Let me start by saying I'm sure this has been answered before but I am unsure of what terms to search.
I have a few data frames that are named like df_A , df_B , and df_C and wish to send them all to ggplot. I tried to loop through them all but have been unsuccessful. Here is what I have now:
for (Param in c("A","B","C"){
chosen_df <- paste0("df_",Param)
ggplot(data=chosen_df...)
}
I receive back an error saying "data must be a data frame". This error makes sense to me since chosen_df is character vector rather than the actual data frame.
I have tried using noquote but to no avail.
My questions are:
1) What kind of search terms can I look up to solve this problem
2) How close am I to solving this problem?
We can use get to return the value of the object names as a string
for (Param in c("A","B","C"){
chosen_df <- get(paste0("df_",Param))
ggplot(data=chosen_df, ...)
}
Or with mget, return the values in a list
lst1 <- mget(ls(pattern = '^df_[A-Z]$'))
Related
This is probably a very simple problem but I have been struggling to search for this issue. Basically, I am using lapply to convert the column names to upper in a list of dataframes. My first attempt did not work, however adding ;x works. What exactly is going on?
This does not work:
df.list <- lapply(df.list,function(x) colnames(x) <- toupper(colnames(x)))
This does:
df.list <- lapply(df.list,function(x) {colnames(x) <- toupper(colnames(x));x})
Since you are modifying the object x (or in this case only the colnames of x) inside the function definition, you have to return the modified object x. This is happening by using ;x which can be read as a new line only returning the object x
I have a list of data frames. I want to use lapply on a specific column for each of those data frames, but I keep throwing errors when I tried methods from similar answers:
The setup is something like this:
a <- list(*a series of data frames that each have a column named DIM*)
dim_loc <- lapply(1:length(a), function(x){paste0("a[[", x, "]]$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.
I have obtained a data set with slightly inconsistent and messy variable names. I would like to rename them in a an efficient and automated way.
I have a set of data frames and I need to rename some columns in several of them. The order of the columns, and length of the data frames differ, so I would like to use any function such as grep() or a subset term (df$x[== "term"]).
I have found an older question regarding this problem (Rename columns in multiple dataframes, R), but I haven't been able to get any of the suggested solutions to work since I get an error message. I do not have reputation enough to comment and ask further questions on those replies. However, my problem seems to be a bit different as I get an error message from my for loop that is not mentioned in the earlier question:
Error in `colnames<-`(`*tmp*`, value = character(0)) :
attempt to set 'colnames' on an object with less than two dimensions
Setup: multiple data frames, let's call them myDF1, myDF2 ...
In those data frames there are columns with names (bad_name1, bad_name2) that should be changed to something else (good_name1, good_name2).
Replicable dataset:
myDF1 <- data.frame(bad_name1="A", bad_name2="B")
myDF2 <- data.frame(bad_name1="C", bad_name2="D")
for (x in c(myDF1,myDF2)) {
colnames(x) <- gsub(x = colnames(x), pattern = "bad_name0", replacement = "good_name1")
}
There are several ways of doing this. One that appealed to me is the subset method:
colnames(myDF1)[names(myDF1) == "bad_name1"] <- "good_name1")
This works fine as a single line, but not as a for loop.
for (x in c(myDF1,myDF2)) {
colnames(x)[colnames(x) == "bad_name1"] <- "good_name1"
}
Which renders the error message.
Error in `colnames<-`(`*tmp*`, value = character(0)) :
attempt to set 'colnames' on an object with less than two dimensions
The same error message applies with a 'gsub'-based method:
for (x in c(myDF1,myDF2)) {
colnames(x) <- gsub(x = colnames(x), pattern = "bad_name1", replacement = "good_name1")
}
I realise that I miss out on something fundamental here. I suppose that the for loop is not receiving the results of the 'colnames(x)' in an appropriate format. But I cannot understand how I'm supposed to make it work. The methods suggested in Rename columns in multiple dataframes, R does not really cover this error message.
Additional clarification, as asked for by vaettchen in a comment:
There is 3 column names that have to be changed (in all data frames). The reason is that they have names like varX.1, varX.2, varX.3 while I would prefer varXcount, varXmean, varXmax. So I have realised that there are names that I am not happy with, and decided on new ones based on my own taste.
You just need a few minor changes. Look at c(myDF1, myDF2) to see why that is not working - it splits the data frames into a list of 4 factors. Combine the data frames into a list and process the list:
all <- list(myDF1=myDF1, myDF2=myDF2)
for (x in seq_along(all)) {
colnames(all[[x]]) <- gsub(x = colnames(all[[x]]), pattern = "bad_name1",
replacement = "good_name1")
}
list2env(all, envir=.GlobalEnv)
I am collecting lists from google trends with a loop. I know want to use a second loop to rbind the $trend data.frame from each list (I have 62 lists).
Instead of doing it with one rbind over all 62 lists (like rbind(list1$trend, list2trend, ..., list62$trend) I want to do it in a more elegant loop.
I tried it with the code below, but it is not working. I get the following error message:
Error in as.POSIXlt.character(x, tz, ...) :
character string is not in a standard unambiguous format
Here is the code I am using. Any help is really appreciated! Thanks a lot!
trend = list1$trend
i=2
for (i in 4) {
list <- paste("list", i, sep = "")
list <- (paste(list, "$trend", sep=""))
rbind(trend, list)
}
Use the rbindlist() from the data.table package. Rbind in a loop is horribly inefficient as the size of the data frame gets redefined with each binding event. If you don't want to stay with the data.table format you can just wrap it in data.frame(). Happy to provide some code if the question gets updated with a reproducible example.
Sometimes I have code which references a specific dataset based on some variable ID. I have then been creating lines of code using paste0, and then eval(parse(...)) that line to execute the code. This seems to be getting sloppy as the length of the code increases. Are there any cleaner ways to have dynamic data reference?
Example:
dataset <- "dataRef"
execute <- paste0("data.frame(", dataset, "$column1, ", dataset, "$column2)")
eval(parse(execute))
But now imagine a scenario where dataRef would be called for 1000 lines of code, and sometimes needs to be changed to dataRef2 or dataRefX.
Combining the comments of Jack Maney and G.Grothendieck:
It is better to store your data frames that you want to access by a variable in a list. The list can be created from a vector of names using get:
mynames <- c('dataRef','dataRef2','dataRefX')
# or mynames <- paste0( 'dataRef', 1:10 )
mydfs <- lapply( mynames, get )
Then your example becomes:
dataset <- 'dataRef'
mydfs[[dataset]][,c('column1','column2')]
Or you can process them all at once using lapply, sapply, or a loop:
mydfs2 <- lapply( mydfs, function(x) x[,c('column1','column2')] )
#G.Grothendieck has shown you how to use get and [ to elevate a character value and return the value of a named object and then reference named elements within that object. I don't know what your code was intended to accomplish since the result of executing htat code would be to deliver values to the console, but they would not have been assigned to a name and would have been garbage collected. If you wanted to use three character values: objname, colname1 and colname2 and those columns equal to an object named after a fourth character value.
newname <- "newdf"
assign( newname, get(dataset)[ c(colname1, colname2) ]
The lesson to learn is assign and get are capable of taking character character values and and accessing or creating named objects which can be either data objects or functions. Carl_Witthoft mentions do.call which can construct function calls from character values.
do.call("data.frame", setNames(list( dfrm$x, dfrm$y), c('x2','y2') )
do.call("mean", dfrm[1])
# second argument must be a list of arguments to `mean`