Question

我正在尝试为我的数据的每个块（层）提取第一条记录。我想在每个块中提取负值（Mag）的第一个外观以及相应的时间。然后我想比较那些＆＃34;次＆＃34;从每个块中找到最小值和最大值。（这是第一件事）

我来到某个地步但被困住了。任何帮助，包括缩短代码，将不胜感激。谢谢！

# to make sample data
data_neg<-seq(-0.98,-1,length=300)
data_pos<-seq(0.98,1,length=300)
time<-seq(1,54,length=600)

# binding those neg and pos numbers together
tot_num<- data.frame(c(rep(time, times=4)),c(rep(cbind(data_pos,data_neg),times=4)))    
colnames(tot_num)=c("time","Mag")

# split data into chunks
n <- 1:4  
dfchunk<- split(tot_num, factor(sort(rank(row.names(tot_num))%%n)))
ext_fsw<-lapply(dfchunk[],function(x)with(x,x[Mag<0,,drop=TRUE])) 
# here I want to exctract first appearance of negative value of Mag in each chunk together with corresponding time.

作为我问题的第二部分在@ zx8754建议之后我试图读取我的真实数据选择负值的第一个外观后进行循环并绘制结果。但我在实际数据中意识到有这样的N.A值（我从我的文件夹中读取了11个数据，因为你可以看到下面的代码......）

   X1      X2
1 27.45 -0.0111
2 43.29 -0.9746
3 32.49 -0.9807
4 28.08 -0.0538
5 28.44 -0.0669
 X1      X2
1 28.71 -0.0834
2 43.29 -0.9736
3 32.49 -0.9521
4 29.16 -0.0032
5 29.70 -0.0469
 X1      X2
1 30.06 -0.0112
2 43.29 -0.9724
3 35.37 -0.0448
4 33.03 -0.0308
5 31.59 -0.0055
 X1      X2
1 35.19 -0.0476
2 43.29 -0.9712
3 39.42 -0.0171
4 40.50 -0.0143
5 36.18 -0.0395
 X1      X2
1    NA      NA
2    NA      NA
3    NA      NA
4 50.85 -0.0371
5    NA      NA
   X1  X2
   1 NA      NA
2    NA      NA
3    NA      NA
4    NA      NA
5    NA      NA
   X1 X2
1    NA      NA
2    NA      NA
3    NA      NA
4    NA      NA
5    NA      NA
     X1     X2
1    NA     NA
2    NA     NA
3 49.77 -3e-04
4    NA     NA
5    NA     NA
     X1      X2
1    NA      NA
2    NA      NA
3    NA      NA
4 43.02 -0.0465
5 45.99 -0.9793
     X1      X2
1    NA      NA
2 37.98 -0.0005
3 45.18 -0.9784
4    NA      NA
5 45.09 -0.0551
     X1      X2
1    NA      NA
2    NA      NA
3 36.90 -0.0148
4 46.17 -0.9813
5    NA      NA

这里是循环读取我的数据

data.list <- dir(pattern = "*.avgm",full.names = FALSE) # creates the list    of all the csv files in the directory

a<-1:length(data.list)
for(k in 1:length(data.list)){
data1_stt<- read.table(data.list[k],colClasses="numeric",skip=0,   fill=FALSE, sep = "", quote="\"'", dec=".", as.is = TRUE, strip.white=FALSE)
StrL1<-data1_stt[,10]
time<-data1_stt[,1]*10^-3
tot_num<- data.frame(time,StrL1)
colnames(tot_num)=c("time","Mag")
n <- 5  # split data into chunks
dfchunk<- split(tot_num, factor(sort(rank(row.names(tot_num))%%n)))
ext_fsw<-lapply(dfchunk,function(x)x[which(x$Mag<0)[1],])#which - gives the index where the conditions is TRUE, then take the 1st value [1], pass it to x as index for rownumber.
x.n <- data.frame(matrix(unlist(ext_fsw),nrow=5, byrow=T))
print(x.n)
curr<-rep(c(8,7,6,5,4,3.6,3.8,4.2,4.4,4.6,4.8),each=5)
plot(curr,x.n,pch = 20) 
}

简而言之，我的任务的第二步是阅读我的所有数据并为其绘制每个curr值。但我没有那样做。很遗憾，我无法在此处提供可重复的示例。由于数据中存在N.A值，因此在长度值方面，长度不同。

Answer 1

试试这个：

ext_fsw<-lapply(dfchunk,function(x)
  x[which(x$Mag<0)[1],]
  )

which - 给出条件为TRUE的索引，然后取第一个值[1]，将其作为rownumber的索引传递给x。

根据变量

1 个答案: