I have the following data.table (data.frame) called output:
> head(output)
Id Title IsProhibited
1 10000
Do this, irrespective of how many columns you have:
df <- apply(df,2,as.character)
Then do write.csv
.
As mentioned in the comments, you should be able to do something like this (untested) to get "flatten" your list
into a character vector:
output$Title <- vapply(output$Title, paste, collapse = ", ", character(1L))
As also mentioned, if you wanted to try the unlist
approach, you could "expand" each row by the individual values in output$Title
, something like this:
x <- vapply(output$Title, length, 1L) ## How many items per list element
output <- output[rep(rownames(output), x), ] ## Expand the data frame
output$Title <- unlist(output$Title, use.names = FALSE) ## Replace with raw values
There is a new function (introduced in november 2016) in data.table package that handles writing a data.table object to csv quite well, even in those cases when a column of the data.table is a list.
fwrite(data.table, file ="myDT.csv")
Another easy solution. Maybe one or more columns are of type list
, so we need convert them to "character" or data frame. So there are two easy solutions
Convert each column "as.character" using--
df$col1 = as.character(df$col1)
df$col2 = as.character(df$col2)
.......and so on
The best one convert df
in to a "matrix"
df = as.matrix(df)
now write df
into csv. Works for me.
Assuming
the path you want to save to is Path
, i.e. path=Path
df
is the dataframe you want to save,
follow those steps:
Save df
as txt document:
write.table(df,"Path/df.txt",sep="|")
Read the text file into R:
Data = read.table("Path/df.txt",sep="|")
Now save as csv:
write.csv(Data, "Path/df.csv")
That's it.
Those are all elegant solutions.
For the curious reader who would prefer some R-code to ready made packages , here's an R-function that returns a non-list dataframe that can be exported and saved as .csv.
output is the "troublesome" data frame in question.
df_unlist<-function(df){
df<-as.data.frame(df)
nr<-nrow(df)
c.names<-colnames(df)
lscols<-as.vector(which(apply(df,2,is.list)==TRUE))
if(length(lscols)!=0){
for(i in lscols){
temp<-as.vector(unlist(df[,i]))
if(length(temp)!=nr){
adj<-nr-length(temp)
temp<-c(rep(0,adj),temp)
}
df[,i]<-temp
} #end for
df<-as.data.frame(df)
colnames(df)<-c.names
}
return(df)
}
Apply the function on dataframe "output" :
newDF<-df_unlist(output)
You can next confirm that the new (newDF) data frame is not 'listed' via apply(). This should successfully return FALSE.
apply(newDF,2,is.list) #2 for column-wise step.
Proceed to save the new dataframe, newDF as a .csv file to a path of your choice.
write.csv(newDF,"E:/Data/newDF.csv")