尽管经历了许多关于Stackoverflow的话题和评论，但我找不到这个问题的答案。希望在这里得到答复。谢谢。
让我们说我们有一个像这样的数据框：
> my_data
year month day pr max min
1 2081 1 1 5.569092e-04 -26.4920749 -24.483246
2 2081 1 2 1.777802e-04 -25.9205721 -20.451972
3 2081 1 3 1.323720e-03 -27.1527253 -10.395930
4 2081 1 4 2.137142e-03 -20.8107204 -9.002432
5 2081 1 5 7.505645e-04 -16.2825782 -8.997454
6 2081 1 6 2.812341e-03 -8.4525805 -8.973068
7 2081 1 7 3.484746e-03 -0.3836075 -16.055945
8 2081 1 8 4.613059e-04 -0.2103037 -25.410168
9 2081 1 9 7.486442e-04 -3.7030182 -27.551599
10 2081 1 10 3.175442e-03 -1.5308754 -27.882620
11 2081 1 11 2.399104e-03 -5.9834657 -24.491168
12 2081 1 12 1.833119e-03 -13.7263921 -22.745234
13 2081 1 13 3.315489e-04 -18.3818204 -22.640128
14 2081 1 14 1.180063e-04 -18.6430621 -17.468890
15 2081 1 15 2.493895e-05 -15.5209717 -16.186150
16 2081 1 16 6.260483e-05 -15.8603685 -11.547591
17 2081 1 17 2.280691e-04 -10.4212179 -7.414533
18 2081 1 18 5.984287e-04 -7.9375899 -7.400936
19 2081 1 19 7.078201e-04 -7.3717562 -13.400183
20 2081 1 20 2.017283e-03 -5.7114717 -17.213636
21 2081 1 21 9.261695e-04 -4.0757166 -18.174468
22 2081 1 22 1.107990e-03 -4.7120487 -18.968903
23 2081 1 23 1.698175e-03 -7.0420167 -17.654700
24 2081 1 24 1.468677e-03 -11.8686058 -12.688654
25 2081 1 25 5.597740e-04 -11.5570338 -9.391358
26 2081 1 26 2.446489e-04 -10.5752366 -8.349224
27 2081 1 27 1.485243e-04 -8.6466939 -7.059217
28 2081 1 28 4.694722e-04 -6.1383411 -12.353198
29 2081 1 29 3.802654e-04 -2.1109669 -15.652165
30 2081 1 30 9.396260e-04 -0.1226451 -19.592908
31 2081 1 31 2.871977e-03 -0.7997992 -22.973038
我想为每行中的 max 创建一个新值，其中 max 小于等于 min 。
我正在使用以下代码：
for (i in 1:nrow(my_data)) {
# Replace the max with the Mean of max in row i to i+10:
my_data$max[my_data$max <= my_data$min] <- mean(my_data$max[i:(i+10)])
}
但是答案将是：
> head(my_data)
year month day pr max min
1 2081 1 1 0.0005569092 -12.447502 -24.483246
2 2081 1 2 0.0001777802 -12.447502 -20.451972
3 2081 1 3 0.0013237197 -7.616386 -10.395930
4 2081 1 4 0.0021371418 -7.616386 -9.002432
5 2081 1 5 0.0007505645 -7.616386 -8.997454
6 2081 1 6 0.0028123409 -8.452581 -8.973068
没有没有任何意义。
必须类似于：
year month day pr max min
1 2081 1 1 0.0005569092 -12.447502 -24.483246
2 2081 1 2 0.0001777802 -11.286985 -20.451972
3 2081 1 3 0.0013237197 -10.601644 -10.395930
4 2081 1 4 0.0021371418 -9.8280386 -9.002432
5 2081 1 5 0.0007505645 -9.3471523 -8.997454
6 2081 1 6 0.0028123409 -9.3087696 -8.973068
您的意见或答案将不胜感激。
编辑：
如果我们使用Excel，这将是整个预期结果：
year month day pr max min
1 2081 1 1 0.000556909 -12.4475020 -24.483246
2 2081 1 2 0.000177780 -11.2869854 -20.451972
3 2081 1 3 0.001323720 -10.6016443 -10.395930
4 2081 1 4 0.002137142 -9.8280386 -9.002432
5 2081 1 5 0.000750565 -9.3471523 -8.997454
6 2081 1 6 0.002812341 -8.4525805 -8.973068
7 2081 1 7 0.003484746 -0.3836075 -16.055945
