我有这段代码来获取热波（连续的日期（按日期），最高和最低温度更高或=第90个分位数），然后获取每个热波的平均温度。
library(data.table)
setDT(df1)
df1[, hotday := +(df1$MAX>=(quantile(df1$MAX,.90, na.rm = T, type = 6)) & df1$MIN>=(quantile(df$MIN,.90, na.rm = T, type = 6)))
] [, length := with(rle(hotday), rep(lengths,lengths)) # to calculate lenght so I can select consecutive days only
] [hotday==0, length:=0][!!hotday, Highest_Mean := max(MEAN) , rleid(length)][] # to find the highest Mean temp for each consecutive group
现在，此代码适用于具有一个站的df（df1）：
head(df1)
YEAR MONTH DAY Date MEAN TMAX TMIN
1 1965 1 1 1/1/1965 NA 27.0 17.0
2 1965 1 2 1/2/1965 24.0 28.0 20.7
3 1965 1 3 1/3/1965 19.9 23.7 16.2
4 1965 1 4 1/4/1965 18.0 23.4 12.0
5 1965 1 5 1/5/1965 19.7 24.0 14.0
6 1965 1 6 1/6/1965 18.6 24.0 13.0
and would like to run it for a df (df2) that has about 1005 stations like this:
head(df2) # an example
x y date Tmaxq90 Tmax Tminq85 Tmin
34.000 33.000 5/25/1998 295.887 296.857 295.016 296.765
34.000 33.000 5/26/1998 295.887 296.778 295.016 296.702
34.000 33.000 5/27/1998 295.887 296.442 295.016 297.233
34.000 33.000 5/28/1998 295.887 293.971 295.016 296.923
34.000 33.000 5/29/1998 295.887 294.018 295.016 293.871
34.000 33.000 5/30/1998 295.887 293.910 295.016 293.746
34.000 33.000 5/31/1998 295.887 298.767 295.016 300.565
35.125 33.000 5/1/1989 301.084 302.898 298.897 299.553
35.125 33.000 5/2/1989 301.084 302.903 298.897 299.801
35.125 33.000 5/3/1989 301.084 299.393 298.897 297.521
35.125 33.000 5/4/1989 301.084 301.485 298.897 299.998
35.125 33.000 5/5/1989 301.084 295.539 298.897 295.085
35.125 33.000 5/6/1989 301.084 292.740 298.897 292.282
35.125 33.000 5/7/1989 301.084 292.150 298.897 291.397
35.125 33.000 5/8/1989 301.084 293.541 298.897 292.617
35.125 33.000 5/9/1989 301.084 294.249 298.897 293.766
35.125 33.000 5/10/1989 301.084 293.966 298.897 293.470
35.125 33.000 5/11/1989 301.084 292.951 298.897 291.870
35.125 33.000 5/12/1989 301.084 294.441 298.897 293.631
35.125 33.000 5/13/1989 301.084 296.407 298.897 295.729
35.125 33.000 5/14/1989 301.084 303.836 298.897 299.863
35.125 33.000 5/15/1989 301.084 303.290 298.897 302.021
35.125 33.000 5/16/1989 301.084 305.929 298.897 302.519
35.125 33.000 5/17/1989 301.084 303.316 298.897 301.235
35.125 33.000 5/18/1989 301.084 299.501 298.897 298.803
35.125 33.000 5/19/1989 301.084 302.325 298.897 299.509
35.125 33.000 5/20/1989 301.084 302.769 298.897 302.178
35.125 33.000 5/21/1989 301.084 303.988 298.897 301.407
35.125 33.000 5/22/1989 301.084 300.546 298.897 299.280
35.125 33.000 5/23/1989 301.084 295.673 298.897 295.154
35.125 33.000 5/24/1989 301.084 296.452 298.897 295.916
35.125 33.000 5/25/1989 301.084 295.904 298.897 295.585
35.125 33.000 5/26/1989 301.084 295.532 298.897 294.625
35.250 33.000 5/23/1990 299.237 296.108 296.897 299.145
35.250 33.000 5/24/1990 299.237 296.298 296.897 299.140
35.250 33.000 5/25/1990 299.237 298.298 296.897 297.466
35.250 33.000 5/26/1990 299.237 300.516 296.897 299.670
35.250 33.000 5/27/1990 299.237 303.569 296.897 301.019
35.250 33.000 5/28/1990 299.237 301.090 296.897 300.419
35.250 33.000 5/29/1990 299.237 299.757 296.897 299.138
35.250 33.000 5/30/1990 299.237 300.233 296.897 299.204
35.250 33.000 5/31/1990 299.237 301.268 296.897 300.429
35.250 33.000 5/1/1991 299.237 291.746 296.897 291.408
35.250 33.000 5/2/1991 299.237 292.045 296.897 290.981
35.250 33.000 5/3/1991 299.237 293.270 296.897 292.417
35.250 33.000 5/4/1991 299.237 296.360 296.897 295.466
35.250 33.000 5/5/1991 299.237 300.263 296.897 298.036
35.250 33.000 5/6/1991 299.237 301.099 296.897 298.810
35.250 33.000 5/7/1991 299.237 298.764 296.897 297.550
35.250 33.000 5/8/1991 299.237 304.438 296.897 301.194
35.250 33.000 5/9/1991 299.237 295.781 296.897 299.455
35.250 33.000 5/10/1991 299.237 296.701 296.897 300.393
35.250 33.000 5/11/1991 299.237 297.779 296.897 299.184
35.500 33.000 5/12/1991 299.237 300.330 297.897 299.254
35.500 33.000 5/13/1991 299.237 299.714 297.897 299.074
35.500 33.000 5/14/1991 299.237 299.751 297.897 298.759
35.500 33.000 5/15/1991 299.237 304.703 297.897 301.440
35.500 33.000 5/16/1991 299.237 293.104 297.897 292.175
35.500 33.000 5/17/1991 299.237 293.706 297.897 293.228
35.500 33.000 5/18/1991 299.237 294.243 297.897 293.336
35.500 33.000 5/19/1991 299.237 296.941 297.897 296.350
35.500 33.000 5/20/1991 299.237 296.482 297.897 295.638
35.500 33.000 5/21/1991 299.237 292.741 297.897 292.402
35.500 33.000 5/22/1991 299.237 293.129 297.897 292.516
35.500 33.000 5/23/1991 299.237 294.424 297.897 293.436
35.500 33.000 5/24/1991 299.237 295.830 297.897 294.658
35.500 33.000 5/25/1991 299.237 298.135 297.897 296.773
35.500 33.000 5/26/1991 299.237 295.076 297.897 294.366
35.500 33.000 5/27/1991 299.237 292.145 297.897 291.631
35.500 33.000 5/28/1991 299.237 292.971 297.897 292.263
here作为CSV文件提供了数据示例
df2中的每个站都有自己的x和y（lon和lat），并且记录了10357天。 有没有一种方法可以为每个工作站运行代码
答案 0 :(得分：1)
通常，如果您提供一个最小的示例（我们可以用来重现您的问题），则帮助会更容易。
对于此类问题，dplyr软件包可以提供帮助。假设您有一个station_id变量，该变量唯一地标识了以以下内容开头的电台
library(dplyr)
df2 %>%
by_group(station_id) %>%
... ## dplyr version of your old code