I have a shiny app and when I run it I get an error saying that an object of type ‘closure’ is not subsettable. What is that and how can I fix it?
Note: I wrote this question as this comes up a lot, and the possible dupes are either not shiny related or so specific that it is not obvious that the answers are broadly applicable.
See also this question which covers this error in a non-Shiny context.
How to fix this:
This is a very common error in shiny apps. This most typically appears when you create an object such as a list, data.frame or vector using the reactive() function – that is, your object reacts to some kind of input. If you do this, when you refer to your object afterwards, you must include parentheses.
For example, let’s say you make a reactive data.frame like so:
MyDF<-reactive({ code that makes a data.frame with a column called “X” })
If you then wish to refer to the data.frame and you call it MyDF or MyDF$X you will get the error. Instead it should be MyDF() or MyDF()$X You need to use this naming convention with any object you create using reactive().
Why this happens:
When you make a reactive object, such as a data.frame, using reactive() it is tempting to think of it as just like any other non-reactive data.frame and write your code accordingly. However, what you have created is not really a data.frame. Rather, what you have made is instructions, in the form of a function, which tell shiny how to make the data.frame when it is needed. When you wish to actually use this function to get the data.frame you have to use the parenthesis, just like you would any other function in R. If you forget to use the parenthesis, R thinks you are trying to use part of a function and gives you the error. Try typing:
plot$x
at the command line and you will get the same error.
You may not see this error right when your app starts. Reactive objects have what is called “lazy” evaluation. They are not evaluated until they are needed for some output. So if your data.frame is only used to make a plot, the data.frame will not exist until the user sees the plot for the first time. If when the app starts up the user is required to click a button or change tabs to see the plot, the code for the data.frame will not be evaluated until that happens. Once that happens, then and only then will shiny use the current values of the inputs to run the function that constructs the data.frame needed to make the plot. If you have forgotten to use the parentheses, this is when shiny will give you the error. Note that if the inputs change, but the user is not looking at the plot, the function that makes the data.frame will not be re-run until the user looks at the plot again.
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I have a shiny app and when I run it I get an error saying that an object of type ‘closure’ is not subsettable. What is that and how can I fix it?
Note: I wrote this question as this comes up a lot, and the possible dupes are either not shiny related or so specific that it is not obvious that the answers are broadly applicable.
See also this question which covers this error in a non-Shiny context.
How to fix this:
This is a very common error in shiny apps. This most typically appears when you create an object such as a list, data.frame or vector using the reactive() function – that is, your object reacts to some kind of input. If you do this, when you refer to your object afterwards, you must include parentheses.
For example, let’s say you make a reactive data.frame like so:
MyDF<-reactive({ code that makes a data.frame with a column called “X” })
If you then wish to refer to the data.frame and you call it MyDF or MyDF$X you will get the error. Instead it should be MyDF() or MyDF()$X You need to use this naming convention with any object you create using reactive().
Why this happens:
When you make a reactive object, such as a data.frame, using reactive() it is tempting to think of it as just like any other non-reactive data.frame and write your code accordingly. However, what you have created is not really a data.frame. Rather, what you have made is instructions, in the form of a function, which tell shiny how to make the data.frame when it is needed. When you wish to actually use this function to get the data.frame you have to use the parenthesis, just like you would any other function in R. If you forget to use the parenthesis, R thinks you are trying to use part of a function and gives you the error. Try typing:
plot$x
at the command line and you will get the same error.
You may not see this error right when your app starts. Reactive objects have what is called “lazy” evaluation. They are not evaluated until they are needed for some output. So if your data.frame is only used to make a plot, the data.frame will not exist until the user sees the plot for the first time. If when the app starts up the user is required to click a button or change tabs to see the plot, the code for the data.frame will not be evaluated until that happens. Once that happens, then and only then will shiny use the current values of the inputs to run the function that constructs the data.frame needed to make the plot. If you have forgotten to use the parentheses, this is when shiny will give you the error. Note that if the inputs change, but the user is not looking at the plot, the function that makes the data.frame will not be re-run until the user looks at the plot again.
This is the code in R and I'm having trouble understanding the role of function(x) and qdata[[x]] in this line of code. Can someone elaborate me this piece by piece? I didn't write this code. Thank you
outs=lapply(names(qdata[,12:35]), function(x)
hist(qdata[[x]],data=qdata,main="Histogram of Quality Trait",
xlab=as.character(x),las=1.5)$out)
This code generate a series of histograms, one for each of columns 12 to 35 of dataframe qdata. The lapply function iterates over the columns. At each iteraction, the name of the current column is passed as argument "x" to the anonymous function defined by "function(x)". The body of the function is a call to the hist() function, which creates the histogram. qdata[[x]] (where x is the name of a column) extracts the data from that column. I am actually confused by "data=qdata".