8 2081 1 8 0.000461306 -0.2103037 -25.410168
9 2081 1 9 0.000748644 -3.7030182 -27.551599
10 2081 1 10 0.003175442 -1.5308754 -27.882620
11 2081 1 11 0.002399104 -5.9834657 -24.491168
12 2081 1 12 0.001833119 -13.7263921 -22.745234
13 2081 1 13 0.000331549 -18.3818204 -22.640128
14 2081 1 14 0.000118006 -9.9240751 -17.468890
15 2081 1 15 0.000024900 -15.5209717 -16.186150
16 2081 1 16 0.000062600 -8.8302784 -11.547591
17 2081 1 17 0.000228069 -8.1744898 -7.414533
18 2081 1 18 0.000598429 -7.7851374 -7.400936
19 2081 1 19 0.000707820 -7.3717562 -13.400183
20 2081 1 20 0.002017283 -5.7114717 -17.213636
21 2081 1 21 0.000926170 -4.0757166 -18.174468
22 2081 1 22 0.001107990 -4.7120487 -18.968903
23 2081 1 23 0.001698175 -7.0420167 -17.654700
24 2081 1 24 0.001468677 -11.8686058 -12.688654
25 2081 1 25 0.000559774 -5.7072452 -9.391358
26 2081 1 26 0.000244649 -4.7322805 -8.349224
27 2081 1 27 0.000148524 -3.5636892 -7.059217
28 2081 1 28 0.000469472 -6.1383411 -12.353198
29 2081 1 29 0.000380265 -2.1109669 -15.652165
30 2081 1 30 0.000939626 -0.1226451 -19.592908
31 2081 1 31 0.002871977 -0.7997992 -22.973038
答案 0 :(得分：3)
只需遍历序列并分配
v1 <- sapply(seq_len(nrow(my_data)), function(i)
mean(my_data$max[i:(min(nrow(my_data), (i+10)))]))
i1 <- with(my_data, max <= min)
my_data$max[i1] <- v1[i1]
# year month day pr max min
#1 2081 1 1 5.569092e-04 -12.4475020 -24.483246
#2 2081 1 2 1.777802e-04 -11.2869854 -20.451972
#3 2081 1 3 1.323720e-03 -10.6016443 -10.395930
#4 2081 1 4 2.137142e-03 -9.8280386 -9.002432
#5 2081 1 5 7.505645e-04 -9.3471523 -8.997454
#6 2081 1 6 2.812341e-03 -8.4525805 -8.973068
#7 2081 1 7 3.484746e-03 -0.3836075 -16.055945
#8 2081 1 8 4.613059e-04 -0.2103037 -25.410168
#9 2081 1 9 7.486442e-04 -3.7030182 -27.551599
#10 2081 1 10 3.175442e-03 -1.5308754 -27.882620
#11 2081 1 11 2.399104e-03 -5.9834657 -24.491168
#12 2081 1 12 1.833119e-03 -13.7263921 -22.745234
#13 2081 1 13 3.315489e-04 -18.3818204 -22.640128
#14 2081 1 14 1.180063e-04 -9.9240751 -17.468890
#15 2081 1 15 2.493895e-05 -15.5209717 -16.186150
#16 2081 1 16 6.260483e-05 -8.8302784 -11.547591
#17 2081 1 17 2.280691e-04 -8.1744898 -7.414533
#18 2081 1 18 5.984287e-04 -7.7851374 -7.400936
#19 2081 1 19 7.078201e-04 -7.3717562 -13.400183
#20 2081 1 20 2.017283e-03 -5.7114717 -17.213636
#21 2081 1 21 9.261695e-04 -4.0757166 -18.174468
#22 2081 1 22 1.107990e-03 -4.7120487 -18.968903
#23 2081 1 23 1.698175e-03 -7.0420167 -17.654700
#24 2081 1 24 1.468677e-03 -11.8686058 -12.688654
#25 2081 1 25 5.597740e-04 -5.7072452 -9.391358
#26 2081 1 26 2.446489e-04 -4.7322805 -8.349224
#27 2081 1 27 1.485243e-04 -3.5636892 -7.059217
#28 2081 1 28 4.694722e-04 -6.1383411 -12.353198
#29 2081 1 29 3.802654e-04 -2.1109669 -15.652165
#30 2081 1 30 9.396260e-04 -0.1226451 -19.592908
#31 2081 1 31 2.871977e-03 -0.7997992 -22.973038