search for: var9

...0 1 3 1 0 1 4 0 1 1 5 0 1 1 > dat1 id var4 var5 var6 2 1 0 1 3 1 0 1 6 0 1 1 7 0 1 1 > dat2 id var7 var8 var9 2 1 0 1 5 1 0 1 6 0 1 1 8 0 1 1 Basically what I'd like to do is combine these variables on id and create one large data frame that looks like the following. > dat3 id var1 var2 var3 var4...

Dear all, I have a dataset that looks like this: x <- read.table(textConnection("col1 col2 3 1 2 2 4 7 8 6 5 10"), header=TRUE) I want to rewrite it as below: var1 var2 var3 var4 var5 var6 var7 var8 var9 var10 1 0 1 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 1 0...

...<- c(0.44,0.07,0.49) range_prob[[8]]  <- c(0.54,0.06,0.40) range_prob[[9]]  <- c(0.26,0.62,0.12) range_prob[[10]] <- c(0.65,0.19,0.16)   pdf <- expand.grid(range_prob)   data_lab$probs <- apply(pdf, 1, prod)   joint_probs = xtabs(probs ~ Var1 + Var2+Var3+Var4+Var5+Var6+Var7+Var8+Var9+Var10, data = data_lab)   write.csv(data.frame(joint_probs), 'joint_probs.csv', row.names = FALSE) ONS = read.csv('joint_probs.csv')   Names = NULL   for (i in 1:length(joint_probs))  {        Names[i] = paste(ONS$Var1[i], ONS$Var2[i], ONS$Var3[i], ONS$Var4[i], ONS$Var5[i], ONS$Va...

> Dear All > > I have data as follows. > > D T M L > 0.20 1 03 141 > 0.32 1 07 62 > 0.50 1 05 49 > 0.80 1 04 46 > 0.20 2 14 130 > 0.32 2 17 52 > 0.50 2 13 41 > 0.80 2 14 36 > 0.20 3 24 120 > 0.32

Let's say I have a program that returns variables whose names may be any string within the vector NAMES=c("varA","varB","varC","varD","varE","varF"..."varZ"), but I do not ever know which ones have actually been created. So in one example output, "varA", "varC", and "varD" could exist, but

...7 7 12 12 12 9 6 6 var4 4 5 4 10 12 9 2 2 2 var5 4 5 4 10 9 10 3 2 3 var6 5 4 5 2 3 2 1 3 5 var7 5 4 5 7 7 7 3 3 3 var8 3 4 3 10 10 8 4 2 4 var9 3 4 3 2 2 2 2 2 2 var10 3 3 3 4 4 4 3 1 2 Table 2 unknown var1 23 var2 4 var3 7 var4 4 var5 4 var6 6 var7 5 var8 3 var9 3 var10 3 Thanks RS [[alternative HTML version deleted]]

...7 7 12 12 12 9 6 6 var4 4 5 4 10 12 9 2 2 2 var5 4 5 4 10 9 10 3 2 3 var6 5 4 5 2 3 2 1 3 5 var7 5 4 5 7 7 7 3 3 3 var8 3 4 3 10 10 8 4 2 4 var9 3 4 3 2 2 2 2 2 2 var10 3 3 3 4 4 4 3 1 2 Table 2 unknown var1 23 var2 4 var3 7 var4 4 var5 4 var6 6 var7 5 var8 3 var9 3 var10 3 Thanks RS [[alternative HTML version deleted]]

Dear R-helpers, I have a list containing 5000 elements, each element is a dataframe containing one ID column (identical over the 5000 dataframes) and 9 numeric variables, e.g. ID VAR1 VAR2 VAR3 ... VAR9 I would like to create a new dataframe containing the ID column and the mean values of the 9 numeric variables. So, the structure of this new dataframe would be identical to the structure of the dataframes stored in my list (and the ID column would also be identical) but the values would be mean v...

...using pca. I have tried using CLUSPLOT(), but that only allows for 'princomp' where I need 'prcomp' as I do not want to reduce my columns. Is there a way to edit the CLUSPLOT() code to use 'prcomp', please? # sample of my data PRVID,VAR1,VAR2,VAR3,VAR4,VAR5,VAR6,VAR7,VAR8,VAR9,VAR10,VAR11 PRV1,0,54463,53049,62847,75060,184925,0,0,0,0,0 PRV2,0,2100,76,131274,0,0,0,0,0,0,18 PRV3,967,0,0,0,0,0,0,0,0,3634,0 PRV4,817,18344,3274,9264,1862,0,0,141,0,0,0 PRV5,0,0,0,0,0,0,29044,0,0,0,0 PRV6,59,6924,825,3008,377,926,0,0,10156,0,5555 PRV7,11,24902,36040,47223,20086,0,0,749,415,0,0...

var1 var2 var3 var4 var5 var6 var7 var8 var9 var10 gold 2 3 1 2 4 0 1 4 4 3 2 2 4 2 4 3 4 2 4 4 4 2 3 3 0 0 4 1 0 2 4 4 2 1 4 0 3 2 0 0 2 4 4 2 3 4 0 2 2 0 0 0 3 4 2 2 2 3 2 2 0 0 0 2 4 2 2 4 1 1 2 0 0 3 3 3 2 3 4 1 4 0 0 0 0 3 4 2 3 1 0 2 2 1 0...

...rting a character string to a R object. Let me describe this by an example; > dim(a) [1] 270 14 > dim("a") NULL > names(a) [1] "Var1" "Var2" "Var3" "Var4" "Var5" "Var6" "Var7" "Var8" "Var9" [10] "Var10" "Var11" "Var12" "Var13" "Var14" > names("a") NULL I realise that the character string lacks both a dimension and any column names; my question is how to make R understand that I look for the object a when I write &q...

...describe this by an example; > > > dim(a) > [1] 270 14 > > dim("a") > NULL > > > names(a) > [1] "Var1" "Var2" "Var3" "Var4" "Var5" "Var6" "Var7" > "Var8" "Var9" > [10] "Var10" "Var11" "Var12" "Var13" "Var14" > > names("a") > NULL > > I realise that the character string lacks both a dimension > and any column names; my question is how to make R understand > that I...

...all percents, so they are easy comparable. Is there any way to do this in R? Below is a small sample of the data (from SPSS) and the desired output. Thanks, Danny *Sample Data. DATA LIST LIST /id(F8) var1(F8.2) var2(F8.2) var3(F8.2) var4(F8.2) var5 (F8.2) var6(F8.2) var7(F8.2) var8(F8.2) var9(F8.2) var10(F8.2) var11(F8.2). BEGIN DATA. 10170069 3.51 4.02 6.53 11.05 6.53 8.04 13.57 20.10 11.05 8.55 7.04 10190229 1.89 5.66 4.61 7.62 8.45 13.21 9.50 20.82 16.07 9.36 3.77 10540023 3.40 5.08 3.39 4.52 10.18 14.71 13.56 16.38 9.60 7.89 11.85 10650413 6.64 6.64 3.73 4.70 3.78 13.23 19.82 15....

I am trying to Sweave the output of calculating correlations between one variable and several others. I wanted to print a table where the odd-numbered rows contain the variable names and the even-numbered rows contain the correlations. So if VarA is correlated with all the variables in mydata.df, then it would look like var1 var2 var3 corr1 corr2 corr3 var4 var5

I have a dataframe called "data" with 5 records (in rows) each of which has been scored on each of many variables (in columns). Five of the variables are named var1, var2, var3, var4, var5 using headers. The other variables are named using other conventions. I can create a new variable called var6 with the value 15 for each record with this code: > var6=var1+var2+var3+var4+var5