similar to: Why only a "" string for heading for row.names with write.csv with a matrix?

Hi, I have 100000 units with 10 attributes (attr1, attr2, attr3, etc...) For instance: unit attr1 attr2 attr3 ... 1 a ww 12 2 a re 11 3 b ww 09 4 c yt 02 5 a qw 02 ... I'd like to answer to the question: a) what are the most frequent combinations of attributes? b) How could I describe the relations

Dear R experts, I would really appreciate if you had an idea on how to use more efficiently the aggregate method: More specifically, I would like to calculate the mean of certain values on a data frame,? grouped by various attributes, and then create a new column in the data frame that will have the corresponding mean for every row. I attach part of my code: matchMean <-

In R-devel (svn 49628) and back to at least R 2.7.0 we get inconsistent results when attempting to attach attributes to a variable with the value NULL. If we use attributes<- it finishes but changes the value to list(). > a<-NULL > attributes(a)<-list(attr1="First attribute", attr2=2+2i) > a list() attr(,"attr1") [1] "First

Ok, So, I''ve got two data tables associated through a foreign key. class Child < ActiveRecord::Base belongs_to :parent, :class => Parent, :foreign_key => "parent_id" # also has attr1, attr2 end class Parent < ActiveRecord::Base has_many :children, :class => Child, :foreign_key => "parent_id" end So, I''m trying to build the new/edit

Dear R users, I have two datasets: id1 <- c(rep(1,10), rep(2,10), rep(3,10)) value1 <- sample(1:100, 30, replace=TRUE) dataset1 <- cbind(id1,value1) id2 <- c(1,2,3) subtract.value <- c(1,3,5) dataset2 <- cbind(id2, subtract.value) I want to subtract the number of rows in the subtract.value that corresponds to the id value in dataset1. So for the 1 in id1, I want to

I find myself writing the following frequently: r = MyActiveRecord.where(:attr1 => cond1, :attr2 => cond2, ...) r.exists? ? r.first : r.create ... which has the effect of returning an instance of MyActiveRecord if all the conditions are met, or creating one if it doesn''t. A variant of this: c = MyActiveRecord.new(:attr1 => val1, :attr2 => val2, ...) r =

Dear r experts, Sorry for this basic question, but I can't seem to find a solution? I have this data frame: df <- data.frame(id = c("id1", "id1", "id1", "id2", "id2", "id2"), A = c(11905, 11907, 11907, 11829, 11829, 11829), v1 = c(NA, 3, NA,1,2,NA), v2 = c(NA,2,NA, 2, NA,NA), v3 = c(NA,1,NA,1,NA,NA), v4 = c("N",

Hi, From your example data, dat1<- read.table(text=" id1?? id2?? value a????? b?????? 10 c????? d??????? 11 b???? a???????? 10 c????? e???????? 12 ",sep="",header=TRUE,stringsAsFactors=FALSE) #it is easier to get the output you wanted dat1[!duplicated(dat1$value),] #? id1 id2 value #1?? a?? b??? 10 #2?? c?? d??? 11 #4?? c?? e??? 12 But, if you have cases like the one

Dear R users, I have a big text file formatted like this: x x_string y y_string id1 id1_string id2 id2_string z z_string w w_string stuff stuff stuff stuff stuff stuff stuff stuff stuff // x x_string1 y y_string1 z z_string1 w w_string1 stuff stuff stuff stuff stuff stuff stuff stuff stuff // x x_string2 y y_string2 id1

Hi Together, I have a problem with the plyr package - more precisely with the ddply function - and would be very grateful for any help. I hope the example here is precise enough for someone to identify the problem. Basically, in this step I want to identify observations that are identical in terms of certain identifiers (ID1, ID2, ID3) and just want to save those observations (in this step,

Hi Group, I have a data frame below. Within this data frame there are samples (columns) that are measured more than once. Samples are indicated by "idx". So "id1" is present in columns 1, 3, and 5. Not every id is repeated. I would like to create a new data frame so that the repeated ids are averaged. For example, in the new data frame, columns 1, 3, and 5 of the original

Hi - I have a data frame with a large number of observations (62,000 rows, but only 2 columns - a character ID and a result list). Sample: > my.df <- data.frame(id=c("ID1", "ID2", "ID3"), result=1:3) > my.df id result 1 ID1 1 2 ID2 2 3 ID3 3 I have a list of ID vectors. This list will have anywhere from 100 to 1000 members, and

When I use rbind() or rbind.data.frame() to add a row to an existing dataframe, it appears that attributes for the column of type "factor" are dropped. See the sample example below to reproduce the problem. Please suggest How I can fix this. Thanks, Sammy a=c("Male", "Male", "Female", "Male") b=c(1,2,3,4) c=c("great", "bad",

Thanks for pointing me out "aggregate", that works fine! There is one complication though: I have mixed types (numerical and character), So the matrix is of the form: A 1.0 200 ID1 A 3.0 800 ID1 A 2.0 200 ID1 B 0.5 20 ID2 B 0.9 50 ID2 C 5.0 70 ID1 One letter always has the same ID but one ID can be shared by many letters (like ID1) I just want to keep track of the ID, and get

Hello, with a data.frame like this : > toto <- data.frame(id=c("id1","id1","id2","id3","id3","id3"),dpt=c("13","13","34","30","30","30")) > toto id dpt 1 id1 13 2 id1 13 3 id2 34 4 id3 30 5 id3 30 6 id3 30 what is the most efficient ways to obtain : id

Hi all, I have a data.frame I received with data that look like this (comma separated strings in last row): ID Shop Items ID1 A1 item1, item2, item3 ID2 A2 item4, item5 ID3 A1 item1, item3, item4 But I would like to unbind the strings in col(2) items so that it will look like this: ID Shop Items ID1 A1 item1 ID1 A1 item2 ID1 A1 item3 ID2 A2 item4 ID2 A2 item5 ID3 A1 item1 ID3 A1 item3 ID3 A1

Hello, I am try to make a density plot where plots are stacked like the one found here: http://dsarkar.fhcrc.org/lattice/book/images/Figure_14_03_stdBW.png I am facing problems, however. Using the code example below, I'd like to generate a separate panel for each val of id2. Within each panel, I'd like to have individual histograms each on separate lines based on the value of id1. ?Note

Hi, I'm stuck with parsing data into R for heatmap representation. The data looks like: 1 id1 x1 x2 x3 .... x20 2 id1 x1 x2 x3 .... x20 3 id1 x1 x2 x3 .... x20 4 id1 x1 x2 x3 .... x20 ......... 348 id2 x1 x2 x3 .... x20 349 id2 x1 x2 x3 .... x20 350 id2 x1 x2 x3 .... x20 351 id2 x1 x2 x3 .... x20 ......... The data is sorted for the IDs (id1,id2 .....id40) and I like to

Hi all, I am working with some social network analysis in R and ran into a problem I just cannot solve. Each observation in my data consists of a respondent, some characteristics and up to five friends. The problem is that all of these five friends might no show up later as a respondent (observation). Therefore I might not have characteristics on all the friends listed in the data and I want to

Hello, I have a dataframe with 9 columns, and I would like to sort (order) the right-most eight of them alphabetiaclly, i.e.: ID1 ID2 F G A B C E D would become ID1 ID2 A B C D E F G Right now, I'm using this code: attach(data) data<-data.frame(ID1,ID2,data[,sort(colnames(data)[3:9])]) detach(data) but that's not very elegant. Ideally I could specify which columns to sort and