similar to: Reshape with multiple aggregate functions

I have a data frame and I would like to reshape it to wide format while at the same time applying different aggregate functions to each column AND at times multiple aggregate functions:   test1 = data.frame(         id = c(rep('101',8),rep('102',8)),         phase  = rep(c('D','D','L','L'),4),         day =

Hi, I'd like to merge mutliple dataframes from a list of dataframes by some common columns. The approach for simply merging 2 dataframes is working with: merge(df1,df2,by=c("col1","col2","col3"),all=TRUE) For mutliple dataframes in a list I try to use the merge_all command from the package reshape. The documentation states that the command takes a list of

Dear all, Lets say I have the following data frame: > set.seed(1) > col1 <- c(rep('happy',9), rep('sad', 9)) > col2 <- rep(c(rep('alpha', 3), rep('beta', 3), rep('gamma', 3)),2) > dates <- as.Date(rep(c('2009-10-13', '2009-10-14', '2009-10-15'),6)) > score=rnorm(18, 10, 3) > df1<-data.frame(col1=col1,

Dear R users, I have a matrix like A X 1 B Y 2 C Z 3 I want to reshape this matrix into this format X Y Z A 1 B 2 C 3 Thanks in advance for your help. Dinesh -- Dinesh Kumar Barupal Junior Specialist Metabolomics Fiehn Lab UCD Genome Center 451 East Health Science Drive GBSF Builidng University of California DAVIS 95616

Dear all, I have a dataframe which looks like this (dummy): date<-c("jan", "feb", "mar", "apr", "may", "june", "july", "aug","sep","oct","nov","dec") col1<-c(8.2,5.4,4.3,4.1,3.1,2.5,1.1,4.5,3.2,1.9,7.8,6.5) col2<-c(3.1,2.3,4.7,6.9,7.5,1.1,3.6,8.5,7.5,2.5,4.1,2.3)

Hi, I would like to split dataframe based on one colum and want to connect the two dataframes by rows (like rbind). Here a small example: # The orgininal dataframe df1 <- data.frame(col1 = c("A","A","B","B"),col2 = c(1:4), col3 = c(1:4)) # The datafame how it could look like df2 <- data.frame(A.col2 = c(1,2), A.col3 = c(1,2), B.col2 = c(3,4), B.col3

hi all - i'm just wondering what sort of code people write to essentially performa an aggregate call, but with different functions being applied to the various columns. for example, if i have a data frame x and would like to marginalize by a factor f for the rows, but apply mean() to col1 and median() to col2. if i wanted to apply mean() to both columns, i would call: aggregate(x, list(f),

Help-Rs   As someone who is newer to R and trying to make the transition from Access into R, there is a frequetnly used function that I'd like to try and duplicate in the R world.  It involved creating an aggregate table of the top (n)  orders for an item by sum of cost over a select period of time.   So, take the following example :   group <- c(rep(1,10), rep(2,10), rep(3,10)) product

Hello! I am merging two datasets and I have encountered a problem with sort. Can someone please point me to my error. Here is the example. ## I have dataframes, first one with factor and second one with factor ## and integer > tmp1 <- data.frame(col1 = factor(c("A", "A", "C", "C", "0", "0"))) > tmp2 <- data.frame(col1 =

Patrick, ## Run the following script an notice the different values of the dataframe "data" in each instance. # I understand you have done something like the following: data <- data.frame(COL1 = c("6/1/14", "7/1/14"), COL2 = c("5/1/15", "5/1/15"), stringsAsFactors = FALSE) data$Date_Flag <- ifelse(data$COL2 >

Hola: Si codificas "col1" como un factor, lo puedes cambiar todo de una vez renombrando los niveles correspondientes: > df$col1<-as.factor(df$col1) > df$col1  [1] uno   dos   3     4     cinco 6     siete 8     9     diez Levels: 3 4 6 8 9 cinco diez dos siete uno > levels(df$col1)[1:5] <-

