 |
+-------------+----------+-----------+-------------+

Answer 1

尝试:

df['NumSurvived']=df.groupby('Surname')['Survived'].transform(lambda x: x.eq(1).sum())

打印(df)

   PassengerId  Survived    Surname  NumSurvived
0            1         0     Braund            0
1            2         1    Cumings            2
2            3         1  Heikkinen            1
3            4         1   Futrelle            1
4            5         0     Braund            0
5            6         0      Moran            0
6            7         0   Futrelle            1
7            8         0     Braund            0
8            9         1    Cumings            2