python - 使用 lambda、Pandas 添加 10 行

Question

我在以下形式的 pandas 中有一个数据框:

        column
0       0
1       1
2       3
3       6
4       10
5       15
6       21
7       28
8       36
9       45
10      55
11      66
12      78
13      91
14      105
15      120

任务是每 10 行求和并创建新列来求和。结果应该是这样的数据框:

        num     sum        Description(no need to add this column)
0       0       0          sum of numbers of rows of column "num" by indexes(0)
1       1       1          sum of numbers of rows of column "num" by indexes(0-1)
2       3       4          sum of numbers of rows of column "num" by indexes(0-2)
3       6       10         sum of numbers of rows of column "num" by indexes(0-3)
4       10      20         sum of numbers of rows of column "num" by indexes(0-4)
5       15      35         sum of numbers of rows of column "num" by indexes(0-5)
6       21      56         sum of numbers of rows of column "num" by indexes(0-6)
7       28      84         sum of numbers of rows of column "num" by indexes(0-7)
8       36      120        sum of numbers of rows of column "num" by indexes(0-8)
9       45      165        sum of numbers of rows of column "num" by indexes(0-9)
10      55      220        sum of numbers of rows of column "num" by indexes(1-10)
11      66      285        sum of numbers of rows of column "num" by indexes(2-11)
12      78      360        sum of numbers of rows of column "num" by indexes(3-12)
13      91      445        sum of numbers of rows of column "num" by indexes(4-13)
14      105     540        sum of numbers of rows of column "num" by indexes(5-14)
15      120     645        sum of numbers of rows of column "num" by indexes(6-15)

你能解释一下如何使用 lambda 吗？我试过使用 shift，但没用。

Answer 1

您可以使用 rolling .sum 与 min_periods = 1:

df['sum'] = df.column.rolling(10, min_periods=1).sum()
df