R - Pie, X values must be positive - r

I am new to R and drew some testdata about countries in a csv from the web. I am currenty fooling arround with plotting and encountered said error while creating a pie chart of the worlds unemployment.
i issued the following:
>values <- read.csv("D:\\test\\countrydata.csv")
>names(values)
[1] "name" "size" "pop" "unemployed" ...
>typeof(values$unemployed)
"integer"
>pie(values$pop)
Error in pie(values$unemployed) :
'x' values must be positive
>pie(values$pop, na.rm=TRUE)
Error in pie(values$unemployed, na.rm=TRUE) :
'x' values must be positive
The dataset i want to plot is a set of integers, all of them are positive, 0 (thanks kim) or NA.
0 are not a problem when plotting integers, i tried
>pie(as.integer(c(0,1,2,3))
and it worked fine.
What am i missing here?
Thanks and Regards,
BillDoor


I don't have access to your data but in my experience the following might help and is definitely worth a try:
pie(table(values$unemployed))
Would love to learn whether this solved your problem!


According to the R documentation, the first argument must be "non-negative vector" Now when we write
pie(value$pop)
Then R considers it as a numeric data frame which you can check by
str(value$pop).
When you typecast via as.numeric or as.integer, you convert it to a vector, that's why it works on typecasting:
pie(as.numeric(value$pop))


I encountered a similar problem. Here's what worked for me:
vectorVal <- as.numeric(table)
pie(vectorVal)

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Did you also make sure none of them are infinite? As that's the other part of that message?
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Are the classes of your variables character or factor?I was having this problem. My solution was to change al variables to factor.
#my data.frame was "aux.da"
i=0
while(i < ncol(aux.da)){
i=i+1 aux.da[,i] = as.factor(aux.da[,i])
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It's difficult to tell without further input, but what you can do is:
Find the function where the error occurred (via traceback()),
Set a breakpoint and debug it:
trace(tab.disjonctif, browser)
I did the following (offline) to find the name of tab.disjonctif:
Found the package on the CRAN mirror on GitHub
Search for that particular expression that gives the error

I just started to learn R yesterday, but the error comes from the fact that the MCA is for categorical data, so that's why your data cannot be numeric. Then to be more precise, before the MCA a "tableau disjonctif" (sorry i don't know the word in english : Complete disjunctive matrix) is created.
So FactomineR is using this function :
https://github.com/cran/FactoMineR/blob/master/R/tab.disjonctif.R
Where i think it's looking for categorical values that can be matched to a numerical value (like Y = 1, N = 0).
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To build off #marques, #Khaled, and #Pierre Gourseaud:
Yes, changing the format of your variables to factor should address the error message, but you shouldn't change the format of numerical data to factor if it's supposed to be continuous numerical data. Rather, if you have both continuous and categorical variables, try running a Factor Analysis for Mixed Data (FAMD) in the same FactoMineR package.
If you go the FAMD route, you can change the format of just your categorical variable columns to factor with this:
data[,c(3:5,10)] <- lapply(data[,c(3:5,10)] , factor)
(assuming column numbers 3,4,5 and 10 need to be changed).

This will not work for only numeric variables. If you only have numeric use PCA. Otherwise, add a factor variable to your data frame. It seems like for your case you need to change your variables to binary factors.

Same problem as well and changing to factor did not solve my answer either, because I had put every variable as supplementary.
What I did first was transform all my numeric data to factor :
Xfac = factor(X[,1], ordered = TRUE)
for (i in 2:29){
tfac = factor(X[,i], ordered = TRUE)
Xfac = data.frame(Xfac, tfac)
}
colnames(Xfac)=labels(X[1,])
Still, it would not work. But my 2nd problem was that I included EVERY factor as supplementary variable !
So these :
MCA(Xfac, quanti.sup = c(1:29), graph=TRUE)
MCA(Xfac, quali.sup = c(1:29), graph=TRUE)
Would generate the same error, but this one works :
MCA(Xfac, graph=TRUE)
Not transforming the data to factors also generated the problem.
I posted the same answer to a related topic : https://stackoverflow.com/a/40737335/7193352

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I am wondering why this error occurs and how to fix it. There is no missing data in my table and all of the variables are categorical.
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I have had this error before because the function requires the variables to be factors (and the data I was passing it wasn't fully converted into factors). Unlike a lot of other R functions, this one does not convert the data for you even if all columns are categorical.
I'm not quite sure what your data is, but it is likely that one or more columns is not as a factor variable. If your columns 1 to 8 are already factors then it may be in the read.csv call; string variables will automatically be converted into a factors when you read them in from the csv, but numeric ones will not.

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As Arun hints at it could be that the column is character rather than numeric.
If you are sure that all the values are correct you could coerce the values with
d_Temp_Experiment$value <- as.numeric(d_Temp_Experiment$value)
You might have the below sort of business going on.
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str(x)
Then if 'xa' is how you are referring to x[['a']] you would do this:
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