I was wandering if it is possible to use the following data.table feature without providing column names:
dt <- data.table(mtcars)[,.(mpg, cyl)]
dt[,`:=`(avg=mean(mpg), med=median(mpg))]
Let's say for example that I have a function that return more than one column like this
mfun=function(x){cbind(x^2,x^3)}
But if I want to assign it as new columns that specific way, R would execute function mfun twice, which is not efficient.
dt[,`:=`(sqr=mfunc(mpg)[,1], cub=mfunc(mpg)[,2])]
So, without 'work arounds', is it possible to do something similar to this:
dt[,`:=`(mfunc(mpg))] #this returns an error
dt[,`:=`(error2=mfunc(mpg))] #this returns an error
Related
In my data frame I am trying to sort the data in descending order. I am using the below line of code for sorting my data and it works as intended.
CNS25VOL <- CNS25VOL[order(-CNS25VOL$MATVOL22), ]
However if I refer to the same column by it's index number, the code throws an error
CNS25VOL <- CNS25VOL[order(-CNS25VOL[, 2]), ]
Error thrown is
Error in CNS25VOL[, 2] : incorrect number of dimensions
While I do have a solution to what I am intending to do, but issue I see is if all of a sudden name of my column changes the code won't work. I know that their position will stay same in the data frame.
How can we handle it.
order(-CNS25VOL[, 2]) order here does expect a vector which you try to construct via the [] in CNS25VOL[, 2]. Normal dataframes will return a vector consisting only of the 2nd column. A tibble however will return a tibble with only one column.
You can reproduce the behaviour of normal data.frames with the drop = FALSE argument to [] as in
CNS25VOL[, 2, drop = TRUE]
Try to always be aware whether you are using a standard data.frame or a tibble or a data.table because they look very similar and are not in the details. Also see https://tibble.tidyverse.org/reference/subsetting.html
dplyr functions tend to give you a tibble back even if you fed them a classical data.frame.
I am currently trying to create a table from a list of variable names (something I feel should be relatively simple) and I can't for the life of me, figure out how to do it correctly.
I have a data table that I've named 'file' and there are a list of 3 variable names within this file. What I want to do is create a table of each variable and then rbind them together. For further context, these few lines of code will be worked into a much larger function. The list of variable names must be able to accommodate the number of variables the user defines.
I have tried the following:
file<-as.data.table(dt)
variable_list<-list("outcome", "type")
for (variable in variable_list){
var_table<-as.data.table(table(file$variable_list))
na_table<-as.data.table(table(is.na(file$variable)))
}
When I run the above code, R returns empty tables of var_table and na_table. What am I doing wrong?
An option is to loop over the 'variable_list, extract the column, apply tableandrbindwithindo.call`
do.call(rbind, lapply(variable_list, function(nm) table(file[[nm]])))
NOTE: assuming that the levels of the columns are the same
If the levels are not the same, make it same by converting the columns to factor with levels specified
lvls <- na.omit(sort(unique(unlist(file[, unlist(variable_list), with = FALSE]))))
do.call(rbind, lapply(variable_list, function(nm)
table(factor(file[[nm]], levels = lvls))))
Or if we have a data.table, use the data.table methods
rbindlist(lapply(variable_list, function(nm) file[, .N,by = c(nm)]), fill = TRUE)
The problem (at least one of the problems) might be that you are attempting to use the $ operator incorrectly. You cannot substitute text values into the second argument. You can use its syntactic equivalent [[ instead of $, however. So this would be a possible improvement. (I've not tested it since you provided no test material.)
file<-as.data.table(dt)
variable_list<-list("outcome", "type")
for (variable in variable_list){
var_table<-as.data.table(table(file[[variable]])) # clearly not variable_list
na_table<-as.data.table(table(is.na(file[[variable]] )))
}
I'm guessing you might have done something like, ...
var_table <- file[, table(variable ) ]
... since data.table syntax evaluates text values in the environment of the file (which in this case is confusing named "file". It's better not to use such names, since in this case there's also an R function by that name.
I have a dataframe called "commit.277", with 600 list of investor_ids and deal_ids. I want to construct dyad_id based on investor_ids and deal_ids. Here is the function below (provided by someone from Stackoverflow):
function(investor_id,deal_id){
paste0("1",
# this rule adds 0 if the ids are shorter/longer
# but should be changed to match what you need
paste0(rep("0",(7 - nchar(investor_id)-nchar(deal_id))),collapse = ""),
investor_id,
"0",
deal_id
)
}
However, with this function, I can only get the result one by one, I have 600 ids to create in a dataframe. So is there a way (something like a for loop?) I can use this function to generate the result in the dataframe very quickly?
