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在时间间隙插入NA

na time-series plot r

Vint · 技术社区 · 6 年前

我有一个时间序列数据集,我正试图绘制出来,但时间序列有很大的数据间隙。当绘制这个数据集时,r用一条直线在这些间隙上绘制,我更希望最终的绘制不在这些数据间隙上绘制。我知道的唯一解决方法是在数据集中的间隙之间手动插入一行na。为此,我编写了一个循环遍历数据帧的函数。这个函数可以工作,但是运行起来非常慢。

#Define Function to Insert NA in long stretches so don't plot line 

PlotSpace<-function(DF){

NROW<-nrow(DF)
for(t in seq(1:NROW)){

TimeDiff<-difftime(DF$TimeStamp[t+1], DF$TimeStamp[t], units = "hours") 
DF[t,"TimeDiff"]<-TimeDiff  

if( !is.na(TimeDiff) & TimeDiff > 5 ){

    NewTimeStamp<-DF$TimeStamp[t] + 1
    NewProfStamp<-DF$ProfStamp[t] + 1
    print(NewTimeStamp)
    DF<-rbind(DF,NA) #Add last row that is NA
    DF[nrow(DF),'TimeStamp']<-NewTimeStamp
    DF[nrow(DF),'ProfStamp']<-NewProfStamp




    }
}

DF <- DF[order(DF$TimeStamp),]
DF<-DF[-1,]
DF$TimeStamp<-as.POSIXct(DF$TimeStamp)

return(DF)

}

有没有更有效的方法在r中实现这一点?

示例数据:

 TimeStamp<-c("2015-05-01 10:00:00","2015-05-01 10:05:00","2015-05-01 10:10:00","2015-05-01 10:15:00",
"2015-05-01 10:20:00","2015-05-01 15:00:00","2015-05-01 15:05:00","2015-05-01 15:10:00"
,"2015-05-01 15:20:00","2015-05-01 15:30:00","2015-05-01 15:35:00")

Data<-c(1,2,3,4,5,3,7,8,9,2,11)

DF<-data.frame(TimeStamp, Data)

DF$TimeStamp<-as.POSIXct(DF$TimeStamp)

plot(DF$TimeStamp, DF$Data, type='l')

如您所见,上面的图表绘制了7小时数据间隔之间的一条线。我想在任何时间间隔大于2小时插入NA。阿卡

             TimeStamp Data
1  2015-05-01 10:00:00    1
2  2015-05-01 10:05:00    2
3  2015-05-01 10:10:00    3
4  2015-05-01 10:15:00    4
5  2015-05-01 10:20:00    5
   2015-05-01 10:21:00    NA
6  2015-05-01 15:00:00    3
7  2015-05-01 15:05:00    7
8  2015-05-01 15:10:00    8
9  2015-05-01 15:20:00    9
10 2015-05-01 15:30:00    2
11 2015-05-01 15:35:00   11

1 回复 | 直到 6 年前

IceCreamToucan 6 年前

library(data.table)
setDT(DF)

# Create indicator for time gap
DF[, gap := c(diff(TimeStamp) > 2*60, F)]
# If there's a gap, add a new row
DF[, if(gap) rbind(.SD, .(TimeStamp = TimeStamp + 60), fill = T)
     else .SD
   , by = 1:nrow(DF)
   ][, -'gap']
#               TimeStamp Data
#  1: 2015-05-01 10:00:00    1
#  2: 2015-05-01 10:05:00    2
#  3: 2015-05-01 10:10:00    3
#  4: 2015-05-01 10:15:00    4
#  5: 2015-05-01 10:20:00    5
#  6: 2015-05-01 10:21:00   NA
#  7: 2015-05-01 15:00:00    3
#  8: 2015-05-01 15:05:00    7
#  9: 2015-05-01 15:10:00    8
# 10: 2015-05-01 15:20:00    9
# 11: 2015-05-01 15:30:00    2
# 12: 2015-05-01 15:35:00   11