熊猫 - 具有条件公式的Groupby

Question

   Survived  SibSp  Parch
0         0      1      0
1         1      1      0
2         1      0      0
3         1      1      0
4         0      0      1

鉴于上述数据框架,groupby有条件的优雅方式吗？我想根据以下条件将数据拆分为两组:

(df['SibSp'] > 0) | (df['Parch'] > 0) =   New Group -"Has Family"
 (df['SibSp'] == 0) & (df['Parch'] == 0) = New Group - "No Family"

然后采取这两个组的方法,最终输出如下:

               SurvivedMean
 Has Family    Mean
 No Family     Mean

可以使用groupby完成,还是必须使用上述条件语句追加新列？

谢谢!

Answer 1

一种简单的分组方法是使用这两列的总和.如果它们中的任何一个为正,则结果将大于1.并且groupby接受任意数组,只要该长度与DataFrame的长度相同,因此您不需要添加新列.

family = np.where((df['SibSp'] + df['Parch']) >= 1 , 'Has Family', 'No Family')
df.groupby(family)['Survived'].mean()
Out: 
Has Family    0.5
No Family     1.0
Name: Survived, dtype: float64