reshape2

This question already has an answer here: Faster ways to calculate frequencies and cast from long to wide 4 answers I have a dataset and I want to reshape it with package reshape2 from R, but I'm getting this error: Aggregation function missing: defaulting to length This is the head() of my data: cat_one customer valor cama A 1 cama B 1 cama C 1 mesa D 1 mesa A 1 mesa A 1 And I want to reshape it like this, with a count between both variables: customer cama mesa A 1 0 B 2 ... C D ... ... This is my code: dcast(dados_teste, cat_one ~ customer, value.var = 'valor') And I'm following this other

In the "An Introduction to reshape2" package Sean C. Anderson presents the following example. He uses the airquality data and renames the column names names(airquality) <- tolower(names(airquality)) The data look like # ozone solar.r wind temp month day # 1 41 190 7.4 67 5 1 # 2 36 118 8.0 72 5 2 # 3 12 149 12.6 74 5 3 # 4 18 313 11.5 62 5 4 # 5 NA NA 14.3 56 5 5 # 6 28 NA 14.9 66 5 6 Then he melts them by aql <- melt(airquality, id.vars = c("month", "day")) to get # month day variable value # 1 5 1 ozone 41 # 2 5 2 ozone 36 # 3 5 3 ozone 12 # 4 5 4 ozone 18 # 5 5 5 ozone NA # 6 5 6 ozone 28

RStudio was crashing when I tried to reshape a particular data frame using dcast (from the reshape2 package). I discovered that the crash was actually happening in R itself, so I ran my casting code in R.app and got the type of error that gives this site its name: Error: segfault from C stack overflow . With the help of Google and SO, I learned that this is a memory access error. Okay, I got that far, but I don't know where to go from here. I can't provide a true reproducible example, because my data frame is about 558,000 rows and the problem doesn't occur on small toy examples. For example,

Hoping someone can help me with labelling columns of a grouped barchart with percentages. I couldn't find an existing post that I could make work successfuly. Below is the code for a basic example dataframe. Service<-c("AS","AS","PS","PS","RS","RS","ES","ES") Year<-c("2015","2016","2015","2016","2015","2016","2015","2016") Q1<-c("Dissatisfied","Satisfied","Satisfied","Satisfied","Dissatisfied","Dissatisfied","Satisfied","Satisfied") Q2<-c("Dissatisfied","Dissatisfied","Satisfied","Dissatisfied","Dissatisfied","Satisfied","Satisfied","Satisfied") Example<-data.frame(Service,Year,Q1,Q2) Next, I

Why can't one have multiple variables passed to value.var in dcast ? From ?dcast : value.var name of column which stores values, see guess_value for default strategies to figure this out. It doesn't explicitly indicate that only one single variable can be passed on as value. If however I try that, then I get an error: > library("reshape2") > library("MASS") > > dcast(Cars93, AirBags ~ DriveTrain, mean, value.var=c("Price", "Weight")) Error in .subset2(x, i, exact = exact) : subscript out of bounds In addition: Warning message: In if (!(value.var %in% names(data))) { : the condition has length

Consider the following code: set.seed(1) M = matrix(rnorm(9), ncol = 3) dimnames(M) = list(LETTERS[1:3], LETTERS[1:3]) print(M) A B C A -0.6264538 1.5952808 0.4874291 B 0.1836433 0.3295078 0.7383247 C -0.8356286 -0.8204684 0.5757814 melt(M) Var1 Var2 value 1 A A -0.6264538 2 B A 0.1836433 3 C A -0.8356286 4 A B 1.5952808 5 B B 0.3295078 6 C B -0.8204684 7 A C 0.4874291 8 B C 0.7383247 9 C C 0.5757814 If i call melt using a data.frame , i get a different result: DF = data.frame(M) melt(DF) variable value 1 A -0.6264538 2 A 0.1836433 3 A -0.8356286 4 B 1.5952808 5 B 0.3295078 6 B -0.8204684 7 C

This question already has an answer here: dcast error: ‘Aggregation function missing: defaulting to length’ 1 answer I have seen this reshape2 several times on SO but haven't seen a solution to my particular problem; I have a dataset like this; head(data) student test score Adam Exam1 80 Adam Exam2 90 John Exam1 70 John Exam2 60 I am trying to cast this to a wide format that looks like this; Student Exam1 Exam2 ........ ExamX Adam 80 90 John 70 60 using; dcast(data,student~test,value.var='score') but the data ends up looking like something like this; Student Exam1 Exam2 Adam 0 0 John 0 1 with