similar to: Deleting rows with NA from isolated column in matrix

Hi R-users, I'm trying to find an elegant way to count the number of rows in a dataframe with a unique combination of 2 values in the dataframe. My data is specifically one column with a year, one with a month, and one with a day. I'm trying to count the number of days in each year/month combination. But for simplicity's sake, the following dataset will do:

Hi all, I have two datasets, one that represents a long-term time series and one that represents summary data for the time series. It looks something like this: x<-data.frame(Year=c(2001,2001,2001,2001,2001,2001,2002,2002,2002,2002,2002,2002), Month=c(1,1,1,2,2,2),Q=c(5,5,5,6,6,6,3,3,3,4,4,5)) y<-data.frame(Year=c(2001,2001,2002,2002),Month=c(1,2,1,2),Threshold_Q=c(5,5,4,4)) What I'd

Please, I am receiving lot of e-mails that I do not want. Please could you delete my e-mail. Thank, Judit -----Original Message----- From: r-help-bounces at r-project.org [mailto:r-help-bounces at r-project.org] On Behalf Of Thomas Adams Sent: Monday, December 12, 2011 3:22 PM To: Bert Gunter Cc: r-help at r-project.org Subject: Re: [R] Boxplot of multiple vectors with different lengths Bert,

Hello, I'm attempting to write a code that automatically imports data from different files (with different lengths-just one variable) and makes tidy box plots for comparison. I can successfully import the data and create a list of the vectors I want to compare. But I cannot, for the life of me, figure out how to generate box plots using the "list" option. Suppose these are my data:

Hi all, I'm trying to identify a particular digit or value within a vector of factors. Specifically, this is environmental data where in some cases the minimum value reported is "<" a particular number (and I want to manipulate only these). For example: x<-c("1","2","3","4","<1") For a dataset that is hundreds or

Hi all, I'm attempting to make a quite-specific plot where the axes cross at the origin and with gridlines for guidance. I've been using ablines to create the reference lines because I want a lot of control as to where they are placed on the axis. This command works very well for such control. However... These ablines don't seem to work when I specify the origin as 0,0. They go

Hi all, I'm trying to import Microsoft Access data into R. It looks like I'm supposed to use the ROBC package, and this works fine with old Access files (those with an .mdb extension). However, lovely Microsoft must constantly update their software. Modern Access files have an .ACCDB extension. I cannot seem to coerce R to import data from such a file. Any advice? I've been using

Hi all, I am very new to R and I'm trying to import data from Microsoft Access. So far, I've managed to do so successfully using the following code: testdb <- file.path("c:\Databse.accdb") channel2 <- odbcConnectAccess2007(testdb) data.table <- sqlFetch(channel2,"data") This successfully imports a table(?) called "data.table". But when I try to

Full_Name: Utz J. Pape Version: 2.2.0 OS: linux Submission from: (NULL) (141.14.23.12) If I use phyper and set parameter x equal to k (meaning that all balls I draw are white) phyper returns 1 which is not (always) correct: pape at xxx:~> R2.2.0 --vanilla R : Copyright 2005, The R Foundation for Statistical Computing Version 2.2.0 (2005-10-06 r35749) ISBN 3-900051-07-0 R is free software

Dear everyone, I have looked all over the internet but I cannot find a way to solve my problem. In my data I want to sum a couple of variables. Some of these variables have NA values, and when I add them together, the result is NA dat <- data.frame( id = gl(5,1), var1 = rnorm(5, 10), var2 = rnorm(5, 7), var3 = rnorm(5, 6), var4 = rnorm(5, 3), var5 = rnorm(5, 8) ) dat[3,3] <- NA dat[4,5]

I have some square matrices with na values in corresponding rows and columns. M<-matrix(1:2,10,10) M[6,1:2]<-NA M[10,9]<-NA M<-as.matrix(as.dist(M)) print (M) 1 2 3 4 5 6 7 8 9 10 1 0 2 1 2 1 NA 1 2 1 2 2 2 0 1 2 1 NA 1 2 1 2 3 1 1 0 2 1 2 1 2 1 2 4 2 2 2 0 1 2 1 2 1 2 5 1 1 1 1 0 2 1 2 1 2 6 NA NA 2 2 2 0 1 2 1 2 7 1 1 1 1 1 1 0 2 1 2 8

Hi everybody, I would like to delete rows based on duplicate entries in column 3 in the data matrix X (size 60000 x 57). I have tried the unique(x) command as > data <- X[unique(X[,3]),] however, for some reason the command introduces a lot of NA's into the dataset. So, now I'm looking for a function that eliminates rows, if they have duplicate values in column 3. Does anyone

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I have a dataframe of 10 different columns (length of each column is the same). I want to eliminate any column that has 'NA' greater than 15% of the column length. Do i first need to make a function for calculating the percentage of NA for each column and then make another dataframe where i apply the function? Whats the best way to do this.

Dear colleges, I do not understand the following behaviour: > aa <- data.frame(a1= 1:10, a2= c(rep(NA, 5), 1:5) ) > aa a1 a2 1 1 NA 2 2 NA 3 3 NA 4 4 NA 5 5 NA 6 6 1 7 7 2 8 8 3 9 9 4 10 10 5 > aa[!aa$a2==1, ] # removing rows with a2==1 a1 a2 NA NA NA NA.1 NA NA NA.2 NA NA NA.3 NA NA NA.4 NA NA 7 7 2 8 8 3 9 9 4 10 10 5 I didn't

I'd like to remove duplicated rows within a matrix, with missing data being treated as wildcards. For example > x <- matrix((1:3), 5, 3) > x[4,2] = NA > x[3,3] = NA > x [,1] [,2] [,3] [1,] 1 3 2 [2,] 2 1 3 [3,] 3 2 NA [4,] 1 NA 2 [5,] 2 1 3 I would like to obtain [,1] [,2] [,3] [1,] 1 3 2 [2,] 2 1 3

Hi, Given a test matrix, test <- matrix(c(1,2,3,NA,2,3,NA,NA,2), 3,3) A) How to compute the counts of each column (excluding the NA) i.e., 3, 2, 1 B) How to compute the counts of each column (excluding the NA) that are greater than the column means ? i.e., 1, 1, 0 I could write a for loop, but hope to use better alternative. [[alternative HTML version deleted]]

Hi all, I would like to remove rows from a matrix, based on the frequency of missing values. If there are more than 10 % missing values, the row should be deleted. I use the following to calculate the frequencies, thereby getting a new matrix with the frequencies: freqNA=rowMeans(is.na(exprdata)) But is there a shorter way to remove the rows based on "(1-freqNA)>0.1"

Hello, I use read.xls from the gdata package to read in xlsx files. Sometimes these data.frames contain NA columns and rows only. I know how to get rid of those ones but here is the R output of a test data set read in with read.xls > t1 A B X D X.1 X.2 1 test 1 NA NA 2 <NA> asd NA

Dear List, I have a data matrix that consists of ~4500 rows and 25 columns (i.e. an exprSet object that I converted via the 'exprs' function into a data matrix) Now I want to remove/delete the rows where all exp. values in that particular row are below or equal to a specific cut-off value (e.g 1.11) I have tried using several commands to address this issue: >Matrix[rowSums(Matrix