R 聚合函数生成每日平均值，而不是每小时平均值

我有一个data.frame，第一列中有15分钟的时间步长，还有16列数据。我想得到每列每小时的平均值。我使用的是聚合，对于1分钟的数据，它工作得非常好

mydata <- list()
for(j in colnames(data_frame)){
  data_mean <- aggregate(data_frame[j], 
                        list(hour=cut(as.POSIXct(data_frame$TIME), "hour")),
                        mean, na.rm=TRUE)
  mydata[[j]] <- data_mean
}

对于15分钟的数据：

"TIME","Tair","RH"
2016-01-01 00:01:00,5.9,82
2016-01-01 00:02:00,5.9,82
2016-01-01 00:03:00,5.9,82
2016-01-01 00:04:00,5.89,82
2016-01-01 00:05:00,5.8,82
2016-01-01 00:06:00,5.8,82
2016-01-01 00:07:00,5.8,82
2016-01-01 00:08:00,5.8,82
2016-01-01 00:09:00,5.8,82
2016-01-01 00:10:00,5.8,82
2016-01-01 00:11:00,5.8,82
2016-01-01 00:12:00,5.8,82
2016-01-01 00:13:00,5.8,82
2016-01-01 00:14:00,5.8,82
2016-01-01 00:15:00,5.8,82
2016-01-01 00:16:00,5.8,82
2016-01-01 00:17:00,5.8,82
2016-01-01 00:18:00,5.8,82
2016-01-01 00:19:00,5.8,82
2016-01-01 00:20:00,5.8,82
2016-01-01 00:21:00,5.75,82
2016-01-01 00:22:00,5.78,82
2016-01-01 00:23:00,5.78,83
2016-01-01 00:24:00,5.8,82
2016-01-01 00:25:00,5.73,82
2016-01-01 00:26:00,5.7,82
2016-01-01 00:27:00,5.7,82
2016-01-01 00:28:00,5.7,82
2016-01-01 00:29:00,5.7,82
2016-01-01 00:30:00,5.7,82
2016-01-01 00:31:00,5.7,83
2016-01-01 00:32:00,5.76,83
2016-01-01 00:33:00,5.8,83
2016-01-01 00:34:00,5.8,82
2016-01-01 00:35:00,5.8,82
2016-01-01 00:36:00,5.8,83
2016-01-01 00:37:00,5.79,83
2016-01-01 00:38:00,5.7,82

"TIME","Tair","RH"
2016-01-01 00:15:00,6.228442,80.40858
2016-01-01 00:30:00,6.121088,81.00000
2016-01-01 00:45:00,6.075000,NA
2016-01-01 01:00:00,5.951910,NA
2016-01-01 01:15:00,5.844144,NA
2016-01-01 01:30:00,5.802242,NA
2016-01-01 01:45:00,5.747619,NA
2016-01-01 02:00:00,5.742889,NA
2016-01-01 02:15:00,5.752584,81.12135
2016-01-01 02:30:00,5.677753,81.00000
2016-01-01 02:45:00,5.500224,81.61435
2016-01-01 03:00:00,5.225282,82.29797
2016-01-01 03:15:00,5.266441,83.00000
2016-01-01 03:30:00,5.200448,83.32584
2016-01-01 03:45:00,5.098876,84.00000
2016-01-01 04:00:00,5.081061,83.76894
2016-01-01 04:15:00,5.230769,82.88664
2016-01-01 04:30:00,5.300000,82.06742
2016-01-01 04:45:00,5.300000,NA
2016-01-01 05:00:00,5.399776,NA

---

你的代码对我有用

但是，您的循环有点浪费，因为它为data.frame的每一列重复计算

TIME

列的切分。你可以预先计算，但有更好的解决方案

只需一次调用

aggregate（）

，就可以以更简单、更传统、更有用的形式生成相同的结果：

数据

df1 <- data.frame(TIME=as.POSIXct(c('2016-01-01 00:01:00','2016-01-01 00:02:00',
'2016-01-01 00:03:00','2016-01-01 00:04:00','2016-01-01 00:05:00','2016-01-01 00:06:00',
'2016-01-01 00:07:00','2016-01-01 00:08:00','2016-01-01 00:09:00','2016-01-01 00:10:00',
'2016-01-01 00:11:00','2016-01-01 00:12:00','2016-01-01 00:13:00','2016-01-01 00:14:00',
'2016-01-01 00:15:00','2016-01-01 00:16:00','2016-01-01 00:17:00','2016-01-01 00:18:00',
'2016-01-01 00:19:00','2016-01-01 00:20:00','2016-01-01 00:21:00','2016-01-01 00:22:00',
'2016-01-01 00:23:00','2016-01-01 00:24:00','2016-01-01 00:25:00','2016-01-01 00:26:00',
'2016-01-01 00:27:00','2016-01-01 00:28:00','2016-01-01 00:29:00','2016-01-01 00:30:00',
'2016-01-01 00:31:00','2016-01-01 00:32:00','2016-01-01 00:33:00','2016-01-01 00:34:00',
'2016-01-01 00:35:00','2016-01-01 00:36:00','2016-01-01 00:37:00','2016-01-01 00:38:00')),
Tair=c(5.9,5.9,5.9,5.89,5.8,5.8,5.8,5.8,5.8,5.8,5.8,5.8,5.8,5.8,5.8,5.8,5.8,5.8,5.8,5.8,5.75,
5.78,5.78,5.8,5.73,5.7,5.7,5.7,5.7,5.7,5.7,5.76,5.8,5.8,5.8,5.8,5.79,5.7),RH=c(82L,82L,82L,
82L,82L,82L,82L,82L,82L,82L,82L,82L,82L,82L,82L,82L,82L,82L,82L,82L,82L,82L,83L,82L,82L,82L,
82L,82L,82L,82L,83L,83L,83L,82L,82L,83L,83L,82L));

