similar to: Partial comparison in string vector

Hi, I encounter a situation where I have a list whose element is a column matrix. Says, $'1' [,1] 1 2 3 $'2' [,1] 4 5 6 Is there fast way to collapse the list into a matrix like a cbind operation in this case? Meaning, the result should be a matrix that looks like: [,1] [,2] [1,] 1 4 [2,] 2 5 [3,] 3 6 I can loop through all elements and do

What is the right way to assign a new variable into each a of list of data frames? Here is my failed attempt: mylist <- list(df1 = data.frame(A = runif(5), B = runif(5)), df2 = data.frame(A = runif(5), B= runif(5))) lapply(mylist, function(x){x$Y <- x$A * x$B}) $df1 [1] 0.25589928 0.03446026 0.94992362 0.21388326 0.08668821 $df2 [1] 0.08771839 0.05643553 0.09036894

Hello I have 2 data frames DF1 and DF2 where DF2 is a subset of DF1: DF1= data.frame(V1=1:6, V2= letters[1:6]) DF2= data.frame(V1=1:3, V2= letters[1:3]) How do I create a new data frame of the difference between DF1 and DF2 newDF=data.frame(V1=4:6, V2= letters[4:6]) In my real data, the rows are not in order as in the example I provided. Thanks much Joseph [[alternative HTML version

Hello All, I have two dataframes and I wish to insert the values of one dataframe into another (let's call them DF1 and DF2). DF1 looks like this: col1.....col2 a...........1 b...........2 c...........3 d...........4 e...........5 f............6 g...........7 where col1 (which is just the first column of the dataframe) is a list of characters and col2 is the numeric value associated with

If you want colors mapped to the _values_ in DF1$C, there are a number of ways to do it: Color_unq<-color.scale(DF1$C,c(1,0),c(0,0,c(0,1)) This will produce colors from the lowest values (red) through the highest (blue). See the help page for color.scale to get different colors. With this you can use color.legend to add a mapping of the values and colors. If you just want different colors,

Dear expeRts, What is the best approach to create a third data frame from two given ones, when the new/third data frame has last column computed from the last columns of the two given data frames? ## Okay, sounds complicated, so here is an example. Assume we have the two data frames: df1 <- data.frame(Year=rep(2001:2010, each=2), Group=c("Group 1","Group 2"), Value=1:20)

#I want to "merge" or "join" 2 dataframes (df1 & df2) into a 3rd (mydf). I want the 3rd dataframe to contain 1 row for each row in df1 & df2, and all the columns in both df1 & df2. The solution should "work" even if the 2 dataframes are identical, and even if the 2 dataframes do not have the same column names. The rbind.fill function seems to work. For

Full_Name: Long Qu Version: 2.3.1 OS: Windows XP Submission from: (NULL) (64.113.93.235) The QQ-plot of two versions of simulating noncentral F-distributed random numbers has quite different scales: > qqplot(rf(1000,2,15,3),qf(runif(1000),2,15,3)) The rf() function reads: > rf function (n, df1, df2, ncp = 0) { if (ncp == 0) .Internal(rf(n, df1, df2)) else rchisq(n, df1,

Hi, Two ways to create what should normally be the same data frame: > df1 <- data.frame(a=character(0), b=character(0))> df1 [1] a b <0 rows> (or 0-length row.names) > df2 <- as.data.frame(matrix(character(0), ncol=2, dimnames=list(NULL, letters[1:2]))) > df2 [1] a b <0 rows> (or 0-length row.names) unique() works as expected except that I

Hi, I'm trying to compare two linear regressions. I'm using the following approach: ################## xx<-1:100 df1 <- data.frame(x = xx, y = xx * 2 + 30 + rnorm(n=length(xx),sd=10), g = 1) df2 <- data.frame(x = xx, y = xx * 4 + 9 + rnorm(n=length(xx),sd=10), g = 2) dta <- rbind(df1, df2) dta$g <- factor(dta$g)

