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Error in <my code> : object of type 'closure' is not subsettable
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Closed 8 years ago.
I am trying to use read.csv() command, but I do not understand colClasses part to run coding. Does anyone explain what it is, and also give me example of simple coding for read.csv()?
Also, if I run my coding for read.csv(), I get an error
> object of type 'closure' is not subsettable
What type of error is this? Last time I run my code, it worked, but now I get this. I am not sure what change I should make here. This is my code:
Precipfiles[1:24] <- list.files(pattern=".csv")
> DF <- NULL
> for (f in Precipfiles[1:24]) {
data[1:24]<-read.csv(f,header=T,sep="\t",na.string="",colClasses="character")
DF[1:24]<-rbind(DF,data[1:24])
}
Basically, I load all data and put them together, but I have not able to use merge() command since I am having troubles I listed above.
I think I should not use colClasses="character" because data I am using are all numeric in 200 by 200 matrix. There are 24 data files that I have to put them together.
If you have any suggestions and advise to improve this coding please let me know.
Thank you for all of your help.
You really don't need the [1:24] in every assignment, this is what is causing your problems. You are assign to a subset of a indexed vector of some description.
The error message when are trying to assign to data[1:24], without data being assigned previously (in your previous usage (which you mentioned worked), data was probably a list or data.frame you had created.). As such data is a function (for loading data associated with packages, see ?data) and the error you saw is saying that (a function includes a closure)
I would suggest something like
Precipfiles <- list.files(pattern=".csv")
DFlist <- lapply(Precipfiles, read.table, sep = '\t',
na.string = '', header = TRUE)
bigDF <- do.call(rbind, DFlist)
# or, much faster using data.table
library(data.table)
bigDF <- rbindlist(DFlist)
Related
tree_mvBM <- read.nexus("C:/Users/Zach/Desktop/tree_mvBM.tre")
View(tree_mvBM)
dat <- data$Tp; names(dat) <- rownames(data)
Error in data$Tp : object of type 'closure' is not subsettable
You're trying to refer to an object called data in your global workspace, presumably a data frame. The object doesn't exist (you forgot to read it in,or you called it something else, or ... ?), so R is instead finding the built-in function data. It is trying to "subset" it (i.e. $Tp tells R to extract the element named "Tp"), which is not possible because you can't extract an element of a function. (Functions are called "closures" in R for technical reasons.)
This is one reason (probably the main reason) that you shouldn't give your variables names that match the names of built-in R objects (like I, t, c, data, df, ...). If you had called your data my_data instead the error message would be
Error: object 'my_data' not found
which might be easier to understand.
This is such a common error that there are jokes about it (image search the error message):
I would like to know if someone got a similar error using the ord function?
My code hasn't worked since using the new version of R (4.0.2) and I wonder if it's associated with made4 updates?
I would really appreciate it if someone would give some hint
This is the problematic piece of code
res_coa <- ord(tdata, classvec=Species, type="coa")
where tdata is a matrix and Species a factor
I had the same problem and I fixed it just converting my data into a data.frame. You can try something like:
res_coa <- ord(data.frame(tdata), classvec=Species, type="coa")
I am new to programming and trying to learn R using swirl.
In one of the exercises I was told to use the summary function on a dataset. However I encountered a discrepancy in the way the summary was printed:
Instead of summarizing the categorical variable values, it instead says something about length, class and mode.
I went around searching for why this might be happening to no avail, but I did manage to find what the output is supposed to look like:
Any help would be greatly appreciated!
This behaviour is due to the option stringsAsFactors, which is FALSE by default on R 4. Previously it was TRUE by default:
From R 4 news: "now uses a `stringsAsFactors = FALSE' default, and hence by default no longer converts strings to factors in calls to data.frame() and read.table()."
A way to return to the previous behaviour with the same code is to run options(stringsAsFactors=T) before building dataframes. However, there is a warning saying this option will eventually be removed, as explained here.
For your new code, you can use the stringsAsFactors parameter, for instance data.frame(..., stringsAsFactors=T).
If you already have dataframes and you want to convert them, you could use this function to convert all character variables (you will have to adapt if only some variables need conversion):
to.factors <- function(df) {
i <- sapply(df, is.character)
df[i] <- lapply(df[i], as.factor)
df
}
We have always been an SPSS shop but we're trying to learn R. Been doing some basics. I am trying to do a simple t-test, just to learn that code.
Here's my code, and what's happening:
Code screenshot
I don't get why it says "score" isn't found. It's in the table, and the read.csv code defaults to assuming the first row contains headers. I can't see why it's not "finding" the column for score. I'm sure it's something simple, but would appreciate any help.
You didn't store your imported csv file in a variable. It printed to the console because it had nowhere else to go - it just gets printed and then thrown away. You need to assign it for it to be saved in memory:
my_data_frame <- read.csv("ttest.csv")
Now your data exists in the variable my_data_frame and you can use it by supplying it as the data argument:
t.test(score ~ class, mu=0, alt="two.sided", conf=0.95, var.eg=F, paired=F, data=my_data_frame)
Also, in general, I would recommend using read_csv from the package readr over the default read.csv - it's faster.
Finally, when you ask questions, please provide your code as text, not a picture. You should also provide your data or a toy dataset - you can use the function dput to print code that will create your data, or just provide the csv file or some code that creates toy data.
I am trying to prepare data for cluster analysis. That's why I have prepared data tables in excel and the headers are "id","name","crime_type","crime_date","gender","age"
Then , I convert the excel into .csv format.
Then , I write the following command ->
>crime <- read.csv("crime_data.csv",header=T)
>crime # I print , and it prints
# now I will do cluster with kmeans()
>kmeans.result <- kmeans(crime,3)
But , it shows errors.
"Error is as follows :
Error in do_one(nmeth) : NA/NaN/Inf in foreign function call (arg 1)
In addition: Warning message:
In kmeans(crime, 3) : NAs introduced by coercion"
What I am doing wrong here...
I can't speak to your specific problem without knowing what you data looks like but it could be as simple as giving the xlsx package a try. I think it handles NaNs better
install.packages(xlsx)
library(xlsx)
yourdata <- read.xlsx("YOURDATASHEET.xlsx", sheetName="THESHEETNAME")
Seems like you are asking two questions. For the first; you can also try reading directly from the clipboard (beware of large tables tough, but so far I have good results with 40k rows, 30 col)
d1<-read.table(file="clipboard",sep="\t",header=FALSE,stringsAsFactors=FALSE)
set header to TRUE if you want to name your columns. You can also use what was suggested above to open excel sheets directly but this might not be practical if you have non standard tables.
For the second part perhaps you should convert to numerical using the sapply function and or suppressWarnings().