这是我的数据框的样子;
Zaman Operasyon Paket
1 2013-01-18 21:39:00 installed linux-api-headers
2 2013-01-18 21:39:00 installed tzdata
3 2013-01-18 21:39:00 installed glibc
4 2013-01-18 21:39:00 installed ncurses
5 2013-01-18 21:39:00 installed readline
6 2013-01-18 21:39:00 installed bash
Zaman是POSIXct，其他2个colums是因素。我想计算每天分组的行数。我试过了，
> aggregate(data,by=list(data$Zaman),FUN=sum)
Error occured: Summary.POSIXct(c(1358537940, 1358537940, 1358537940, 1358537940, :
'sum' not defined for "POSIXt" objects
> aggregate(data,by=list(data$Zaman),FUN=count)
Error occured: match.fun(FUN) : Couldn't find 'count' object
我该怎么做？
dput(data)
dput(data)
structure(list(Zaman = structure(c(1358537940, 1358537940, 1358537940,
1358537940, 1358537940, 1358537940, 1358537940, 1358537940, 1358537940,
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1359224100), class = c("POSIXct", "POSIXt"), tzone = ""), Operasyon = structure(c(1L,
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"xz", "zip", "zlib", "zsh", "zvbi"), class = "factor")), .Names = c("Zaman",
"Operasyon", "Paket"), row.names = c(NA, -730L), class = "data.frame")
答案 0 :(得分：5)
您必须表示您想要天;这应该可以解决问题：
table(factor(format(data$Zaman,"%D")))
答案 1 :(得分：3)
使用cut，它具有处理日期的内置支持：
attributes(data$Zaman)$tzone <- "GMT"
table(cut(data$Zaman, "1 day"))
#
# 2013-01-18 2013-01-19 2013-01-20 2013-01-21 2013-01-22 2013-01-23 2013-01-24 2013-01-25 2013-01-26
# 339 209 20 8 76 56 0 10 12
table(cut(data$Zaman, "2 days"))
#
# 2013-01-18 2013-01-20 2013-01-22 2013-01-24 2013-01-26
# 548 28 132 10 12
答案 2 :(得分：3)
我偏爱这些任务的data.table：
library(data.table)
dt <- as.data.table(df)
dt[,days:=format(Zaman,"%d.%m.%Y")]
dt[,.N,by=days]
days N
1: 18.01.2013 133
2: 19.01.2013 415
3: 20.01.2013 20
<snip>
答案 3 :(得分：1)
由于没有名为count的函数。
但您可以使用count plyr个包裹：
count(dat, vars = 'Zaman')
Zaman freq
1 2013-01-18 20:39:00 66
2 2013-01-18 20:40:00 16
3 2013-01-18 20:41:00 47
4 2013-01-18 20:52:00 1
5 2013-01-18 23:47:00 1
6 2013-01-18 23:53:00 2
7 2013-01-19 00:04:00 68
8 2013-01-19 00:05:00 9
9 2013-01-19 00:06:00 4
10 2013-01-19 00:08:00 3
11 2013-01-19 00:11:00 9
12 2013-01-19 00:14:00 1
13 2013-01-19 00:19:00 89
14 2013-01-19 00:20:00 9
答案 4 :(得分：0)
也许您只是在寻找length函数？
> aggregate(data,by=list(data$zaman),FUN=length)
Group.1 zaman oper paket
1 2013-01-18 21:39:00 6 6 6