similar to: difference of two data frames

Hello I have 2 data frames df1 and df2. I would like to create a new data frame new_df which will contain only the common rows based on the first 2 columns (chrN and start). The column score in the new data frame should be replaced with a column containing the average score (average_score) from df1 and df2. df1= data.frame(chrN= c(“chr1”, “chr1”, “chr1”, “chr1”, “chr2”, “chr2”, “chr2”),

Hi, I have two lists (c and h - see below) containing matrices with similar cases but different values. I want to split these matrices into multiple matrices based on the values in h. So, I did the following: years<-c(1997:1999) for (t in 1:length(years)) { year=as.character(years[t]) h[[year]]<-sapply(colnames(h[[year]]), function(var)

I have a data frame that looks like this: V1 V2 V3 a b 0:1:12 d f 1:2:1 c d 1:0:9 where V3 is in the form x:y:z Can someone show me how to subset the rows where the values of x, y and z <= 10: V1 V2 V3 d f 1:2:1 c d 1:0:9 Thanks Joseph [[alternative HTML version deleted]]

Hi All I have a datafram which looks like this : CustomerID DietType 1 a 1 c 1 b 2 f 2 a 3 j 4 c 4 c 4 f And I would like to reshape this so I can

I'm trying to find a more elegant way of doing this. What I'm trying to accomplish is to count the frequency of letters (major / minor alleles) in a string grouped by the factor levels in another column of my data frame. Ex. > DF<-data.frame(c("CC", "CC", NA, "CG", "GG", "GC"), c("L", "U", "L",

I believe you need to spend time with an R tutorial or two: a data frame (presumably the "table" data structure you describe) can *not* contain "blanks" -- all columns must be the same length, which means NA's are filled in as needed. Also, 8e^5 * 7e^4 = 5.6e^10, which almost certainly will not fit into any local version of R (maybe it would in some server version --

I want to remove the column names from a data frame. I do it the long way, can any body show me a better way ? df= data.frame(chrN= c(“chr1”, “chr2”, “chr3”), start= c(1, 2, 3), end= c(4, 5, 6), score= c(7, 8, 9)) df #I write a txt file without row or column names write.table(df,"df1.txt",sep='\t',quote=FALSE,row.names=F,col.names=F) #then I read it with the header = F

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

Hi I have probably a very simple question but I'm going crazy trying to find the solution. I have two data.frames with headers and I'm doing an intersection between them by names, such that the intersected data.frames are returned by: df1[intersect(names (df1), names(df2))] and the same for df2 Now, I want to have all the opposite data that did not intersect. I tried to do:

Hello, I would like to merge two data frames with partially overlapping column names with an rbind-like operation. For the follow data frames, df1 <- data.frame(a=c("A","A"),b=c("B","B")) df2 <- data.frame(b=c("b","b"),c=c("c","c")) I would like the output frame to be (with NAs where the frames don't

OK, I need help!! I've been searching, but I don't understand the logic of some this dataframe addressing syntax. What is this type of code called? test [["v3"]] [is.na(test[["v2"]])] <-10 #choose column v3 where column v2 is == 4 and replace with 10 and where is it documented? The code below works for what I want to do (find the non-missing value in a row),

Hi all, I have a dataframe (df1) that I am trying to select values from to a second dataframe that at the current time is only for the selected items from df1 (df2). The values that I am trying to save from df1 are factors with alphanumeric names df1 looks like this: 'data.frame': 3014 obs. of 13 variables: $ Num : int 1 1 1 2 2 2 3 3 3 4 ... $ Tag_Num : int 1195

Colleagues, (R: 2.13.0; OS X) I often receive sequential datasets in which there are new rows interposed between existing rows. For example: SET1 <- data.frame(list(LETTERS=LETTERS[c(1:4, 6:10)], NUMBERS=c(1:4, 6:10))) SET2 <- data.frame(list(LETTERS=LETTERS[1:10], NUMBERS=1:10)) > SET1 LETTERS NUMBERS 1 A 1 2 B 2 3 C 3 4 D 4 5

How does one remove a column from a data frame when the name of the column to remove is stored in a variable? For Example: colname <- "LOT" newdf <- subset(olddf,select = - colname) The above statement will give an error, but thats what I'm trying to accomplish. If I had used: newdf <- subset(olddf,select = - LOT) then it would have worked, but as I said the column

Hi, I have two data frames each with 5 columns and different number of rows. some of the row names in one data frame are the same as the row names in the other. I want to be able to merge the two data frames to get a new data frame in which the duplicated row names are only shown once with the data for the rest of the columns used from the first data frame. Essentially, I want to make a union

#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)

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.

Why do you want to modify df1? Why not just reassemble the parts as a new data frame and use that going forward in your calculations? That is generally the preferred approach in R so you can re-do your calculations easily if you find a mistake later. -- Sent from my phone. Please excuse my brevity. On January 7, 2018 7:35:59 PM PST, Ek Esawi <esawiek at gmail.com> wrote: >I just came

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)