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 [[alternative HTML version deleted]]
Hello, It's more simple than you believe it is. One thing at a time. First, in order to lighten the instructions, create index vectors. test2 <- test # save 'test' for later na.v1 <- is.na(test[["v1"]]) na.v2 <- is.na(test[["v2"]]) na.v3 <- is.na(test[["v3"]]) Now use them. test[[ "result" ]][ !na.v1 ] <- test[[ "v1" ]][ !na.v1 ] test[[ "result" ]][ !na.v2 ] <- test[[ "v2" ]][ !na.v2 ] test[[ "result" ]][ !na.v3 ] <- test[[ "v3" ]][ !na.v3 ] Note that above, for instance, n the first line, on each side of '<-' we have two different types of indexing, in a certain sense. One, a data.frame is a list of a special type, each list member is a (random?) variable and all variables have the same number of observations. So test[[ "result" ]] refers to a vector of the data.frame. Another is the indexing of that vectors' elements. Imagine that we had assigned test.res <- test[[ "result" ]] and then accessed the elements of 'test.res' with test.res[ !na.v1 ] <- ...etc... That's what we are doing. Considering that a df is a list with a tabular form, we could also use the row/column type of indexing. Maybe this would be more intuitive. Equivalent, exactly equivalent to the code above is: test2[ !na.v1 , "result" ] <- test2[ !na.v1 , "v1" ] test2[ !na.v2 , "result" ] <- test2[ !na.v2 , "v2" ] test2[ !na.v3 , "result" ] <- test2[ !na.v3 , "v3" ] all.equal(test, test2) # TRUE Hope this helps, Rui Barradas Em 14-07-2012 21:22, Charles Stangor escreveu:> 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 <http://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 <http://is.na>(test[["v1"]]))] <- test > [["v1"]] [!(is.na <http://is.na>(test[["v1"]]))] > test [["result"]] [!(is.na <http://is.na>(test[["v2"]]))] <- test > [["v2"]] [!(is.na <http://is.na>(test[["v2"]]))] > test [["result"]] [!(is.na <http://is.na>(test[["v3"]]))] <- test > [["v3"]] [!(is.na <http://is.na>(test[["v3"]]))] > > thanks! > > > On Fri, Jul 13, 2012 at 6:41 AM, Rui Barradas <ruipbarradas at sapo.pt > <mailto:ruipbarradas at 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 at r-project.org <mailto:R-help at 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 at r-project.org <mailto:R-help at 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 >
Hello, Thank you, I'm gald it helped. Two notes. 1. I don't believe 1t's a problem with the documentation, though many times, and R is not an exception, there are books that explain in simpler terms what the docs alreay explain well. Check out the "contributed" link in http://cran.r-project.org/ (it's on the left, bottom-most). There are several books that though have specific areas, start with an introduction to R. 2. You've missinterpreted a point in my post, data.frames are list. Stricktly speakng they are also, like any other list, collections of list, but that's NOT the way they should be seen. It's more natural to see them as implementing the statistical concepts of variables and observations. In this case a column is a variable/vector (not list) and whithin a vector, we have observations. In the general case variables need not have the same number of observations; if they do, the list can become tabular, a data.frame. And we can speak of rows. Rule: call the columns variables and call the rows observations or, well, or columns and rows. But think of the columns as vectors. Like I've said above, a column is still a list, and can hold any type of data. Some questions are about keeping entire matrices as elements of a data.frame column, but the answer is "yes, it is possible but NO, don't do that". Em 15-07-2012 16:05, Charles Stangor escreveu:> Rui, > > Thank you SO MUCH!! This was exactly the explanation I needed > > Now I can see that dataframes are collections of lists