rankhospital <- function(state = factor(), outcome = factor(), num = factor()) { #read data caremeasures <- read.csv("D:/data science specialization/course stuff/rprogw3/outcome-of-care-measures.csv", na.strings = "NA", stringsAsFactors = FALSE) #separate required columns requiredOutcomes <- caremeasures[11, 17, 23] #assign columns names names(requiredOutcomes[3]) <- "heart attack" names(requiredOutcomes[4]) <- "heart failure" names(requiredOutcomes[5]) <- "pneumonia" arrangedData <- order(requiredOutcomes[caremeasures$State == state, c(caremeasures$Hospital.Name, outcome)]) if (num == "best"){ result <- arrangedData[1, 1] return(result) } else if (num == "worst"){ result <- arrangedData[nrow(arrangedData[,1]),1] return(result) } else result <- arrangedData[num, 1] return(result) }
This code is supposed to return the name of a single hospital that corresponds to the inputs given to the function, yet I'm getting an error stating:
Error in requiredOutcomes[caremeasures$State == state, c(caremeasures$Hospital.Name, :
incorrect number of dimensions
I don't have your data, so I'll project what I think is leading up to the problem.
The reference to caremeasures[11, 17, 23]
is likely not doing what you need, and it is therefore returning something you aren't expecting. Try it with caremeasures[,c(11, 17, 23)]
.
I'll try to show what's going on using mtcars
:
requiredOutcomes <- mtcars[1,2,3]
requiredOutcomes
# [1] 6
requiredOutcomes[1,2]
# Error in requiredOutcomes[1, 2] : incorrect number of dimensions
Because mtcars
is a data.frame
, your [
indexing uses [.data.frame
under the hood. This translates something like
# equivalent
mtcars[1, 2]
`[.data.frame`(mtcars, 1, 2)
The "arguments" (yes, it's just a regular function) are:
str(formals(`[.data.frame`))
# Dotted pair list of 4
# $ x : symbol
# $ i : symbol
# $ j : symbol
# $ drop: language if (missing(i)) TRUE else length(cols) == 1
which means that your 11, 17, 23
arguments are effectively
`[.data.frame`(requireOutcomes, 11, 17, 23)
which is applied to the arguments as
`[.data.frame`(x = requireOutcomes, i = 11, j = 17, drop = 23)
Okay, so x=
makes sense (the data). i=
gives your row selection (11), and j=
gives the column selection. However, when R expected a logical
, then anything that is not zero is considered TRUE
, so this is effectively
`[.data.frame`(x = requireOutcomes, i = 11, j = 17, drop = TRUE)
which completely loses your intent (I suspect) by returning a scalar (single value, a vector of length 1 in R). Side note: had you used 0
or FALSE
, then you would have returned a data.frame
with 1 row and 1 column.
Here's a method for debugging what's going on so that you are able to find this for yourself next time.
myfunc <- function(x) {
res <- x[1,2,3]
return(res[1:3,])
}
myfunc(mtcars)
# Error in res[1:3, ] (from #3) : incorrect number of dimensions
Okay, we see the same error. We'll use debug(myfunc)
(whatever your function name is), though you can achieve similar results by placing browser()
at a specific place within your function.
debug(myfunc)
myfunc(mtcars)
# debugging in: myfunc(mtcars)
# debug at #1: {
# res <- x[1, 2, 3]
# return(res[1:3, ])
# }
# Browse[2]>
We're now in R's debugger, giving us step execution tracing. Typing n
executes the n
ext line; you can read more of the commands with ?browser
.
n
# debug at #2: res <- x[1, 2, 3]
# Browse[2]>
n
# debug at #3: return(res[1:3, ])
# Browse[2]>
res
# [1] 6
("debug at" shows the next line to be executed, so we have not yet run return(...)
.) With this, we can see that res
-- which we think should be a data.frame
-- is just a single number. Huh. Now look back at the code and figure out what happened. To me (and in this simple example), it's clearly x[1,2,3]
that's a problem.
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