similar to: MySQL

Hi, I have a dataset with x and y coordinates and in each point I have an identity of point, in some cases I can have more then one identity by point. My dataset is something like this: > x <- rep(c(1:4),4) > y <- rep(c(1:4),c(4,4,4,4)) > area1 <- sample(factor(rep(c("a","b","c","d"),4))) > area2 <-

Dear list, When I use VennDiagram package, I got a error as follow: venn.plot <- draw.pairwise.venn( area1 = 3186, area2 = 325, cross.area = 5880); Error in draw.pairwise.venn(area1 = 3186, area2 = 325, cross.area = 588) : Impossible: cross section area too large. Does anyone have suggestion? Thank you.

I'm reading Torgo (2010) *Data Mining with R*<http://www.liaad.up.pt/~ltorgo/DataMiningWithR/code.html>in preparation for a class I'll be teaching next quarter. Here's an example that is very non-functional. > pH <- c(4.5,7,7.3,8.2,6.3) > names(pH) <- c('area1','area2','mud','dam','middle') > pH area1 area2 mud dam

Hi there, I am not getting anywhere near a solution, so here is my question. I have searched the archives and didn't find a solution, but maybe my search didn't use the right words. So here it is: I have a dataframe with the following structure factor1 factor2 value In the (rather large) dataset I have to work on, there are some factor combinations missing, e.g. factor1 <-

Hi R-helpers, Can some one tell me how to train 'mynn' of this type?: mynn <- nnet(y ~ x1 + ..+ x8, data = lgist, size = 2, rang = 0.1, decay = 5e-4, maxit = 200) I assume that this nn is untrained, and to train I have to split the original data into train:test data set, do leave-one-out refitting to refine the weights (please straighten this up if I was wrong). I just don't know

I have a dataframe ("mydf") that contains "differences of means". I wish to test whether these differences are significantly different from zero. Below, I calculate the t-statistic for each column. What is a "good" method to calculate/look-up the p-value for each column? mydf=data.frame(a=c(1,-22,3,-4),b=c(5,-6,-7,9)) mymean=mean(mydf) mysd=sd(mydf)

I'm using area() to evaluate the area under 2 functions (defined using approxfun()) and the result is in contradiction with visual inspection (please see: http://sites.google.com/site/eospansite/dummy/problem_area.jpg ) The area under the red curve should be larger than the one under the black curve, but I'm geting the opposite result using area(). This is what I'm doing:

Is it true that append=T does not work in assignTable() in RMySQL ? More specifically: I cannot append a data.frame to an existing table in a MySQL database, although I can use the same data.frame to create a new table. Even more specifically: > assignTable(con,"employee",dita,append=T) Error in execStatement.MySQLConnection(con, statement, ...) : RS-DBI driver: (could not

Dear all, I am trying to merge two data frames based on a common column but for this common column both data frame do not have the same length and associated information. I checked previous exemples in the list but was not able to apply them in my case... Is someone know how to do that? Below is my code with the expected result: # data frame 1 Id1 <- c(1,1,1,2,2,2,3,3,3) Habit1 <-

Dear All I would really appreciate some help with a script which a colleague wrote for me (attached), but I am having problems running (and have not been able to contact my colleague). The script is designed to compare the area of suitable habitat in binary projections of a large number of species current and future distributions, and create an excel file detailing the total area suitable in the

Hi, I recently discovered the R program and I thought it could be useful to me. I have to analyse data saved as .Px file (x between 0 and 8 - .P0 files have 18 lines at the beginning that I have to skip). New files are generated everyday. This is my strategy : In order to analyse the data, I first want to copy the new data in a database in MySQL (which already contains the previous data). So

My data frame looks like: SightingID PA1 PA2 PlotID InOverlap Area1 2001 1 -99 392 Y 0.22 2002 1 -99 388 Y 0.253 2008 1 NA 104 N 0.344 2010 1 NA 71 N 0.185 2012 1 NA 61 N 0.166 2013 1 NA 61 N 0.227 2014 1 NA 62

Hi there, Could someone help me with the following programming problem..? I have written a function that works for my intended purpose, but it is quite closely tied to a particular dataframe and the names of the variables in this dataframe. However, I'd like to use the same function for different dataframes and variables. My problem is that I'm not quite sure how to tell my function in

Hi all, This is a potentially very stupid question about MySQL <-> R interaction, but I have not been able to solve it. I'm just trying to connect R to my MySQL databse, and gets this: > library(RMySQL) Loading required package: methods > m <- dbDriver("MySQL") > con <- dbConnect(m,group="testdb") Process R segmentation fault at Wed Oct 16 07:04:30

Hi all: Here's a question about result of loglinear analysis. There're 2 factors:area and nation.The raw data is in the attachment. I fit the saturated model of loglinear with the command: glm_sat<-glm(fre~area*nation, family=poisson, data=data_Analysis) After that,I extract the coefficients: result_sat<-summary(glm_sat) result_coe<-result_sat$coefficients I find that all the

http://bugs.freedesktop.org/show_bug.cgi?id=13319 Summary: YV12 and YUY2 overlay broken on PPC with NV34M Product: xorg Version: 7.3 Platform: Other OS/Version: All Status: NEW Severity: normal Priority: medium Component: Driver/nouveau AssignedTo: nouveau at lists.freedesktop.org

Given the data structure below, how can I create a bar plot for the values of disc for each area grouped by year? bar <-structure(list(year = c(2003, 2003, 2003, 2003, 2003, 2003, 2003, 2007, 2007, 2007, 2007, 2007, 2007, 2007), area = structure(c(6L, 4L, 1L, 2L, 3L, 5L, 7L, 6L, 4L, 1L, 2L, 3L, 5L, 7L), .Label = c("AK", "ID", "MT", "NW",

Estimad en s, quería realizar una consulta Dado un data frame llamado aves, como puedo sustiuir las variables area, dist y distm por sus logaritmos en base10 y volver a crear un data frame? Muchas gracias Saludos Susana [[alternative HTML version deleted]]

Hi again, this is the second part of the patch extending lua. This time it adds the dmi functions (com32/modules/dmi*) to lua: dmi.supported(): returns true if DMI is supported dmi.gettable(): returns array of key, value pairs containing system info Sorry, but this patch does not apply cleanly if [PATCH 1/2] was applied before. There's just one line to fix in com32/lua/src/linit.c

Greetings All. We wanted to be able to parse the DHCP values and options and write a lua script based on the information found. We are also using the CPU flags, but thankfully in at least version 4.04 there is already some CPU value parsing even if it isn't documented. Using the information from the CPU table we wanted to be able to choose the kernel to boot. Using the DHCP table