r-factor

I have the following data frame (simplified) with the country variable as a factor and the value variable has missing values: country value AUT NA AUT 5 AUT NA AUT NA GER NA GER NA GER 7 GER NA GER NA The following generates the above data frame: data <- data.frame(country=c("AUT", "AUT", "AUT", "AUT", "GER", "GER", "GER", "GER", "GER"), value=c(NA, 5, NA, NA, NA, NA, 7, NA, NA)) Now, I would like to replace the NA values in each country subset using the method last observation carried forward (LOCF). I know the command na.locf in the zoo package. data <- na.locf(data) would give me the

I have a data frame with columns initially labeled arbitrarily. Later on, I want to change these levels to numerical values. The following script illustrates the problem. library(ggplot2) library(reshape2) m <- 10 n <- 6 nam <- list(c(),letters[1:n]) var <- as.data.frame(matrix(sort(rnorm(m*n)),m,n,F,nam)) dtf <- data.frame(t=seq(m)*0.1, var) mdf <- melt(dtf, id=c('t')) xs <- c(0.25,0.5,1.0,2.0,4.0,8.0) levels(mdf$variable) <- xs g <- ggplot(mdf,aes(variable,value,group=variable,colour=t)) g + geom_point() + #scale_x_continuous() + opts() This plot is produced. The 'variable' quantities are

I can't find a way to ask ggplot2 to show an empty level in a boxplot without imputing my dataframe with actual missing values. Here is reproducible code : # fake data dftest <- expand.grid(time=1:10,measure=1:50) dftest$value <- rnorm(dim(dftest)[1],3+0.1*dftest$time,1) # and let's suppose we didn't observe anything at time 2 # doesn't work even when forcing with factor(..., levels=...) p <- ggplot(data=dftest[dftest$time!=2,],aes(x=factor(time,levels=1:10),y=value)) p + geom_boxplot() # only way seems to have at least one actual missing value in the dataframe dftest2 <- dftest dftest2

I've looked through a number of posts about ordering factors, but haven't quite found a match for my problem. Unfortunately, my knowledge of R is still pretty rudimentary. I have a subset of an archaeological artifact catalog that I'm working with. I'm trying to cross-tabulate diagnostic historical artifact types and site testing locations. Easy enough with ddply or tapply. My problem is that I want to sort the artifact types (a factor) by their mean diagnostic date (number/year), and I keep getting them alphabetically. I know I need to make it an ordered factor, but can't figure out how to

I would like to create boxplots of multiple variables for groups of a continuous x-variable. The boxplots should be arranged next to each other for each group of x. The data looks like this: require (ggplot2) require (plyr) library(reshape2) set.seed(1234) x <- rnorm(100) y.1 <- rnorm(100) y.2 <- rnorm(100) y.3 <- rnorm(100) y.4 <- rnorm(100) df <- as.data.frame(cbind(x,y.1,y.2,y.3,y.4)) which I then melted dfmelt <- melt(df, measure.vars=2:5) The facet_wrap as shown in this solution ( Multiple plots by factor in ggplot (facets) ) gives me out each variable in an individual plot, but I would

This is the information contained within my dataframe: ## minuteofday: factor w/ 89501 levels "2013-06-01 08:07:00",... ## dDdt: num 7.8564 2.318 ... ## minutes: POSIXlt, format: NA NA NA I need to convert the minute of day column to a date/time format: minuteave$minutes <- as.POSIXlt(as.character(minuteave$minuteofday), format="%m/%d/%Y %H:%M:%S") I've tried as.POSIXlt , as.POSIXct and as.Date . None of which worked. Does anyone have ANY thoughts. The goal is to plot minutes vs. dDdt, but it won't let me plot in the specified time period that I want to as a factor. I have no idea what to try

Supose I have a data frame with 3 columns ( name , y , sex ) where name is character, y is a numeric value and sex is a factor. sex<-c("M","M","F","M","F","M","M","M","F") x<-c("MARK","TOM","SUSAN","LARRY","EMMA","LEONARD","TIM","MATT","VIOLET") name<-as.character(x) y<-rnorm(9,8,1) score<-data.frame(x,y,sex) score name y sex 1 MARK 6.767086 M 2 TOM 7.613928 M 3 SUSAN 7.447405 F 4 LARRY 8.040069 M 5 EMMA 8.306875 F 6 LEONARD 8.697268 M 7 TIM 10.385221 M 8 MATT 7.497702 M 9 VIOLET 10.177969 F If I wanted to order it by y I would use: score[order(score$y),] x y sex 1 MARK 6.767086 M 3 SUSAN 7

I have a function in which I define a data.frame that I use loops to fill with data. At some point I get the Warning message: Warning messages: 1: In [<-.factor ( *tmp* , iseq, value = "CHANGE") : invalid factor level, NAs generated Therefore, when I define my data.frame, I'd like to set the option stringsAsFactors to FALSE but I don't understand how to do it. I have tried: DataFrame = data.frame(stringsAsFactors=FALSE) and also: options(stringsAsFactors=FALSE) What is the correct way to set the stringsAsFactors option? MvG It depends on how you fill your data frame, for which you haven't