OK, I need help!!

I've been searching, but I don't understand the logic of some this
dataframe addressing syntax.

What is this type of code called?

test [["v3"]] [is.na(test[["v2"]])] <-10  #choose column v3 where column v2
is == 4 and replace with 10

and where is it documented?


The code below works for what I want to do (find the non-missing value in a
row), but why?

test <- read.table(text="
v1  v2  v3  result
3  NA  NA  NA
NA  3   NA NA
NA  NA   3 NA
"
, header=TRUE)

test [["result"]] [!(is.na(test[["v1"]]))] <- test [["v1"]] [!(is.na
(test[["v1"]]))]
test [["result"]] [!(is.na(test[["v2"]]))] <- test [["v2"]] [!(is.na
(test[["v2"]]))]
test [["result"]] [!(is.na(test[["v3"]]))] <- test [["v3"]] [!(is.na
(test[["v3"]]))]

thanks!


On Fri, Jul 13, 2012 at 6:41 AM, Rui Barradas <ruipbarradas@sapo.pt> wrote:

> Hello,
>
> Check the structure of what you have, df and newdf. You will see that in
> df dateTime is of class POSIXlt and in newDf newDateTime is of class
> POSIXct.
>
> Solution:
>
> [...]
> df$dateTime <- strptime(df$dateTime,"%m/%d/%Y %H:%M")
> df$dateTime <- as.POSIXct(df$dateTime)
> [...]
>
> Hope this helps,
>
> Rui Barradas
>
> Em 13-07-2012 10:24, vioravis escreveu:
>
>> I have the following dataframe with the first column being of type
>> datetime:
>>
>> dateTime <- c("10/01/2005 0:00",
>>                "10/01/2005 0:20",
>>                "10/01/2005 0:40",
>>                "10/01/2005 1:00",
>>                "10/01/2005 1:20")
>> var1 <- c(1,2,3,4,5)
>> var2 <- c(10,20,30,40,50)
>> df <- data.frame(dateTime = dateTime, var1 = var1, var2 = var2)
>> df$dateTime <- strptime(df$dateTime,"%m/%d/%Y %H:%M")
>>
>> I want to create 10 minute interval data as follows:
>>
>> minTime <- min(df$dateTime)
>> maxTime <- max(df$dateTime)
>> newTime <- seq(minTime,maxTime,600)
>> newDf <- data.frame(newDateTime = newTime)
>> newDf <- merge(newDf,df,by.x = "newDateTime",by.y = "dateTime",all.x =
>> TRUE)
>>
>> The objective here is to create a data frame with values from df for the
>> datetime in df and NA for the missing ones. However, I am getting the
>> following data frame with both Var1 and Var2 having all NAs.
>>
>>  newDf
>>>
>>            newDateTime var1 var2
>> 1 2005-10-01 00:00:00   NA   NA
>> 2 2005-10-01 00:10:00   NA   NA
>> 3 2005-10-01 00:20:00   NA   NA
>> 4 2005-10-01 00:30:00   NA   NA
>> 5 2005-10-01 00:40:00   NA   NA
>> 6 2005-10-01 00:50:00   NA   NA
>> 7 2005-10-01 01:00:00   NA   NA
>> 8 2005-10-01 01:10:00   NA   NA
>> 9 2005-10-01 01:20:00   NA   NA
>>
>> Can someone help me on how to do the merge based on the two datetime
>> columns?
>>
>> Thank you.
>>
>> Ravi
>>
>>
>>
>>
>>
>>
>> --
>> View this message in context: http://r.789695.n4.nabble.com/**
>> Merging-on-Datetime-Column-**tp4636417.html<http://r.789695.n4.nabble.com/Merging-on-Datetime-Column-tp4636417.html>
>> Sent from the R help mailing list archive at Nabble.com.
>>
>> ______________________________**________________
>> R-help@r-project.org mailing list
>> https://stat.ethz.ch/mailman/**listinfo/r-help<https://stat.ethz.ch/mailman/listinfo/r-help>
>> PLEASE do read the posting guide http://www.R-project.org/**
>> posting-guide.html <http://www.R-project.org/posting-guide.html>
>> and provide commented, minimal, self-contained, reproducible code.
>>
>>
> ______________________________**________________
> R-help@r-project.org mailing list
> https://stat.ethz.ch/mailman/**listinfo/r-help<https://stat.ethz.ch/mailman/listinfo/r-help>
> PLEASE do read the posting guide http://www.R-project.org/**
> posting-guide.html <http://www.R-project.org/posting-guide.html>
> and provide commented, minimal, self-contained, reproducible code.
>



-- 
Charles Stangor
Professor and Associate Chair

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