similar to: advanced tabulation

Hi, I am trying to reproduce some functionalities of Excel pivot table in R, sadly, I couldn't figure out how to do it. I am wondering if this is even possible in R. Does anyone know? Here is an example: year=rep(2003,16) quarter=rep(1:4,each=4) sales=1:16 company=rep(c("a","b","c","d"),4) df=data.frame(year,quarter,sales,company) #this is the

hello, using the package "descr" i created a crosstab e.g.: Table <- crosstab(age,question,weight=pond) "age": being a variable that consists of the surveyed data of the ages of children: the values are "6 years", "7 years" and "8 years". "question": is a variable that consists of the answers of these children to a question: the

Hi, I have a huge number of categorical variables, say at least 10000, and I put them into a matrix, each column is one variable. The question is: how can I make all of the pairwise cross tabulation tables efficiently? The straightforward solution is to use for-loops by looping two indexes on the table() function, but it was just too slow. Is there a more efficient way to do that? Any guidance

Hi all, I have a data set x1 x2 x3 1 2 1 1 2 3 2 1 2 1 2 1 3 1 1 I want to tabulate in the following way. 1 2 3 x1 3 2 1 x2 2 3 0 x3 3 1 1 It is just like frequency distribution Any help is highly appreciated [[alternative HTML version deleted]]

Hi every one, how to get frequency distributions for one variable across other variable. ex: var1=age, var2=height i need frequency distribution of age across height. Thanks in Advance. -- View this message in context: http://www.nabble.com/cross-tabulation-for-frequency-distributions-tp24968531p24968531.html Sent from the R help mailing list archive at Nabble.com.

Hello, might be rather easy for R pros, but I've been searching to the dead end to ... twsource.area <- table(twsource, area, useNA="ifany") gives me a nice cross tabulation of frequencies of two factors, but now I want to convert to pecentages of those absolute values. In addition I'd like an extra column and an extra row with absolute sums. I know, Excel or the

I am aware of table(is.na(df$var)) but is there an efficient way of create a table that shows the number of missing values in each variable of a data frame? Right now I am forced to create a new variable, varna<-is.na(df$var), for each variable of the data frame, bind them to a new data frame and tabulate it, but surely there is a simpler way? any help is greatly appreciated, angelo

Hi R, This is a cross tabulation question. Suppose that, > d=read.table("clipboard",header=F) > d V1 V2 V3 A One Apple A One Cake A One Cake B One Apple B One Apple B One Apple > table(d$V2,d$V3) Apple Cake One 4 2 But, I don't want the count to be like the above. Here, it is counting the

Hi, I am attempting to tabulate binned data. The '1' represents the appearance of the focal mouse pup, and '2' represents the disappearance of the focal mouse pup. The code written below is intended to calculate the total time spent appeared out of 3600s. For Sample 1, both the hand calculation and R code yield the same result, 50. A problem seems to occur when '1' is the

I have a data frame with a number of observed and predicted values by classification as shown below: Count Volume FCLASS 1 55000 60000 Grade Separated 2 43000 39000 Grade Separated 3 26000 26500 Major Arterial 4 19500 20000 Major Arterial ... There are four classes here: Grade Separated, Major Arterial, Minor Arterial, and Collector I am looking

R-helpers: I have a data frame containing 4 factor variables (let's say A,B,C, and D) and 1 numerical variable (N). I would like to produce a cross-tabulated data frame in which A,B,C are individual columns, each factor of D is its own column, and the field is calculated as a given function of N (I would like to have two output data frames, one with the mean(N) and one with the

Hi useRs! I would like to know how to make aggregated data.frame with aggregate() tabulated. For example, I run the following command to aggregate re with respect to group1 and group2. > (aggr <- with(final, aggregate(re, group1, group2, mean))) Group.1 Group.2 x 1 1992 15 0.16392 2 1993 15 0.15467 3 1994 15 0.15456 4 1995 15 0.15391

hi, i'm new in R and i need some help. Please, ¿do you know a function how can process cross tables for many variables and show the result in one table who look like this?: +----------------------------------------------------+ |------------------ | X variable | |----------------- | Xop1 | Xop2 | Xop3|.....| +----------------------------------------------------+ |Yvar1 |

I think this is one for Gabor. I don't seem to be able to find my way to an answer despite numerous rereadings of factor and table. Here is a toy example: ### Some data EthnicCode <- c("European/Other", NA, "European/Other", "European/Other", "Pacific", "European/Other", "European/Other",

I have a data frame with data similar to this: NameA GrpA NameB GrpB Dist A Alpha B Alpha 0.2 A Alpha C Beta 0.2 A Alpha D Beta 0.4 B Alpha C Beta 0.2 B Alpha D Beta 0.1 C Beta D Beta 0.3 Dist is a distance measure between two entities. The table displays all to all distances, but the

I am quite new to R, so please bear over with me if I have problems with the R terminology. I want to (try to) use R for some analyses within vegetation ecology, using the vegan package. I have my data in a postgresql database, and I manage to get them into R as a dataframe with columns for respectively: Name of the analysed m2, Name of the species, coverage of species in the square in %. I

Hi, I've read in the past a thead in the R discussion list about the multi-valued type variable (what was called checklist). At the moment Gregory had intention to add some general code in his gregmisc package. I'm wondering if there's some general code / packages available ? A general class for taking account this type of variable would be very useful in the domain of survey

Full_Name: Frank Harrell Version: 1.6.1 OS: RedHat 8.0 Linux Submission from: (NULL) (128.143.108.90) I get an error when trying to load a URL that contains a file that was saved using save(object, compress=TRUE): > load('http://hesweb1.med.virginia.edu/biostat/s/data/sav/kprats.sav') Error in gzfile(file, "rb") : unable to open connection In addition: Warning message:

The Design library has been fully ported to R except for Cox proportional hazards regression modeling (using Therneau's survival package) which will be available in about two weeks. It will take much longer to make all the example code executable, is it currently contains many examples for which data are not provided. Thanks to Xiao Gang Fan <xiao.gang.fan1 at libertysurf.fr> who

The Design library has been fully ported to R except for Cox proportional hazards regression modeling (using Therneau's survival package) which will be available in about two weeks. It will take much longer to make all the example code executable, is it currently contains many examples for which data are not provided. Thanks to Xiao Gang Fan <xiao.gang.fan1 at libertysurf.fr> who