similar to: Analyzing subsets

Why does this sapply code change df3 but not df1? Thanks df1 <- read.table(text=" cola colb colc cold cole 1 NA 5 9 NA 17 2 NA 6 NA 14 NA 3 3 NA 11 15 19 4 4 8 12 NA 20 ", header=TRUE) df2 <-df1*2 df1 df2 df3 <-sapply(names(df1),function(x) {df1[[x]]<- df2[[x]]}) df1 df3 [[alternative HTML version deleted]]

'grepl' returns a logical vector; you have to use this to get your subset. You can use: df_tq <- subset(df, grepl("t1", Command)) df_t2 <- subset(df, grepl("t2", Command)) # if you want to also get a subset that has both, use df_both <- subset(df, grepl("t1", Command) & grepl("t2", Command)) Jim Holtman Data Munger Guru What is

now after this: df_both <- subset(df, grepl("t1", Command) & grepl("t2", Command)) I use factor to apply the subset to df but then the Command level becomes 0 df_both$Command=factor(df_both$Command) str(df_both) $ Protocol : Factor w/ 0 levels: Do you know what is the reason? Thanks for replying On Sunday, April 24, 2016 12:18 PM, jim

Hi I have the following df and I created two subsets but I don't know how to use these subsets as the colors of my plot. data.frame': 36919 obs. of 162 variables $TE :int 38,41,11,52,48,75,..... $TR :int 100,210,548,546,..... $Command :factor W/2229 levels

Dear all, I have a data frame with different variables and I want to build different subsets out of this data frame using some conditions and I want to use a loop because there will be a lot of subsets and this would be saving a lot of time. I try to give you an overview about my data frame. I have a data frame named "Baumdaten" and it has one column named "transectID" with

Hello, Say I have 2 columns, bmi and gender, the first being all the values and the second being male or female. How would I subset this into males only and females only? I have searched these fora and read endlessly about select[] and split() functions but to no avail. Also the table is not ordered. bmi gender -> bmi gender + bmi gender 1 24.78 male

Hi all, I am looking to create a rank variable based on a continuous variable for subsets of the data. For example, for an R integrated data set about US states this is how a loop could create what I want: ### Example with loop data <- cbind(state.region,as.data.frame(state.x77))[,1:2] # choosing a subset of the data data <- data[order(data$state.region, 1/data$Population),] #

I have data of the form tC <- textConnection(" Subject Date parameter1 bob 3/2/99 10 bob 4/2/99 10 bob 5/5/99 10 bob 6/27/99 NA bob 8/35/01 10 bob 3/2/02 10 steve 1/2/99 4 steve 2/2/00 7 steve 3/2/01 10 steve 4/2/02 NA steve 5/2/03 16 kevin 6/5/04 24 ") data <- read.table(header=TRUE, tC) close.connection(tC) rm(tC) I am trying to calculate rate of change of parameter1 in

I'm attempting to change a data set by compressing rows into columns. Currently there are several rows that all have information about one "patient," but at different cycles. I'm trying to make each patient only have one row in the data set. Does anyone know a good way to combine data sets by factor level? I've separated the groups into different subsets by cycle, but not

For each date, I would like to keep the line with the lowest speed and discard the rest. The result would have one line for each date. Can I use aggregate for this? My table is as follows: structure(list(speed = c(3,9,14,8,7,6), result = c(0.697, 0.011, 0.015, 0.012, 0.018, 0.019), house = c(1, 1, 1, 1, 1, 1), date = c(719, 1027, 1027, 1027, 1030, 1030), id = c("1000",

Dear all, First, let's create some data to play around: set.seed(1) (df <- data.frame(Group=rep(c("Group1","Group2","Group3"), each=10), Value=c(rexp(10, 1), rexp(10, 4), rexp(10, 10)))[sample(1:30,30),]) ## Now we need the empirical distribution function: edf <- function(x) ecdf(x)(x) # empirical distribution function evaluated at x ##

Why does the subset not work in the which() version below? Thank you v1 <- subset(t1, version_1==as.character("100-1") | version_1==as.character("100-2")) a<-c("100-1", "100-2") v1 <- subset(t1, which(a==as.character(version_1)) != 0) [[alternative HTML version deleted]]

Dear list, I have this dataframe: > names(events) [1] "EID" "X" "Y" "trip" "tow" "catch" "effort" "depth" [9] "season" Where some of my unique ID "EID" appears more than once in 162 cases. > length(events$EID)-length(unique(events$EID)) [1] 162 I would like to combined

Hi R-listers, I am in plyr and using the script below and when I try to pull up the .csv file with head() it does not show up. I am not sure where I am going wrong. I have also checked the file box for turtlehatch.csv and it still does not show up when I head(turtlehatch.csv). Am I missing a command? Please advise, Jean > devel.index <- function(values, weights=c(1, 2, 3, 4, 5, 6)) { +

I am trying to aggregate data in column 2 to identifiers in col 1 eg.. take this> identifier quantity 1 10 1 20 2 30 1 15 2 10 3 20 and make this> identifier quantity 1 45 2 40 3 20 Thanks in

Dear R helpers I have following two data.frames viz. equity_data and param. equity_data = data.frame(security_id = c("Air", "Air", "Air", "Air", "Air", "Air", "Air", "Air", "Air", "Air", "Air", "Air", "AB", "AB", "AB", "AB",

Hi group, I imported 16 data frames using the function "list.files" temp <- list.files(path="...........") myfiles = lapply(temp, read.table,sep = "") Now I have 16 data set imported in R window. I want to combine them by row and tried some thing like (Here I am considering only 20 columns) for(i in 1:16){ data<- cbind(myfiles[[i]][,1:20]) } but it

Hi, I am new to R so I would appreciate any help. I have some data that has passenger flight data between city pairs. The way I got the data, there are multiple rows of data for each city pair; the number of passengers needs to be summed to get a TOTAL annual passenger count for each city pair. So my question is: how do I create a new table (or data frame) that selectively sums My initial

HI, Dear R community, I want to split a data frame by using two variables: let and g > x = data.frame(num = c(10,11,12,43,23,14,52,52,12,23,21,23,32,31,24,45,56,56,76,45), let = letters[1:5], g = 1:2) > x num let g 1 10 a 1 2 11 b 2 3 12 c 1 4 43 d 2 5 23 e 1 6 14 a 2 7 52 b 1 8 52 c 2 9 12 d 1 10 23 e 2 11 21 a 1 12 23 b 2 13 32 c 1 14

Hi List I have a dataframe (~1,200,000 rows deep) and I'd like to conditionally reorder groups of rows in this dataframe. I would like to reorder any rows where the Chr.Strand column contains a '-' but reorder within subsets delineated by the Probe.Set.Name column. # toy example #### library(plyr) negStrandGene <- data.frame(Probe.Set.Name =