For loop R create and populate new column with output

Question

I've got a csv with some results. I want to loop over the results, run a power.prop.test and output the result for each row in a new column. So far I've got this:

data <- read.csv("Downloads/data.csv", sep = ",", header = TRUE)

for (i in 1:nrow(data)) {
  n <- power.prop.test( p1 = data[i,5], p2 = data[i,6], sig.level=.1, power = .8, alternative = "one.sided")
  data <- cbind(data, n[1])
}
head(data)

Rather than populating one column with the output, I'm looping through and creating a new column for ever power.prop.test I'm running. I'm binding a new column for each output instead of populating one column with each output. Issue is I'm not sure how to achieve the latter.

If anyone has any advice on how to consolidate these outputs into one column that would be great.

Thanks!

Create a new column in advance of the desired data type (e.g., data$output = 0), and then write data[i,'output'] = (relevant value) in the loop. — Max Candocia
– Max Candocia, Commented Jul 7, 2014 at 21:17
Just a head's up, read.csv("Downloads/data.csv") would be fine. You included the default values for sep and header — Rich Scriven
– Rich Scriven, Commented Jul 7, 2014 at 21:18
Power prop tests are described here: stat.ethz.ch/R-manual/R-patched/library/stats/html/… — Andy Clifton
– Andy Clifton, Commented Jul 7, 2014 at 21:20
@user2471446: You're looking for a new column per loop, right? I admit, I'm not sure if dplyr is able to do that, sorry. I'd love to see a solution using this package, though. — maj
– maj, Commented Jul 7, 2014 at 21:50
@user1362215: I'm very close your suggestion works, but i get the following error on 8th record "provided 8 variables to replace 1 variables". So it only populates column for first 8 rows. Thanks again for help. — user2471446
– user2471446, Commented Jul 7, 2014 at 21:55

rucker · Accepted Answer · 2014-07-07 23:54:51Z

6

Try this:

data <- read.csv("Downloads/data.csv", sep = ",", header = TRUE)

data$newcolumn <- 0

for (i in 1:nrow(data)) {
  n <- power.prop.test( p1 = data[i,5], p2 = data[i,6], sig.level=.1, power = .8, alternative = "one.sided")
  data$newcolumn[i] <- n
}
head(data)

I just added a new column, filled it with zeroes, and then added in the power.prop.test values one at a time as they are calculated.

answered Jul 7, 2014 at 23:54

rucker

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2 Comments

user2471446 Over a year ago

works like a charm, thanks. i ended up doing it slightly differently (see below) but this totally works.

user2471446 Over a year ago

small change, you need this: data$newcolumn[i] <- n[[1]], since n returns a list of 8 objects.

user2471446 · Accepted Answer · 2014-07-08 19:07:17Z

Thanks for all the help! Here's the solution I'm using for now:

# Read in csv of results
data <- read.csv("Downloads/data.csv")
data$obs=0
data$obs2=0
data$sig=0

# Create a loop to calculate required observations for each test based on CR,     Significance and Statistical Power
for (i in 1:nrow(data)) {
# Error handling: where CR are the same, cannot calculate n and fails, we skip these tests
  possibleError <- tryCatch(
      n <- power.prop.test( p1 = data[i,5], p2 = data[i,6], sig.level=.2, power = .8, alternative = "one.sided")
  ,error=function(e)e
  )
  if(!inherits(possibleError, "error")){
# Real work: calculate n, determine if bigger than actual observations, if not assign   sig = 0, otherwise =1
   n <- power.prop.test( p1 = data[i,5], p2 = data[i,6], sig.level=.2, power = .8,  alternative = "one.sided")
    data[i,'obs'] = n[[1]]
    data$obs2[i] = data$obs[i] * 2
    if(data$obs[i]*2 < data$Traffic[i]) {
      data$sig[i] <- 1
    } else {
      data$sig[i] <-0
    }
    }
    }    
# End for loop

write.csv(data,file = "dataClean.csv")

This runs the power.prop.test on each row, includes error handling and a condition to tell you whether you have enough observations. I'm sure there are more efficient ways to write this, so I'll review your comments to see if I can incorporate them.

IRTFM · Accepted Answer · 2014-07-08 02:01:07Z

0

Looks like a job for apply. To avoid any possible interference with factor or character variables, I'm just submitting the two columns as the argument.

data$power.col <- apply(data[5:6], 1,  
                      function(x) power.prop.test, p1 = x[1], p2 = x[2], 
                         sig.level=.1, power = .8, alternative = "one.sided")
      }

answered Jul 8, 2014 at 2:01

IRTFM

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Comments

maj · Accepted Answer · 2014-07-07 21:16:20Z

-1

First of all, I should say that I have never heard of power-prop tests. But then again, your question really isn't about the statistics, right?

Secondly, there is one package that is able to add columns to a data.frame, namely dplyr.

To quote the documentation: mutate(mtcars, displ_l = disp / 61.0237) - "Add a column displ_l (to mtcars) containing the values from the disp column divided by 61.0237."

answered Jul 7, 2014 at 21:16

maj

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1 Comment

IRTFM Over a year ago

And how is that different than $<-?

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