To use your function as it is you can use mapply. If your function is called fn_name you could do :
result <- mapply(fn_name, commit.277$investor_ids, commit.277$deal_ids)
However, I think your function can be vectorised which will avoid using mapply if you share information about your data and expected output.
I'm having issues with a specific problem I have a dataset of a ton of matrices that all have V1 as their column names, essentially NULL. I'm trying to write a loop to replace all of these with column names from a list but I'm running into some issues.
To break this down to the most simple form, this code isn't functioning as I'd expect it to.
nameofmatrix <- paste('column_', i, sep = "")
colnames(eval(as.name(nameofmatrix))) <- c("test")
I would expect this to take the value of column_1 for example, and replace (in the 2nd line) with "test" as the column name.
I tried to break this down smaller, for example, if I run print(eval(as.name(nameofmatrix)) I get the object's column/rows printed as expected and if I run print(colnames(eval(as.name(nameofmatrix))) I'm getting NULL as expected for the column header (since it was set as V1).
I've even tried to manually type in the column name, such as colnames(column_1) <- c("test) and this successfully works to rename the column. But once this variable is put in the text's place as shown above, it does not work the same. I'm having difficulties finding a solution on how to rename several matrix columns after they have been created with this method. Does anyone have any advice or suggestions?
Note, the error I'm receiving on trying to run this is
Error in eval([as.name](nameofmatrix)) <- \`vtmp\` : could not find function "eval<-"
We could return the values of the objects in a list with get (if there are multiple objects use mget, then rename the objects in the list and update those objects in the global env with list2env
list2env(lapply(mget(nameofmatrix), function(x) {colnames(x) <- newnames
x}), .GlobalEnv)
It can also be done with assign
data(mtcars)
nameofobject <- 'mtcars'
assign(nameofobject, `colnames<-`(get(nameofobject),
c('mpg1', names(mtcars)[-1])))
Now, check the names of 'mtcars'
names(mtcars)[1]
#[1] "mpg1"
I have a list of data frames. I want to use lapply on a specific column for each of those data frames, but I keep throwing errors when I tried methods from similar answers:
The setup is something like this:
a <- list(*a series of data frames that each have a column named DIM*)
dim_loc <- lapply(1:length(a), function(x){paste0("a[[", x, "]]$DIM")}
Eventually, I'll want to write something like results <- lapply(dim_loc, *some function on the DIMs*)
However, when I try get(dim_loc[[1]]), say, I get an error: Error in get(dim_loc[[1]]) : object 'a[[1]]$DIM' not found
But I can return values from function(a[[1]]$DIM) all day long. It's there.
I've tried working around this by using as.name() in the dim_loc assignment, but that doesn't seem to do the trick either.
I'm curious 1. what's up with get(), and 2. if there's a better solution. I'm constraining myself to the apply family of functions because I want to try to get out of the for-loop habit, and this name-as-list method seems to be preferred based on something like R- how to dynamically name data frames?, but I'd be interested in other, more elegant solutions, too.
I'd say that if you want to modify an object in place you are better off using a for loop since lapply would require the <<- assignment symbol (<- doesn't work on lapply`). Like so:
set.seed(1)
aList <- list(cars = mtcars, iris = iris)
for(i in seq_along(aList)){
aList[[i]][["newcol"]] <- runif(nrow(aList[[i]]))
}
As opposed to...
invisible(
lapply(seq_along(aList), function(x){
aList[[x]][["newcol"]] <<- runif(nrow(aList[[x]]))
})
)
You have to use invisible() otherwise lapply would print the output on the console. The <<- assigns the vector runif(...) to the new created column.
If you want to produce another set of data.frames using lapply then you do:
lapply(seq_along(aList), function(x){
aList[[x]][["newcol"]] <- runif(nrow(aList[[x]]))
return(aList[[x]])
})
Also, may I suggest the use of seq_along(list) in lapply and for loops as opposed to 1:length(list) since it avoids unexpected behavior such as:
# no length list
seq_along(list()) # prints integer(0)
1:length(list()) # prints 1 0.