similar to: Reshape, melt and cast query

I am using the following commands for plotting kernel density for three kinds of crops density(s22$Net_income_Total.1, bw="nrd0",adjust=1, kernel=c("gaussian"))->t plot(t, xlim=c(-30000,40000), main="Net Income Distribution", axes=F, ylim=c(0,0.00035). xlab="Value in Rupees") par(new=T) density(s33$Net_income_Total.1, bw="nrd0",adjust=1,

I have data on area under cultivation of a crops for 17 states..I need a scatter plot to be made for the following assignment Read the data file /Data/ep602/areas.csv, and make a scatter plot that displays area under rice in 1960s on the x axis, and percentage change in area under rice between 1960 and 1990 on the y axis. Let origin of the plot be at (50 per cent of area of rice in India as a

I'm havinf a problem with a simple file i have the following data State 1960 1970 1980 1990 1 All India 35988.70 37346.00 39707.30 42321.00 2 Andhra Pradesh 3431.03 3163.27 3687.23 3695.63 3 Assam 1902.93 2001.60 2278.47 2525.33 4 Bihar 5277.07 5133.80 5138.70 4662.57 5 Gujarat 538.13 456.10 484.23 590.47 6

I have this assignment to do and after ten hours of constant trying my eyes ache and i give up.. all i'm able to get is this plot please help me these are the commands i have used till now read.table(file.choose(), sep=";", header=T) read.table(file.choose(), sep=";", header=T)->areas melt(areas,id=c("Year","State"),m=c("Rice"))->

Hi all, Firstly excuse-me by this off-topic question. I'm very confused to decide what is the better analysis to use. Whem the experiments is a tradicional design of manipulative experiments, it is easy to decide. But in natural observations is too complicated. I have 6 farms, each farm cultives some sugarcane's varieties (maybe or not the same varieties by farm). For each farm I make

Hi, I have Mandriva 2006 x86_64. I tried to install wine, but the binaries are for 32 bits and the result is very instable (win programs close suddenly, no internet available for those programs, etc...) So I tried to compile wine 0.9.14 from source, but I have an error during make when "searching for -lXext" : LD_LIBRARY_PATH="../../libs/unicode:$LD_LIBRARY_PATH"

I have been trying to compile Samba 3.0.4 on a SunFire v880 running Solaris 9 but "make" generates a fatal error. My goal is to get Samba compiled with the "--with-ldapsam" option so that I can use SunOne Directory Server 5.2 as the back-end repository for user authentication. I have gcc version 3.3.2 installed in /usr/local/bin/gcc which I have used to successfully compile

Dear all,   I have data from the following experimental design and trying to fit a mixed model with lme function according to following steps but struggling. Any help is deeply appreciated.   1) Experimental design: I have 40 plants each of which has 4 clones. Each clone planted to one of 4 blocks. Phenotypes were collected from each clone for 3 consecutive years. I have genotypes of plants. I

I planted NUT into our project. But my boss asked me: how do you promise the UPS compatibility to those who use our device? I know the compatibility list of NUT is a great reference. However, is also a good idea for us to test the compatibilitywith our complete device. Therefore, I wonder how NUT developers actually test the compatibility with so many type of UPSes? And are there any

Hi , I am struggling with these two question . Any help would be appreciated ,Im looking at doing them on r ? 1. Tests for indications of asbestos in the lungs of employees at an insulation manufacturer resulted in four persons with positive indications of asbestos being sent to a medical center for further testing . if 45% of the employees have positive indications of asbestos in their lungs ,

Hello, I'm trying to analyse the spatial organization of different fields planted with different varieties (each field has only one variety), but I have problems trying to understand the results of the test I did. To do this, I created different neighbourhood matrix. For example, for the first matrix, fields are considered as neighbours if they are distant from 0 to 1000 meters from each

Hi, I'm fitting a relatively simple growth model to some forest plot data. Two species of trees were planted in different mixtures in 10 (nearly-adjacent) plots and measured on four occasions over 10 years. The model is constructed in terms of the diameter increments (per year; DI) in the 3 intervals, in which DI is modelled as a function of mid-interval D and DSQ. The details of the

Hi everybody, I am trying to fit a model with the lmer function for mixed effects. I have an experimental design consisting of 5 field plots. Each plot is divided in 12 subplots where the influence of three factors on the growing of tree seedlings is tested: (1) seed (1 = presence; 0 = absence); (2) seedling species (oak holm vs. pine); (3) treatment (three different treatments). In each of

Hello, I implemented two functions reshape_long and reshape_wide (see full working example below) to reshape data frames. I created several small examples and the two functions seemed to work properly. However, using the reshape_wide function on my real data sets (about 200.000 to 300.000 rows) failed. What happens is set all values for X, Y and Z were set to 1. The structure of my real data

Hi, Try: dat1 <- read.csv("precipitationRglimclim.csv",header=TRUE,stringsAsFactors=FALSE,sep="\t") library(reshape2) dat2M <- melt(dat1,id.var=c("year","month","day")) dat2M1 <- dat2M[with(dat2M,order(year,month,day,variable)),] ?dim(dat2M1) #[1] 1972320?????? 5 ?row.names(dat2M1) <- 1:nrow(dat2M1) ?colnames(dat2M1)[4:5] <-

Hi:I recently started using the melt function and found that it is very useful and powerful,however I can't seem to find the way to change the default column header "value" to my custom column name. Does anyone know how to go about this? any suggestions are very appreciated. Thanks Felipe D. Carrillo Fishery Biologist US Fish & Wildlife Service California, USA

I have a data frame that is the result of a cast (reshape) operation. I deleted the variable column and tried to melt the resulting data frame. Depending on which method I use to delete the column I get different error messages when melting: > head(tinfos) vpn group trial_no item relation trial_type rt variable # 1 102 2 1 4351 diag1 distractor 8471 fix_d 27

Dear R Users, I'm trying to use the reshape package to 'melt' my gridded data into column format. I've done this before on individual files, but this time I'm trying to do it on a directory of files (with variable file names) - therefore I have to also use the 'assign' command. I have come up against a couple of problems however and am therefore seeking advice... >

Hi, I have installed R on my computer with windows 7 . I also installed reshape software, but I am not being able to work with melt cast commands . I have chjecked the commands.It is not working. Thankyou, Deepika [[alternative HTML version deleted]]

I want to make a stacked bar plot with one bar for two variables from my data "chir", the two variables have about 100 values like no, yes and na. I want to show how many no, yes and na they both have together with the stacked bar. I tried to melt these to variables first like this: melt1=melt(data_chir, measure.vars=c("N1_re", "N2_re"), var="zpd") but it