How to use for loop in R

Question

I have a CSV dataset (call it data) as follow:

CLASS      CoverageT1      CoverageT2       CoverageT3
Gamma      90              80               75
Gamma      89              72               79
Gamma      92              86               75
Alpha      50              80               67
Alpha      53              78               60
Alpha      58              81               75

I would like to retrieve the unique classes and calculate the average for each coverage column.

What I've done so far is the following:

classes <- subset(data, select = c(CLASS))
unique_classes <- unique(classes)

for(x in unique_classes){
  cove <- subset(data, CLASS == x , select=c(CoverageT1:CoverageT3))
  average <- colMeans(cove)
  print(cove)
}

As a result, I got the following results:

   CoverageT1    CoverageT2    CoverageT3
1  90            80            75
3  92            86            75
4  50            80            67
6  58            81            75

I want to retrieve the coverage values based on each class and then calculate the average. When I print the retrieved coverage values, I get some rows and the other are missing!

Can someone help me solving this issue

Thanks

Richard Telford · Accepted Answer · 2016-11-20 18:45:01Z

4

Your code isn't working because, amongst other things, you are assigning to average on each iteration and the previous is lost

There are several ways to do what you are trying to do. This would be my approach:

library(dplyr) 

data %>% group_by(CLASS) %>% summarise_all(mean)

answered Nov 20, 2016 at 18:45

Richard Telford

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Kipras Kančys · Accepted Answer · 2016-11-20 18:56:50Z

4

Another option using aggregate

aggregate(data, . ~ CLASS , mean)

edited Nov 20, 2016 at 18:56

answered Nov 20, 2016 at 18:48

Kipras Kančys

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2 Comments

Roman Luštrik Over a year ago

Grrr, tried aggregate(CoverageT1 + CoverageT2 + CoverageT3 ~ CLASS, data = xy, FUN = mean) and it didn't work. Didn't think of using the dot notation...

Kipras Kančys Over a year ago

In case of more than one variable on left side you can do cbind. aggregate(cbind(CoverageT1, CoverageT2, CoverageT3) ~ CLASS, data = xy, FUN = mean) In this case when all variables are used dot notation works as well.

Roman Luštrik · Accepted Answer · 2016-11-20 18:44:06Z

2

Taking your idea and wrapping it in by.

xy <- read.table(text = "CLASS      CoverageT1      CoverageT2       CoverageT3
Gamma      90              80               75
                 Gamma      89              72               79
                 Gamma      92              86               75
                 Alpha      50              80               67
                 Alpha      53              78               60
                 Alpha      58              81               75", header = TRUE)


out <- by(data = xy[, -1], INDICES = list(xy$CLASS), FUN = colMeans)
out <- do.call(rbind, out)
out

      CoverageT1 CoverageT2 CoverageT3
Alpha   53.66667   79.66667   67.33333
Gamma   90.33333   79.33333   76.33333

answered Nov 20, 2016 at 18:44

Roman Luštrik

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Comments

Nasser · Accepted Answer · 2016-11-25 17:10:53Z

1

This is how I solved it:

coverage_all <- aggregate(coverage , list(class=data$CLASS), mean)

answered Nov 25, 2016 at 17:10

Nasser

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