Hi, Attention chi-squared distribution, unlike F distribution, has only df1 as parameter, not df1 and df2. So correct into: outer(1:3, 1:3, function(df1, df2) qchisq(0.95, df1, df2)) outer(1:3, 1:3, function(df1, df2) qchisq(0.95, df1)) ^^^^^^^^^^^^^^^^^^^^ Regards, Vito you wrote: Dear Rs: outer(1:3, 1:3, function(df1, df2) qf(0.95, df1, df2)) I compare this F

I had meant to copy the list on this; must have hit 'Reply' instead of 'Reply All'. P Ehlers -------- Original Message -------- Subject: Re: [R] rbind with partially overlapping column names Date: Mon, 16 May 2011 11:14:11 -0600 From: Peter Ehlers <ehlers at ucalgary.ca> To: Jonathan Flowers <jonathanmflowers at gmail.com> On 2011-05-16 08:56, Jonathan Flowers wrote:

I would suggest the method of Sokal and Rholf (1995) S. 498, using the F test. Below I repeat the analysis by Spencer Graves: Spencer: > df1 <- data.frame(x=1:3, y=1:3+rnorm(3)) > df2 <- data.frame(x=1:3, y=1:3+rnorm(3)) > fit1 <- lm(y~x, df1) > s1 <- summary(fit1)$coefficients > fit2 <- lm(y~x, df2) > s2 <- summary(fit2)$coefficients > db <-

Hi folks, Here is the problem. I am giving an example .I want to find a measure of similarity or dissimilarity among ranking (of students of a same class of size say 50)by two judges. But instead of observing the rank of all the 50 students (Where we could have used rank correlation measures)in each case what I have is 2 list of top 20 students chosen by each judge. The following paper gives out

I'm seeing some inconsistent behavior when re-assigning values in a data frame. The first assignment turns all of the 0s in my data frame to 2s, the second fails to do so. > df1 <- data.frame(a = c(NA, 0, 3, 4)) > df2 <- data.frame(a = c(NA, 0, 0, 4)) > df1[df1 == 0] <- 2 ## Works > df2[df2 == 0] <- 2 Error: NAs are not allowed in subscripted assignments Checking an

Hi all, I need to test the significnce of difference between slopes of two regression lines and regression line with theoretical line. I try to use Slope.test function from emu package, but an error occured... library(emu) d1<-data.frame(P1=c(1,2,3,5,7,8,9,13,14,15), P2=c(1,2,5,8,11,13,15,15,18,24), R=c(2,7,8,9,16,21,27,31,33,36)) # First data set m1<-lm(R~P1+P2+P1*P2,data=d1) # Regr.

Dear Mailing-List, I think this is a newbie question. However, i would like to integrate a loop in the function below. So that the script calculates for each variable within the dataframe df1 the connecting data in df2. Actually it takes only the first row. I hope that's clear. My goal is to apply the function for each data in df1. Many thanks in advance. An example is as follows: df1

Dear community, I'm working with the data.frame attached ( http://r.789695.n4.nabble.com/file/n4122926/df1.xls df1.xls ), let's call it df1. I typed: df1<- read.xls("C:/... dir .../df1.xls",colNames= TRUE, rowNames= TRUE) Then I splited randomly df1 using splitdf function (http://gettinggeneticsdone.blogspot.com/2011/03/splitting- dataset-revisited-keeping.html)

Dear Mailing-List, I think this is a newbie question. However, i would like to integrate a loop in the function below. So that the script calculates for each variable within the dataframe df1 the connecting data in df2. Actually it takes only the first row. I hope that's clear. My goal is to apply the function for each data in df1. Many thanks in advance. An example is as follows: df1

This will handle all the columns; it assumes the ones you want to start with are in column 2 through the end: > library(dplyr) > df1 <- read.table(text = "ID A B + 1 1 2 + 1 0 3 + 2 5 NA + 2 1 3 + 3 1 4 + 4 NA NA + 4 0 1 + 4