How to save a dataframe with list to csv file in R

Question

I don't know if is possible...

I would save the file to import it in others future sessions.

I wanna save this data.frame in a csv file (it's a list of list containing vectors):

> operacions<-list(list(Nom="Victor",Bolis= c("Negro","azul","verde")),list(Nom="Dani",Lapices=c(1:4)))
> operacions
[[1]]
[[1]]$Nom
[1] "Victor"

[[1]]$Bolis
[1] "Negro" "azul"  "verde"


[[2]]
[[2]]$Nom
[1] "Dani"

[[2]]$Lapices
[1] 1 2 3 4

But it give me an error:

> write.csv2(operacions, "file.csv",row.names = FALSE)
Error in data.frame(list(Nom = "Victor", Bolis = c("Negro", "azul", "verde" : 
  arguments imply differing number of rows: 3, 4

This is not a data frame, this is a list of lists. The problem here is that the elements have differing lengths.. rapply(operacions, length) returns 1 3 1 4. This is a problem, because .csv requires fixed lengths. What would the expected format of the output be here? — slamballais
– slamballais, Commented Apr 25, 2016 at 23:34
This may answer your question: stackoverflow.com/a/27594769/5805670 — slamballais
– slamballais, Commented Apr 25, 2016 at 23:40

IRTFM · Accepted Answer · 2016-04-25 23:57:55Z

2

Since it's not a data.frame , and more specifically cannot be coerced to one with as.data.frame which is where that message came from, you need to think of a different method of saving the data. Probably this simplest would be with dput, which writes an ASCII representation of the list structure:

dput(operacions, file="out.txt")

To bring it back into R:

new <- source("out.txt")

Another method would be to convert to JSON format, which would also preserve the key-value information rather than just writing the values:

library(jsonlite)
 toJSON(new)
# value---------
{"value":[{"Nom":["Victor"],"Bolis":["Negro","azul","verde"]},{"Nom":["Dani"],"Lapices":[1,2,3,4]}],"visible":[true]}

You can use the cat function to direct this to a text file:

cat( toJSON(new), file="test.3.txt")

answered Apr 25, 2016 at 23:57

IRTFM

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Technophobe01 · Accepted Answer · 2016-04-26 00:19:54Z

R Data frames and R lists are potentially incompatible...

A list is, essentially a vector where each element can be of a different type and length of elements. Meanwhile, a Data frame can be thought of a uniform spreadsheet where each column can store a different type of data, or nonnested lists where each element is of the same length. This last point is important as lists can have unequal lengths, whilst a Data frames do not.

Thus, it may be easier to save the list as an RDS file using saveRDS()

dataDir <- "."
saveRDS( operacions, file.path(dataDir, "files"))
operacions2 <- readRDS(file.path(dataDir, "files"))

this will save it as an R-Object, and similarly, restore the R object later.

If you do want to convert to a data frame you can first convert to a nested data frame, and then fill in the blanks in the data frame. Thus...

require(data.table)
require(plyr)


operacions<-list(list(Nom="Victor",Bolis= c("Negro","azul","verde")),list(Nom="Dani",Lapices=c(1:4)))
str(operacions)
operacionsdf <- lapply(operacions, data.frame, stringsAsFactors = FALSE)
str(operacionsdf)

operacionsdf2 <- rbind.fill(operacionsdf)
str(operacionsdf2)
write.csv2(operacionsdf2, "file.csv",row.names = FALSE)
operacionsdf3 <- read.csv2("file.csv")
str(operacionsdf3)

output:

> require(data.table)
> require(plyr)
> operacions<-list(list(Nom="Victor",Bolis= c("Negro","azul","verde")),list(Nom="Dani",Lapices=c(1:4)))
> str(operacions)
List of 2
 $ :List of 2
  ..$ Nom  : chr "Victor"
  ..$ Bolis: chr [1:3] "Negro" "azul" "verde"
 $ :List of 2
  ..$ Nom    : chr "Dani"
  ..$ Lapices: int [1:4] 1 2 3 4
> operacionsdf <- lapply(operacions, data.frame, stringsAsFactors = FALSE)
> str(operacionsdf)
List of 2
 $ :'data.frame':   3 obs. of  2 variables:
  ..$ Nom  : chr [1:3] "Victor" "Victor" "Victor"
  ..$ Bolis: chr [1:3] "Negro" "azul" "verde"
 $ :'data.frame':   4 obs. of  2 variables:
  ..$ Nom    : chr [1:4] "Dani" "Dani" "Dani" "Dani"
  ..$ Lapices: int [1:4] 1 2 3 4
> operacionsdf2 <- rbind.fill(operacionsdf)
> str(operacionsdf2)
'data.frame':   7 obs. of  3 variables:
 $ Nom    : chr  "Victor" "Victor" "Victor" "Dani" ...
 $ Bolis  : chr  "Negro" "azul" "verde" NA ...
 $ Lapices: int  NA NA NA 1 2 3 4
> write.csv2(operacionsdf2, "file.csv",row.names = FALSE)
> operacionsdf3 <- read.csv2("file.csv")
> str(operacionsdf3)
'data.frame':   7 obs. of  3 variables:
 $ Nom    : Factor w/ 2 levels "Dani","Victor": 2 2 2 1 1 1 1
 $ Bolis  : Factor w/ 3 levels "azul","Negro",..: 2 1 3 NA NA NA NA
 $ Lapices: int  NA NA NA 1 2 3 4

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