similar to: reshaping a dataset for a network

I've examining a number of linear regression models on a large dataset following the basic ideas presented here http://www.r-bloggers.com/r-calculating-all-possible-linear-regression-models-for-a-given-set-of-predictors/ Calculating all possible linear regressions . I run into a problem with ldply when I have a formula that includes no intercept. Here's a simple test to show what happens.

Seems like this should be easy but I'm struggling a bit. How do I rearrange a data frame to go from the first one to the second shown below ? State Date lbs TX 200701 400 TX 200702 650 TX 200703 950 TX 200704 1000 FL 200701 200 FL 200702 300 FL 200703 500 FL 200704 333 NJ 200701 409 NJ 200702 308 NJ 200703 300 NJ 200704 800 Date TX FL NJ 200701 400 200 409 200702 650

dear all, thank you for reading. I have a dataset of artists and where and when they had an exhibition. I'd like to create an affiliation network in the form of matrix, telling me which aritist have been in the same at the same time. I manage to do it, but given that I have 96000 observation the program takes 30 months to complete. her what i have done. the data look like this Artist

Dear all, I?m having trouble getting a list of regression variables back into a dataframe. mydf <- data.frame(x1=rnorm(100), x2=rnorm(100), x3=rnorm(100)) mydf$fac<-factor(sample((0:2),replace=T,100)) mydf$y<- mydf$x1+0.01+mydf$x2*3-mydf$x3*19+rnorm(100) dlply(mydf,.(fac),function(df) lm(y~x1+x2+x3,data=df))->dl here I?d like to use ldply(dl,coef(summary)) or something

Hello R User, I was trying to display r.squared and p value in table from regression, but I could not display these parameters in the table (matrix) for example individual <- c(1,1,6,8,8,9,9,9,12,12) day <- c(4,17,12,12,17,3,9,22,13,20) condition <- c(0.72, 0.72, 0.67, 0.73, 0.76, 0.65, 0.68, 0.78, 0.73, 0.71) test <- data.frame(individual, day, condition) ind.id <-

Dear R users, I have a problem with reshaping data. I know such questions have been asked before, but I can't get it right, neither with the reshape function nor with the melt function. My dataset has about 407 variables and about 48000 cases. Each case looks as follows: V1 v2 v3 v4 v5 v6 v7 x1 y1 x2 y2 .... x200 y200 V1 is unique, v2-v7 are

Wow ! so many thanks Arun and Rui works like a charm problem solved 2013/4/13 arun <smartpink111@yahoo.com> > Hi, > Try this; > library(reshape2) > res<-dcast(Input,people~place,value.var="time") > res[is.na(res)]<-0 > res > # people beach home school sport > #1 Joe 5 3 0 1 > #2 Marc 0 4 2 0 > #3 Mary

Hi, I have a dataframe basically like this: > head(asturias.gen2011[,c(1,4,9:14)]) municipio total upyd psoe pp iu fac tipo 440 Allande 2031 1.44 31.10 39.75 4.01 21.62 1000-10000 443 Aller 12582 1.37 33.30 37.09 15.53 10.35 10000-50000 567 Amieva 805 1.48 32.69 37.36 6.15 20.16 <1000 849

json_dir is a list of JSON lists mapping lat/long route points between locations using CloudMade's API. post_url is the URL of the HTTP request for (n in json_dir) { i = i + 1 if (typeof(json_dir[[i]]) != "NULL") { if (i == 1) { dat_add <- ldply(json_dir[[i]], function(x) t(data.frame(x)), .progress = "text")

for example : I have files with the name "ma01.dat","ma02.dat","ma03.dat","ma04.dat",I want to read the data in these files into one data.frame flnm<-paste("obs",101:114,"_err.dat",sep="") newdata<-read.table(flnm,skip=2) data<-(flnm,skip=2) but the data only contains data from the flnm[1] I also tried as below : for

In glm() you can use the summary() function to recover the shape parameter (the reciprocal of the dispersion parameter). How do you recover the scale parameter? Also, in the given example, how I estimate and save the geometric mean of the predicted values? For a simple model you can use fitted() or predicted() functions. I will appreciate any help. ? ? ? #Call required R packages require(plyr)?

Hello I have 4 1000*1000 matrix A,B,C,D. I want to use the corresponding element of the 4 matrices. Using the "for loop" as follow: E<-o for (i in 1:1000) {for (j in 1:1000) { E<-fisher.test(matrix(c(A[i][j],B[i][j],C[i][j],D[i][j]),2))#call fisher.test for every element } } It is so time-consuming Need vectorization Yours sincerely ZhaoXing Department of

> On Apr 17, 2018, at 10:10 AM, Allaisone 1 <allaisone1 at hotmail.com> wrote: > > > Hi all > > I have a list of multiple datframes with the same column headers. The last column in each datframe contains a vector of "Interval" class after I have produced this column using "lubridate" package. I needed to convert my list of dataframes to be in a single

I have 100+ .csv files which have the basic format: > test X Substance1 Substance2 Substance3 Substance4 Substance5 1 Time1 10 0 0 0 0 2 Time2 9 5 0 0 0 3 Time3 8 10 1 0 0 4 Time4 7 20 2 1 0 5 Time5

Dear all, I would appreciate please a piece of help regarding the use of acast/dcast functions in reshape2 package. Specifically, I'm working with a data frame, that has information about SAMPLE, GENE, and TYPE of MUTATION (as shown below): Sample Gene Type 22M AEBP1 SNV 17M AEBP1 SNV 22M ATR INDEL 22M ATR SNV 11M BTK SNV 11M BTK

Hi all I have a list of multiple datframes with the same column headers. The last column in each datframe contains a vector of "Interval" class after I have produced this column using "lubridate" package. I needed to convert my list of dataframes to be in a single dataframe for further analysis. I did this using the following syntax : SingleDataframe <- ldply

Hello I have a dataset of people spending time in places. But most people don't hang out in all the places. it looks like: > Input<-data.frame(people=c("Marc","Marc","Joe","Joe","Joe","Mary"), + place=c("school","home","home","sport","beach","school"), +

Hi, I'm trying to move to R the last few data handling routines I was performing in SAS. I'm working on stomach content data. In the simplified example I provide below, there are variables describing the origin of each prey item (nbpc is a ship number, each ship may have been used on different trips, each trip has stations, and individual fish (tagno) can be caught at each

Hello All, I was wondering if it's possible to reshape data from long to wide in R without using a "timevar". I've pasted some sample data below along with some code. The data are sorted by Subject and Drug. I want to transpose the Drug variable into multiple columns in alphabetical order. My data have a variable called "RowNo" that functions almost like a

Hello R users, I am fairly new to R and was hoping you could point me in the right direction I have a set of text files (36). Each file has only two columns (id and count) , I am trying to figure out a way to load all the files together and then have them ordered by id into a matrix data frame. For example If each txt file has : ID count id_00002 20 id_00003 3 A Merged File: ID