在 R 中使用 for 循环计算平均值

Question

This is what I have to do: Using a for loop calculate and store the mean lap time for each bike. The code below is how I tried to solve it. It gives me an error about some unexpected curly brackets and I don't know why. I must use a for loop (no tidyverse or any other package).

racing <- data.frame(Bike=rep(c("A1", "A2", "A3"), times=4),
                     Lap=rep(c(1,2,3,4), each=3),
                     Time=c(71,70,67,73,72,66,68,74,69,68,68,70))
for(bike in racing){
  if([racing$Bike=="A1",]){
    time_mean <- mean(racing$Time)
  }
  else if([racing$Bike=="A2",]){
    time_mean1 <- mean(racing$Time)
  }
  else{
    time_mean2 <- mean(racing$Time)
  }
}
lap_mean <- c(time_mean, time_mean1, time_mean2)
    

Error: unexpected '}' in "    }"

Answer 1

This can be made much simpler in one line using the tapply function:

> (lapmean<-tapply(racing$Time, racing$Bike, mean))
A1 A2 A3 
70 71 68 

Update:

I'm note sure why my post was voted down given that it requires way less typing and is more efficient than any other procedure posted here (22 times more efficient in comparison with the worst performing code). I ran execution times of all the other code submitted and here are the results in order of best to worst performers in terms of elapsed time in seconds:

1. My Code StatsStudent - .01 elapsed sec time using tictoc package
2. akrun (aggregate) - 0.03
3. Dan - 0.07
4. akrun (for loop) - 0.11
5. Duck - 0.22

Answer 2

We can use aggregate from base R

aggregate(Time ~ Bike, data = racing, FUN = mean)

-output

#   Bike Time
#1   A1   70
#2   A2   71
#3   A3   68

---

Or using for loop

unb <- unique(racing$Bike)
out <- c()
for(bike in unb) {
     out <- c(out, mean(subset(racing, Bike == bike, select = Time)$Time))
 }

setNames(out, unb)
#   A1 A2 A3  
# 70 71 68 

Answer 3

Try this. You can create a vector to store the bikes and then loop across it using subset() to filter the data and compute the mean time. Here the code:

#Data
racing <- data.frame(Bike=rep(c("A1", "A2", "A3"), times=4),
                     Lap=rep(c(1,2,3,4), each=3),
                     Time=c(71,70,67,73,72,66,68,74,69,68,68,70),stringsAsFactors = F)
#Bikes
vb <- unique(racing$Bike)
#Loop
vmeans <- numeric(length(vb))
for(i in 1:length(vb))
{
  #Data
  x <- subset(racing,Bike==vb[i])
  #Mean
  vmeans[i] <- mean(x$Time)
}
names(vmeans) <- vb

Output:

vmeans
A1 A2 A3 
70 71 68 

Answer 4

Using base-R, I think the below is very instructional:

results <- data.frame("Bike"=NA, "MeanTime"=NA)

for(i in unique(racing$Bike)) {
  tmp <- filter(racing, Bike == i)
  print(tmp) ;  print(mean(tmp$Time))
  
  results[match(i, unique(racing$Bike)),] <- c(i, mean(tmp$Time))
}
  print(results)

which gives the following:

>   print(results)
  Bike MeanTime
1   A1       70
2   A2       71
3   A3       68

on top of printing what the loop is doing