where each column > is a list. > > I find that R documentation is either very superficial or completely > arcane.... but I'm getting it! > > Thanks again. > > Chuck > > On Sat, Jul 14, 2012 at 7:41 PM, Rui Barradas <ruipbarradas at sapo.pt > <mailto:ruipbarradas at sapo.pt>> wrote: > > Hello, > > It's more simple than you believe it is. One thing at a time. > > First, in order to lighten the instructions, create index vectors. > > test2 <- test # save 'test' for later > > na.v1 <- is.na <http://is.na>(test[["v1"]]) > na.v2 <- is.na <http://is.na>(test[["v2"]]) > na.v3 <- is.na <http://is.na>(test[["v3"]]) > > > Now use them. > > > test[[ "result" ]][ !na.v1 ] <- test[[ "v1" ]][ !na.v1 ] > test[[ "result" ]][ !na.v2 ] <- test[[ "v2" ]][ !na.v2 ] > test[[ "result" ]][ !na.v3 ] <- test[[ "v3" ]][ !na.v3 ] > > > Note that above, for instance, n the first line, on each side of > '<-' we have two different types of indexing, in a certain sense. > > One, a data.frame is a list of a special type, each list member is a > (random?) variable and all variables have the same number of > observations. So test[[ "result" ]] refers to a vector of the > data.frame. > > Another is the indexing of that vectors' elements. Imagine that we > had assigned > > test.res <- test[[ "result" ]] > > and then accessed the elements of 'test.res' with > > test.res[ !na.v1 ] <- ...etc... > > That's what we are doing. > Considering that a df is a list with a tabular form, we could also > use the row/column type of indexing. Maybe this would be more > intuitive. Equivalent, exactly equivalent to the code above is: > > > test2[ !na.v1 , "result" ] <- test2[ !na.v1 , "v1" ] > test2[ !na.v2 , "result" ] <- test2[ !na.v2 , "v2" ] > test2[ !na.v3 , "result" ] <- test2[ !na.v3 , "v3" ] > > all.equal(test, test2) # TRUE > > > Hope this helps, > > Rui Barradas > > Em 14-07-2012 21:22, Charles Stangor escreveu: > > 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 <http://is.na> > <http://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 <http://is.na> > <http://is.na>(test[["v1"]]))] <- test > [["v1"]] [!(is.na <http://is.na> <http://is.na>(test[["v1"]]))] > test [["result"]] [!(is.na <http://is.na> > <http://is.na>(test[["v2"]]))] <- test > [["v2"]] [!(is.na <http://is.na> <http://is.na>(test[["v2"]]))] > test [["result"]] [!(is.na <http://is.na> > <http://is.na>(test[["v3"]]))] <- test > [["v3"]] [!(is.na <http://is.na> <http://is.na>(test[["v3"]]))] > > thanks! > > > On Fri, Jul 13, 2012 at 6:41 AM, Rui Barradas > <ruipbarradas at sapo.pt <mailto:ruipbarradas at sapo.pt> > <mailto:ruipbarradas at sapo.pt <mailto:ruipbarradas at 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> > > <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 at r-project.org <mailto:R-help at r-project.org> > <mailto:R-help at r-project.org <mailto:R-help at r-project.org>> > mailing list > https://stat.ethz.ch/mailman/____listinfo/r-help > <https://stat.ethz.ch/mailman/__listinfo/r-help> > <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> > <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 at r-project.org <mailto:R-help at r-project.org> > <mailto:R-help at r-project.org <mailto:R-help at r-project.org>> > mailing list > https://stat.ethz.ch/mailman/____listinfo/r-help > <https://stat.ethz.ch/mailman/__listinfo/r-help> > <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> > <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 > > > > > > > -- > Charles Stangor > Professor and Associate Chair >
