Question

我有一个数据集，我需要计算一个非常大的数据集的长度（65400行！）。当我们收集数据时，我们记录了我们的焦点动物在每分钟和第二次5分钟时间段内所做的事情。我的样本数据为

 structure(list(date = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L), .Label = "02/04/2015", class = "factor"), minute = c(1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L), sec = 1:11, activity = structure(c(2L, 
2L, 2L, 1L, 3L, 3L, 3L, 2L, 2L, 2L, 2L), .Label = c("N", "S", 
"U"), class = "factor"), day_time = structure(c(1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L), .Label = "14:45", class = "factor")), .Names = c("date", 
"minute", "sec", "activity", "day_time"), class = "data.frame", row.names = c(NA, 
-11L)) 

df
         date minute sec activity day_time
1  02/04/2015      1   1        S    14:45
2  02/04/2015      1   2        S    14:45
3  02/04/2015      1   3        S    14:45
4  02/04/2015      1   4        N    14:45
5  02/04/2015      1   5        U    14:45
6  02/04/2015      1   6        U    14:45
7  02/04/2015      1   7        U    14:45
8  02/04/2015      1   8        S    14:45
9  02/04/2015      1   9        S    14:45
10 02/04/2015      1  10        S    14:45
11 02/04/2015      1  11        S    14:45

我们需要计算的是每个回合的长度（以秒为单位）保持5分钟的会话分开。在这种情况下，我们所需的输出将是

structure(list(date = structure(c(1L, 1L, 1L, 1L), .Label = "02/04/2015", class = "factor"), 
        minute = c(1L, 1L, 1L, 1L), activity = structure(c(2L, 1L, 
        3L, 2L), .Label = c("N", "S", "U"), class = "factor"), day_time = structure(c(1L, 
        1L, 1L, 1L), .Label = "14:45", class = "factor"), bout_length = c(3L, 
        1L, 3L, 4L)), .Names = c("date", "minute", "activity", "day_time", 
    "bout_length"), class = "data.frame", row.names = c(NA, -4L))

desired output

            date minute activity day_time bout_length
    1 02/04/2015      1        S    14:45           3
    2 02/04/2015      1        N    14:45           1
    3 02/04/2015      1        U    14:45           3
    4 02/04/2015      1        S    14:45           4

我试过（rle）没有成功，因为我必须指定不同的分钟和会话。谢谢你的帮助

Answer 1

我终于顺其自然了。如果有一个很短的路可能会很好

bouts1 <- as.data.frame(lapply(df, as.character), stringsAsFactors = FALSE)
bouts1<-head(do.call(rbind, by(bouts1, df$session, rbind, "empty")), -1)
rownames(bouts1) <- seq(length=nrow(bouts1))# this renames row names in my dataframe
diffs <- bouts1$activity[-1L] != bouts1$activity[-length(bouts1$activity)]#tells us where the activity is diff
idx <- c(which(diffs), length(bouts1$activity))
bout.len<-diff(c(0, idx))
trial <- c(which(diffs=="TRUE"))#these are the row IDs that contain activities that change
new.bouts<-bouts1[row.names(bouts1) %in% trial,]# extracting the rows in the data where activity changes
temp<-bouts[65400,]#took the last observation from the main data set. 
new.bouts <- rbind(new.bouts,temp)#these 2 commands I had to create another line so that we get where to put e value
new.bouts$bout.len<-bout.len
new.bouts<-new.bouts[!new.bouts$Date=="empty",]

计算不同活动序列中的回合长度

1 个答案: