如果另一列中的值相邻，则求和数据帧中的列值

Question

你好，我有一个数据帧：

import pandas as pd
df1 = {'name': ["x","x","x","x","x","x","x","y","y","y","y","y","y","y"],
'a': [3,4,5,11,14,15,16,2,3,4,10,13,14,15],
'b': [9,8,7,12,23,22,21,8,7,6,11,22,21,20],
'val': [2,1,3,4,5,6,3,21,11,31,41,51,61,31]    
}
df1 = pd.DataFrame (df1, columns = ['name','a','b','val'])

如果"a"列中的数字相邻，我希望对"val"列中数字求和。例如，在"a"中，您有3，4，5(都挨着(，因此将它们在"val"列中的相关数字相加(即2+1+3(，然后在存在相加值的位置创建一个新列。对我来说，更困难的是按"名称"对它们进行分组。

我不知道我解释得有多好，但这是我希望最终使用的数据帧

df2 = {'name': ["x","x","x","x","x","x","x","y","y","y","y","y","y","y"],
'a': [3,4,5,11,14,15,16,2,3,4,10,13,14,15],
'b': [9,8,7,12,23,22,21,8,7,6,11,22,21,20],
'val': [2,1,3,4,5,6,3,21,11,31,41,51,61,31],
'sum_val': [6,6,6,4,14,14,14,63,63,63,41,143,143,143]
}
df2 = pd.DataFrame (df2, columns = ['name','a','b','val','sum_val'])

Answer 1

通过比较lambda函数中不等于每个组的累积和的差异来创建组，并使用sum:将Series传递给GroupBy.transform

g = df1.groupby('name')['a'].apply(lambda x: x.diff().ne(1).cumsum())
df1['sum_val'] = df1.groupby([g, 'name'])['val'].transform('sum')
print (df1)
name   a   b  val  sum_val
0     x   3   9    2        6
1     x   4   8    1        6
2     x   5   7    3        6
3     x  11  12    4        4
4     x  14  23    5       14
5     x  15  22    6       14
6     x  16  21    3       14
7     y   2   8   21       63
8     y   3   7   11       63
9     y   4   6   31       63
10    y  10  11   41       41
11    y  13  22   51      143
12    y  14  21   61      143
13    y  15  20   31      143