similar to: equivalent of excel "sumif"

I have a data.frame datas which have two columns A and B. I want to filter column A by some values and to get a value list which contain the value in B. Best wishes! [[alternative HTML version deleted]]

#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

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)

The rbind on empty and nonempty data frames behaves inconsistently. I am not sure if by design. In the first example, first row is deleted, which may or may not be on purpose: df1 <- data.frame() df2 <- data.frame(foo=c(1, 2), bar=c("a", "b")) rbind(df1, df2) foo bar 2 2 b Now if we continue: df1 <- data.frame(matrix(0, 0, 2)) names(df1) <- names(df2)

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 there, I have a list of dataframes (generated by reading multiple files) and all dataframes are comparable in dimension and column names. They also have a common column, which, I'd like to use for merging. To give a simple example of what I have: df1 <- data.frame(c(LETTERS[1:5]), c(2,6,3,1,9)) names(df1) <- c("pos", "data") df3 <- df2 <- df1 df2$data

Hi, I have two dataframes: The first, df1, contains some missing data: 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 The second, df2, contains the following: cola colb colc cold cole 1 1.4 0.8 0.02 1.6 0.6 I'm wanting all missing data in df1$cola to be replaced by the value of df2$cola.

Hello all, I have a quandry I have been scratching my head about for a while. I've searched the manual and the web and have not been able to find an acceptable result, so I am hoping for some help. I have two data frames and I want to index into the first using the second, and replace the specific values I have indexed with more values from the second data.frame. I can do this

Hello, I have two dataframes DF1 and DF2 that should be identical but are not (DF1 has some rows that aren't in DF2, and vice versa). I would like to produce a new dataframe DF3 containing rows in DF1 that aren't in DF2 (and similarly DF4 would contain rows in DF2 that aren't in DF1). I have a solution for this problem (see self contained example below) but it's awkward and

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 <-

Hey Folks, Could somebody show me how to loop through a list of dataframes? I want to be able to generically access their elements and do something with them. For instance, instead of this: df1<- data.frame(x=(1:5),y=(1:5)); df2<- data.frame(x=(1:5),y=(1:5)); df3<- data.frame(x=(1:5),y=(1:5)); plot(df1$x,df1$y); plot(df2$x,df2$y); plot(df3$x,df3$y); I would like to do something like:

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)

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

Hi- I have two data frames for which I wish to conditionally subtract the values of one dataframe from the other. I want to subtract df1$x from df2$x when their id is equal and the absolute value of difference between the dates is 12 hours or less. If there is no match of equal id's and dates less than 12 hours apart I want it to return "NA". Note that df1 has missing values in x

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

I have several data frames, eg: > df1 <- data.frame(x=seq(0,10), y=seq(10,20)) > df2 <- data.frame(a=seq(0,10), b=seq(10,20)) It is common to create loops in R like this: > for(df in list(df1, df2)){ #etc. } This works fine when you know the name of the objects to put into the list. I assume that the order of the objects in the list is respected through the loop. Inside the

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

df1 -- dataframe with column date and several other columns. #rows >40k Several of the dates are repeated. df2 -- dataframe with two columns date and index. #rows ~130 This is really a map from date to index. I would like to create a column called index in df1 which has the corresponding index from df2. The following works: index <- NULL for(wk in df1$week){ index <-

This is just a curiosity question. Why do the two different syntaxes for df1 and df2 give such different results in the names(dfx)? Thanks df1 <- data.frame(nas = c("A", "B" , "B" ,"C" ,"B", "A", "D"),nums = c(3, 2, 1, 1, 2, 3, 7)) df2 <- data.frame(nas <- c("A", "B" ,

This is just a suggestion/wish that it would be nice for the F-distribution functions to recognize limiting cases for infinite degrees of freedom, as the t-distribution functions already do. The t-distribution functions recognize that df=Inf is equivalent to the standard normal distribution: > pt(1,df=Inf) [1] 0.8413447 > pnorm(1) [1] 0.8413447 On the other hand, pf() will accept Inf