Thank you Pikal and Bert. My apology for posting parts of my previous email in HTML. Bert's suggestion will work but i am wondering if there is an alternative especially in the case where the data frames are big; that is the difference in lengths among them is large. Below is a list of sample date frames and desired result. EK

Take this as an example: > a=data.frame(col1=c(1,2,3,4,5), col2=c ("my","beloved","daughter","son","wife")) > b=data.frame(col1=c(1,2,4), col2=c("my","beloved","son")) > a col1 col2 1 1 my 2 2 beloved 3 3 daughter 4 4 son 5 5 wife > b col1 col2 1 1 my 2

HI Jim and all, I want to put one more condition. Include col2 and col3 if they are not in col1. Here is the data mydat <- read.table(textConnection("Col1 Col2 col3 K2 X1 NA Z1 K1 K2 Z2 NA NA Z3 X1 NA Z4 Y1 W1"),header = TRUE,stringsAsFactors=FALSE) The desired out put would be Col1 Col2 col3 1 X1 0 0 2 K1 0 0 3 Y1 0 0 4 W1 0 0 6 K2 X1

Jim has been exceedingly patient (and may well continue to be so), but this smells like "failure to launch". At what point will you start showing your (failed) attempts at solving your own problems so we can help you work on your specific weaknesses and become self-sufficient? -- Sent from my phone. Please excuse my brevity. On February 25, 2018 7:55:55 AM PST, Val <valkremk at

Hi Val, My fault - I assumed that the NA would be first in the result produced by "unique": mydat <- read.table(textConnection("Col1 Col2 col3 Z1 K1 K2 Z2 NA NA Z3 X1 NA Z4 Y1 W1"),header = TRUE,stringsAsFactors=FALSE) val23<-unique(unlist(mydat[,c("Col2","col3")])) napos<-which(is.na(val23)) preval<-data.frame(Col1=val23[-napos],

Hi all, I put up an exhaustive model to use R's "step" function: ------------------------ mygam=gam(col1 ~ 1 + col2 + col3 + col4 + col2 ^ 2 + col3 ^ 2 + col4 ^ 2 + col2 ^ 3 + col3 ^ 3 + col4 ^ 3 + s(col2, 1) + s(col3, 1) + s(col4, 1) + s(col2, 2) + s(col3, 2) + s(col4, 2) + s(col2, 3) + s(col3, 3) + s(col4, 3) + s(col2, 4) + s(col3, 4) + s(col4, 4) + s(col2, 5) + s(col3,

Thank you Jim, I read the data as you suggested but I could not find K1 in col1. rbind(preval,mydat) Col1 Col2 col3 1 <NA> <NA> <NA> 2 X1 <NA> <NA> 3 Y1 <NA> <NA> 4 K2 <NA> <NA> 5 W1 <NA> <NA> 6 Z1 K1 K2 7 Z2 <NA> <NA> 8 Z3 X1 <NA> 9 Z4 Y1 W1 On Sat, Feb 24, 2018 at 6:18 PM, Jim

hi Val, Your problem seems to be that the data are read in as a factor. The simplest way I can think of to get around this is: mydat <- read.table(textConnection("Col1 Col2 col3 Z1 K1 K2 Z2 NA NA Z3 X1 NA Z4 Y1 W1"),header = TRUE,stringsAsFactors=FALSE) preval<-data.frame(Col1=unique(unlist(mydat[,c("Col2","col3")]))[-1], Col2=NA,col3=NA) rbind(preval,mydat)

Hello, how to merge a data.frame and a matrix by one column in the data.frame and rownames of the matrix? df <- data.frame(col1=c("kk","yy","kk"),col2=c(6,4,3)) > df   col1 col2 1   kk    6 2   yy    4 3   kk    3 m<-matrix(c(3,8,56,9), nrow=2, dimnames = list(c("aa","kk"),c("col1","col2"))) > m    col1 col2 aa