英文:
pandas window by groupby function
问题
我有一个pd数据框：
pd.DataFrame({'day': [1, 2, 3, 4, 5, 6, 7, 8, 9, 10],
'A': [1, 1, 1, 0, 0, 0, 1, 1, 0, 0],
'B': [7, 8, 4, 3, 5, 6, 3, 1, 4, 5],})
我想要创建一个滑动窗口，只要列的值为1，就找到最大值，一旦值变为0，就找到这些0的最大值。以下是期望的输出：
pd.DataFrame({'day': [1, 2, 3, 4, 5, 6, 7, 8, 9, 10],
'A': [1, 1, 1, 0, 0, 0, 1, 1, 0, 0],
'B': [7, 8, 4, 3, 5, 6, 3, 1, 4, 5],
'Output': [8, 8, 8, 6, 6, 6, 3, 3, 5, 5 ]})
英文:
I have a pd dataframe
pd.DataFrame({'day': [1, 2, 3, 4, 5, 6, 7, 8, 9, 10],
'A': [1, 1, 1, 0, 0,0, 1, 1, 0, 0],
'B': [7, 8, 4, 3, 5, 6, 3, 1, 4, 5],})
I want to do a sliding window that as long as the value of a column is 1 find the max, as soon as the value changes to 0 find the max for those 0. here is a desired output:
pd.DataFrame({'day': [1, 2, 3, 4, 5, 6, 7, 8, 9, 10],
'A': [1, 1, 1, 0, 0,0, 1, 1, 0, 0],
'B': [7, 8, 4, 3, 5, 6, 3, 1, 4, 5],
'Output': [8, 8, 8, 6, 6, 6, 3, 3, 5, 5 ]})
答案1
得分: 0
使用A的移位值和Series.cumsum来创建连续的分组，然后传递给GroupBy.transform，使用max函数：
df['Output'] = df.groupby(df.A.ne(df.A.shift()).cumsum())['B'].transform('max')
print(df)
day A B Output
0 1 1 7 8
1 2 1 8 8
2 3 1 4 8
3 4 0 3 6
4 5 0 5 6
5 6 0 6 6
6 7 1 3 3
7 8 1 1 3
8 9 0 4 5
9 10 0 5 5
英文:
Create consecutive groups by A by compare with shifted values and Series.cumsum, then pass to GroupBy.transform with max:
df['Output'] = df.groupby(df.A.ne(df.A.shift()).cumsum())['B'].transform('max')
print (df)
day A B Output
0 1 1 7 8
1 2 1 8 8
2 3 1 4 8
3 4 0 3 6
4 5 0 5 6
5 6 0 6 6
6 7 1 3 3
7 8 1 1 3
8 9 0 4 5
9 10 0 5 5
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