如果另一列中的值彼此相邻，则对数据框中的列值求和

Question

您好，我有一个数据框：

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”列中的数字彼此相邻，我希望对“val”列中的数字求和。例如。在“a”中，您有 3,4,5（彼此相邻），因此将它们在“val”列中的相关数字相加（即 2+1+3），然后创建一个新列，其中存在附加值.对我来说更难的是按“名称”对它们进行分组。

我不知道我解释得有多好，但这是我希望最终得到的数据框

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

通过比较差异与 lambda 函数中每组的累积总和来创建组，并将Series 传递给GroupBy.transform 和sum：

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