similar to: create a table in the console!!

i  want to print in the console and to have an excel file like this no_GWP                NbOfPolicyClass1[0-1000]     NbOfPolicyClass2[1000-3000]        NbOfPolicyClass3[> 3000] No_GWPMax=8    NbpolicyClass1=5                   NbpolicyClass2=4                            NbpolicyClass3 =3              i have do it like this:!!! data1 <-

----- Message transféré ---- De : Inchallah Yarab <inchallahyarab@yahoo.fr> À : r-help@r-project.org Envoyé le : Mardi, 18 Août 2009, 16h26mn 20s Objet : create a table in the console!! HI I want to do a table with R (in the console) GWP_Max NumberOfPolicies No_GWPMax 8 [0-1000] 4 [1000-3000] 3 [> 3000] 5 i begin by calculate the number of policies in each class :  Data1 <-

i have written this in R, > data1 <- read.csv2("c:/Total1.csv",sep=",") > data2 <- read.csv2("c:/GWPMax1.csv",sep=",") > M <- merge(data1, data2, by.x = "Policy.Number", by.y = "Policy.Number") > nrow(data1) [1] 20 > nrow(M) [1] 12 > NbOfPolicyWithoutGWPMax <- nrow(data1)-nrow(M) >

Hi, Actually, i use the function merge like this: (Data1 <- Data1[1:7,1:3])   Policy.Number AXA.Entity Country 1    1060000077        BNL     BNL 2       4001023         CH     BNL 3    1060000006         UK     BNL 4       4001025         CH     BNL 5      6.00E+13        USA     BNL 6       6100001         UK     BNL 7       4001028        USA     BNL > Data2 <-

i have a matrice M and i want to extract only rows where GWP_Max is positif and smaller than 1000 but it is given me this:!!!??? > M    Policy.Number   GWP_Max 1        4001023       500 2        4001025       700 3        4001028       600 4        4001062    2335.1 5        6100001      2000 6     1060000006      1400 7     1060000009     77.19 8     1060000071  18898.88 9     1060000073

Hello, I have a data set that needs to be combined so that rows are summed by a group based on a certain variable. I'm pretty sure rowsum() or rowsums() can do this but it's difficult for me to figure out how it will work for my data based on the examples I've read. My data are structured like this: Plot SizeClass Stems 12 Class3 1 12 Class4

Hi, I'm working with Version 1.9.0 (2004-04-12) on Windows 98/NT/2000 where I found the following wrong (?) behavior of setValidity(). I already mentioned this on the R-help list (2004-06-11, was "setValidity changes Extends?") , but as I got no answer I tried to figure out what's happening. Well, setValidity() behaves not as I would expect (something about the

I want to create a script for IVR that compiles responses, aggregates them to a total number. Then, run an equation based on the result. Press 1 for X (X is a positive number 500) Press 2 for Y (Y is a positive number 200) Press 3 for Z (Z is a positive number 300) Press 20 to calculate the results = 500+200+300 =1000 then, exten => s,n,Read(NUMBER,,1000) exten => s,n,SayDigits(${NUMBER})

Hi, Please advice on what type of graph can be used to display the following data set. I have the following: Name Class a Class 1 a Class4 b Class2 b Class1 d Class3 d Class5 e Class4 e Class2 So each entry in name can belong to more than one class. I want to represent the data as to see where

I keep expecting R to have something analogous to the =count function in Excel, but I can't find anything. I simply want to count the data for a given category. I've been using the ddply() function in the plyr package to summarize means and st dev of my data, with this code: ddply(NZ_Conifers,.(ElevCat, DataSource, SizeClass), summarise, avgDensity=mean(Density),

Hello, i'm a french student of medical oncology and i'm working on breast cancer. I have a variable with the histologic type of tumor wich is between 1 and 5. I use as.factor function to make some variable with level between 1 and 5. When i put it in the cox model i have only the level between 2 and 5. The level 1 doesn't appear. I think i have to change the number of level but i

Dear All, After having overcome the issue of legends (thanks, Thierry, once more), I am trying to use facetting, but here also I can not find how to do this. I do not want to use qplot, but rather the more flexible options. However, it seems I am doing still something pretty stupid, because I always get an error, even if it seems I am doing everything like the examples. My code is below.

I've got a table of 1 row per observation. 16 questions * n subjects * 4 classrooms (2 teachers * 2 conditions) I'd like to run some simple regressions that look something like this: lm(length ~ elapsed) I'd like to do the regressions several times, split out by questionkey, student, class. What I've been doing is using a series of which's to create new data sets (e.g.

Hi, I'm new to R, and I have searched helpfiles and this forum on my 2 questions. Hope you guys can help me out! :-) Many thanks in advance! Cheers, Lars Q1: I imported a csv file with columnames subject and class. There are about 1000 different classes... It looks like this: subject1, class1 subject1, class2 subject2, class1 subject2, class3 ... subject999, class1 subject999, class2

Dear List, I am trying to assess the prediction accuracy of an ordinal model fit with LRM in the Design package. I used predict.lrm to predict on an independent dataset and am now attempting to assess the accuracy of these predictions. >From what I have read, the AUC is good for this because it is threshold independent. I obtained the AUC for the fit model output from the c score (c =

I has several model objects that flow down like a tree: Class1 has_many Class2 Class2 has_many Class3 and so on. when are the child records actually created? If I do: c1 = Class1.find(:all) are the child objects (C2s below) created then or not until i do something like: c2s = c1.C2s while iterating through the c1s? If the form, that''s cool, no problem, but If I''ve got

Hello, I have a question concerning the R-function chisq.test. For example, I have some count data which can be categorized as follows class1: 15 observations class2: 0 observations class3: 3 observations class4: 4 observations I would like to test the hypothesis whether the population probabilities are all equal (=> Test for discrete uniform distribution) If you have a small sample size

Not the clearest of error messages. A successful cannot load. May 7 21:05:29 10.10.10.213 dovecot: child 21500 (login) returned error 89 May 7 21:05:29 10.10.10.213 dovecot: child 21501 (login) returned error 89 May 7 21:05:29 10.10.10.213 dovecot: child 21502 (login) returned error 89 May 7 21:05:29 10.10.10.213 dovecot: child 21503 (login) returned error 89 May 7 21:05:29 10.10.10.213

My external node classifier returns some arrays in the list of parameters. Example output (names have been changed to protect the innocent): $ ./node_classifier a.b.com --- %YAML:1.0 "classes": ["class1", "class2", "class3"] "parameters": "hostname": "a" "name": "a" "domain":

Hi, I have a question about running multiple in regressions in R and then storing the coefficients. I have a large dataset with several variables, one of which is a state variable, coded 1-50 for each state. I'd like to run a regression of 28 select variables on the remaining 27 variables of the dataset (there are 55 variables total), and specific for each state, ie run a regression of