Hello, again. Inline. Em 15-07-2012 16:17, Charles Stangor escreveu:> Rui, > > Since you are so generous, may I ask you one more question? What is the > deal with the text after the semicolon in the statement below? Is this > an ifelse or something? Why is it needed ? > > obrigado. > > df1 <- read.table(text=" > cola colb colc cold cole > 1 NA 5 9 NA 17 > 2 2 6 NA 14 NA > 3 3 NA 11 15 19 > 4 4 8 12 NA NA > ", header=TRUE) > > df2 <- read.table(text=" > cola colb colc cold cole > 1 8 10 12 14 16 > ", header=TRUE) > > df1[["cola"]][is.na(df1[["cola"]])] <- df2[["cola"]]; > df1[["cola"]] #?? what's happening after the semi?It's printing df1[["cola"]]. Just that. The sem-colon ends an instruction and starts a new one. If it's confusing, put what follows it in a new line. Rui Barradas> > df1 > > > > On Sat, Jul 14, 2012 at 7:41 PM, Rui Barradas <ruipbarradas at sapo.pt > <mailto:ruipbarradas at sapo.pt>> wrote: > > Hello, > > It's more simple than you believe it is. One thing at a time. > > First, in order to lighten the instructions, create index vectors. > > test2 <- test # save 'test' for later > > na.v1 <- is.na <http://is.na>(test[["v1"]]) > na.v2 <- is.na <http://is.na>(test[["v2"]]) > na.v3 <- is.na <http://is.na>(test[["v3"]]) > > > Now use them. > > > test[[ "result" ]][ !na.v1 ] <- test[[ "v1" ]][ !na.v1 ] > test[[ "result" ]][ !na.v2 ] <- test[[ "v2" ]][ !na.v2 ] > test[[ "result" ]][ !na.v3 ] <- test[[ "v3" ]][ !na.v3 ] > > > Note that above, for instance, n the first line, on each side of > '<-' we have two different types of indexing, in a certain sense. > > One, a data.frame is a list of a special type, each list member is a > (random?) variable and all variables have the same number of > observations. So test[[ "result" ]] refers to a vector of the > data.frame. > > Another is the indexing of that vectors' elements. Imagine that we > had assigned > > test.res <- test[[ "result" ]] > > and then accessed the elements of 'test.res' with > > test.res[ !na.v1 ] <- ...etc... > > That's what we are doing. > Considering that a df is a list with a tabular form, we could also > use the row/column type of indexing. Maybe this would be more > intuitive. Equivalent, exactly equivalent to the code above is: > > > test2[ !na.v1 , "result" ] <- test2[ !na.v1 , "v1" ] > test2[ !na.v2 , "result" ] <- test2[ !na.v2 , "v2" ] > test2[ !na.v3 , "result" ] <- test2[ !na.v3 , "v3" ] > > all.equal(test, test2) # TRUE > > > Hope this helps, > > Rui Barradas > > Em 14-07-2012 21:22, Charles Stangor escreveu: > > 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 <http://is.na> > <http://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 <http://is.na> > <http://is.na>(test[["v1"]]))] <- test > [["v1"]] [!(is.na <http://is.na> <http://is.na>(test[["v1"]]))] > test [["result"]] [!(is.na <http://is.na> > <http://is.na>(test[["v2"]]))] <- test > [["v2"]] [!(is.na <http://is.na> <http://is.na>(test[["v2"]]))] > test [["result"]] [!(is.na <http://is.na> > <http://is.na>(test[["v3"]]))] <- test > [["v3"]] [!(is.na <http://is.na> <http://is.na>(test[["v3"]]))] > > thanks! > > > On Fri, Jul 13, 2012 at 6:41 AM, Rui Barradas > <ruipbarradas at sapo.pt <mailto:ruipbarradas at sapo.pt> > <mailto:ruipbarradas at sapo.pt <mailto:ruipbarradas at 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> > > <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 at r-project.org <mailto:R-help at r-project.org> > <mailto:R-help at r-project.org <mailto:R-help at r-project.org>> > mailing list > https://stat.ethz.ch/mailman/____listinfo/r-help > <https://stat.ethz.ch/mailman/__listinfo/r-help> > <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> > <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 at r-project.org <mailto:R-help at r-project.org> > <mailto:R-help at r-project.org <mailto:R-help at r-project.org>> > mailing list > https://stat.ethz.ch/mailman/____listinfo/r-help > <https://stat.ethz.ch/mailman/__listinfo/r-help> > <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> > <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 > > > > > > > -- > Charles Stangor > Professor and Associate Chair >