df15 <- data.frame(TIME=as.POSIXct(c('2016-01-01 00:15:00','2016-01-01 00:30:00',
'2016-01-01 00:45:00','2016-01-01 01:00:00','2016-01-01 01:15:00','2016-01-01 01:30:00',
'2016-01-01 01:45:00','2016-01-01 02:00:00','2016-01-01 02:15:00','2016-01-01 02:30:00',
'2016-01-01 02:45:00','2016-01-01 03:00:00','2016-01-01 03:15:00','2016-01-01 03:30:00',
'2016-01-01 03:45:00','2016-01-01 04:00:00','2016-01-01 04:15:00','2016-01-01 04:30:00',
'2016-01-01 04:45:00','2016-01-01 05:00:00')),Tair=c(6.228442,6.121088,6.075,5.95191,
5.844144,5.802242,5.747619,5.742889,5.752584,5.677753,5.500224,5.225282,5.266441,5.200448,
5.098876,5.081061,5.230769,5.3,5.3,5.399776),RH=c(80.40858,81,NA,NA,NA,NA,NA,NA,81.12135,81,
81.61435,82.29797,83,83.32584,84,83.76894,82.88664,82.06742,NA,NA));

---

df1好的，我发现了问题。由于某种原因，聚合中的
as.Posixct（）
导致了问题。如果在调用aggregate之前创建Posixct，它就会工作。Thx适用于更短更快的版本！
df1 <- data.frame(TIME=as.POSIXct(c('2016-01-01 00:01:00','2016-01-01 00:02:00',
'2016-01-01 00:03:00','2016-01-01 00:04:00','2016-01-01 00:05:00','2016-01-01 00:06:00',
'2016-01-01 00:07:00','2016-01-01 00:08:00','2016-01-01 00:09:00','2016-01-01 00:10:00',
'2016-01-01 00:11:00','2016-01-01 00:12:00','2016-01-01 00:13:00','2016-01-01 00:14:00',
'2016-01-01 00:15:00','2016-01-01 00:16:00','2016-01-01 00:17:00','2016-01-01 00:18:00',
'2016-01-01 00:19:00','2016-01-01 00:20:00','2016-01-01 00:21:00','2016-01-01 00:22:00',
'2016-01-01 00:23:00','2016-01-01 00:24:00','2016-01-01 00:25:00','2016-01-01 00:26:00',
'2016-01-01 00:27:00','2016-01-01 00:28:00','2016-01-01 00:29:00','2016-01-01 00:30:00',
'2016-01-01 00:31:00','2016-01-01 00:32:00','2016-01-01 00:33:00','2016-01-01 00:34:00',
'2016-01-01 00:35:00','2016-01-01 00:36:00','2016-01-01 00:37:00','2016-01-01 00:38:00')),
Tair=c(5.9,5.9,5.9,5.89,5.8,5.8,5.8,5.8,5.8,5.8,5.8,5.8,5.8,5.8,5.8,5.8,5.8,5.8,5.8,5.8,5.75,
5.78,5.78,5.8,5.73,5.7,5.7,5.7,5.7,5.7,5.7,5.76,5.8,5.8,5.8,5.8,5.79,5.7),RH=c(82L,82L,82L,
82L,82L,82L,82L,82L,82L,82L,82L,82L,82L,82L,82L,82L,82L,82L,82L,82L,82L,82L,83L,82L,82L,82L,
82L,82L,82L,82L,83L,83L,83L,82L,82L,83L,83L,82L));

df15 <- data.frame(TIME=as.POSIXct(c('2016-01-01 00:15:00','2016-01-01 00:30:00',
'2016-01-01 00:45:00','2016-01-01 01:00:00','2016-01-01 01:15:00','2016-01-01 01:30:00',
'2016-01-01 01:45:00','2016-01-01 02:00:00','2016-01-01 02:15:00','2016-01-01 02:30:00',
'2016-01-01 02:45:00','2016-01-01 03:00:00','2016-01-01 03:15:00','2016-01-01 03:30:00',
'2016-01-01 03:45:00','2016-01-01 04:00:00','2016-01-01 04:15:00','2016-01-01 04:30:00',
'2016-01-01 04:45:00','2016-01-01 05:00:00')),Tair=c(6.228442,6.121088,6.075,5.95191,
5.844144,5.802242,5.747619,5.742889,5.752584,5.677753,5.500224,5.225282,5.266441,5.200448,
5.098876,5.081061,5.230769,5.3,5.3,5.399776),RH=c(80.40858,81,NA,NA,NA,NA,NA,NA,81.12135,81,
81.61435,82.29797,83,83.32584,84,83.76894,82.88664,82.06742,NA,NA));