We don't have the data object named qdata so we cannot really be sure what will happen with this code. It appears that the author of this code is trying to pass the values of components named outs from function calls to hist. If qdata is an ordinary dataframe, then I suspect that this code will fail in that goal, because the hist function does not have an out component. (Look at the output of ?hist. When I run this with a simple dataframe, I do get histogram plots that appear in my interactive plotting device but I get NULL values for the outs components. Furthermore the 12 warnings are caused by the lack of a data parameter to hte hist function.
qdata <- data.frame(a=rnorm(10), b=rnorm(10))
outs=lapply(names(qdata), function(x)
hist(qdata[[x]],data=qdata,main="Histogram of Quality Trait",
xlab=as.character(x),las=1.5)$out)
#There were 12 warnings (use warnings() to see them)
> str(outs)
List of 2
$ : NULL
$ : NULL
So I think we need to be concerned about the level of R knowledge of the author of this code. It's possible I'm wrong about this presumption. The hist function is generic and it is possible that some unreferenced package has a function designed to handle a data object and retrun an outs value when delivered a vector having a particular class. In a typical starting situation with only the base packages loaded however, there are only three hist.* functions:
methods(hist)
#[1] hist.Date* hist.default hist.POSIXt*
#see '?methods' for accessing help and source code
As far as the questions about the role of function and [[x]]: the keyword function returns a language object that can receive parameter values and then do operations and finally return results. In this case the names get passed to the anonymous function and become, each in turn, the local name, x and the that value is used by the '[['-function to look-up the column in what I am presuming is the ‘qdata’-dataframe.
Help files call attributes() a function. Its syntax looks like a function call. Even class(attributes) calls it a function.
But I see I can assign something to attributes(myobject), which seems unusual. For example, I cannot assign anything to log(myobject).
So what is the proper name for "functions" like attributes()? Are there any other examples of it? How do you tell them apart from regular functions? (Other than trying supposedfunction(x)<-0, that is.)
Finally, I guess attributes() implementation overrides the assignment operator, in order to become a destination for assignments. Am I right? Is there any usable guide on how to do it?
Very good observation Indeed. It's an example of replacement function, if you see closely and type apropos('attributes') in your R console, It will return
"attributes"
"attributes<-"
along with other outputs.
So, basically the place where you are able to assign on the left sign of assignment operator, you are not calling attributes, you are actually calling attributes<- , There are many functions in R like that for example: names(), colnames(), length() etc. In your example log doesn't have any replacement counterpart hence it doesn't work the way you anticipated.
Definiton(from advanced R book link given below):
Replacement functions act like they modify their arguments in place,
and have the special name xxx<-. They typically have two arguments (x
and value), although they can have more, and they must return the
modified object
If you want to see the list of these functions you can do :
apropos('<-$') and you can check out similar functions, which has similar kind of properties.
You can read about it here and here
I am hopeful that this solves your problem.
I am still not very good at using R’s standard debugging tools, and I often find that neither the error nor the traceback tell me enough to figure out what is going on. I would like to change R’s default behavior on error to provide more information.
Specifically, I would always like the call, including the formals, the expression assigned to each formal (the default expression if the default is the expression assigned), and the value of each of the argument expressions as evaluated in place, all returned in a format that makes it unambiguous which expression has been matched to which formal and which values go with which expression. Since the values might be large or of unexpected or evanescent type, I’d like them to be returned in a format, such as a str(), that makes intelligent choices about truncation and correctly identifies promises and other object types that tend to evaluate themselves into something else before you see them.
And finally, I’d like all these things, together with the return value of each call, for every function on the call stack from the error back to (and including) some piece of code that I wrote. It seems to me that the natural structure would be a single R object, a list of lists, one list per call (perhaps tidied, broom-like, into a tibble with some list columns) that I could single-step through in the obvious way.
I apologize if I have described some standard R debugging tool that I just haven't learned how to use properly yet. Is this even possible? If it is, could it be implemented via R's available error handlers, or would it need some package-scale coding project?
I would most prefer a solution that changes the default error response to this, but if that is impracticable, I'd accept a solution that requires that I rerun a code chunk with a wrapper or something similar.
lapply(7:12, function(x) ggplot(mydf)+geom_histogram(aes(mydf[,x])))
will give an error Error in [.data.frame(mydf, , x) : undefined columns selected.
I have used several SO questions (e.g. this) as guidance, but can't figure out my error.
The code below works with the mtcars dataset. Just replace mtcars with mydf.
library(ggplot2)
lapply(1:3,function(i) {
ggplot(data.frame(x=mtcars[,i]))+
geom_histogram(aes(x=x))+
ggtitle(names(mtcars)[i])
})
Notice how the reference to i (the column index) was moved from the mapping argument (the call to aes(...)), to the data argument.
Your problem is actually quite subtle. ggplot evaluates the arguments to aes(...) first in the context of your data - e.g. it looks for column names in mydf. If that fails it jumps to the global environment. It does not look in the function's environment. See this post for another example of this behavior and some discussion.
The bottom line is that it is a really bad idea to use external variables in a call to aes(...). However, the data=... argument does not suffer from this. If you must refer to a column number, etc., do it in the call to ggplot(data=...).