Simplified dput() in R
3 solutions :
a wrapper around
dput
(handles standarddata.frames
,tibbles
andlists
)a
read.table
solution (fordata.frames
)a
tibble::tribble
solution (fordata.frames
, returning atibble
)All include
n
andrandom
parameter which allow one to dput only the head of the data or sample it on the fly.
dput_small1(Df)# Df <- data.frame(# A = c(2, 2, 2, 6, 7, 8),# B = structure(c(1L, 2L, 4L, NA, 3L, 3L), .Label = c("A", "G", "L", # "N"), class = "factor"),# C = c(1L, 3L, 5L, NA, NA, NA) ,# stringsAsFactors=FALSE)dput_small2(Df,stringsAsFactors=TRUE)# Df <- read.table(sep="\t", text="# A B C# 2 A 1# 2 G 3# 2 N 5# 6 NA NA# 7 L NA# 8 L NA", header=TRUE, stringsAsFactors=TRUE)dput_small3(Df)# Df <- tibble::tribble(# ~A, ~B, ~C,# 2, "A", 1L,# 2, "G", 3L,# 2, "N", 5L,# 6, NA_character_, NA_integer_,# 7, "L", NA_integer_,# 8, "L", NA_integer_# )# Df$B <- factor(Df$B)
Wrapper around dput
This option that gives an output very close to the one proposed in the question. It's quite general because it's actually wrapped around dput
, but applied separately on columns.
multiline
means 'keep dput's default output laid out into multiple lines'.
dput_small1<- function(x, name=as.character(substitute(x)), multiline = TRUE, n=if ('list' %in% class(x)) length(x) else nrow(x), random=FALSE, seed = 1){ name if('tbl_df' %in% class(x)) create_fun <- "tibble::tibble" else if('list' %in% class(x)) create_fun <- "list" else if('data.table' %in% class(x)) create_fun <- "data.table::data.table" else create_fun <- "data.frame" if(random) { set.seed(seed) if(create_fun == "list") x <- x[sample(1:length(x),n)] else x <- x[sample(1:nrow(x),n),] } else { x <- head(x,n) } line_sep <- if (multiline) "\n " else "" cat(sep='',name," <- ",create_fun,"(\n ", paste0(unlist( Map(function(item,nm) paste0(nm,if(nm=="") "" else " = ",paste(capture.output(dput(item)),collapse=line_sep)), x,if(is.null(names(x))) rep("",length(x)) else names(x))), collapse=",\n "), if(create_fun == "data.frame") ",\n stringsAsFactors = FALSE)" else "\n)")}dput_small1(list(1,2,c=3,d=4),"my_list",random=TRUE,n=3)# my_list <- list(# 2,# d = 4,# c = 3# )
read.table
solution
For data.frames
I find it comfortable however to have the input in a more explicit/tabular format.
This can be reached using read.table
, then reformatting automatically the type of columns that read.table
wouldn't get right. Not as general as first solution but will work smoothly for 95% of the cases found on SO
.
dput_small2 <- function(df, name=as.character(substitute(df)), sep='\t', header=TRUE, stringsAsFactors = FALSE, n= nrow(df), random=FALSE, seed = 1){ name if(random) { set.seed(seed) df <- df[sample(1:nrow(df),n),] } else { df <- head(df,n) } cat(sep='',name,' <- read.table(sep="',sub('\t','\\\\t',sep),'", text="\n ', paste(colnames(df),collapse=sep)) df <- head(df,n) apply(df,1,function(x) cat(sep='','\n ',paste(x,collapse=sep))) cat(sep='','", header=',header,', stringsAsFactors=',stringsAsFactors,')') sapply(names(df), function(x){ if(is.character(df[[x]]) & suppressWarnings(identical(as.character(as.numeric(df[[x]])),df[[x]]))){ # if it's a character column containing numbers cat(sep='','\n',name,'$',x,' <- as.character(', name,'$',x,')') } else if(is.factor(df[[x]]) & !stringsAsFactors) { # if it's a factor and conversion is not automated cat(sep='','\n',name,'$',x,' <- factor(', name,'$',x,')') } else if(inherits(df[[x]], "POSIXct")){ cat(sep='','\n',name,'$',x,' <- as.POSIXct(', name,'$',x,')') } else if(inherits(df[[x]], "Date")){ cat(sep='','\n',name,'$',x,' <- as.Date(', name,'$',x,')') }}) invisible(NULL)}
Simplest case
dput_small2(iris,n=6)
will print:
iris <- read.table(sep="\t", text=" Sepal.Length Sepal.Width Petal.Length Petal.Width Species 5.1 3.5 1.4 0.2 setosa 4.9 3.0 1.4 0.2 setosa 4.7 3.2 1.3 0.2 setosa 4.6 3.1 1.5 0.2 setosa 5.0 3.6 1.4 0.2 setosa 5.4 3.9 1.7 0.4 setosa", header=TRUE, stringsAsFactors=FALSE)
which in turn when executed will return :
# Sepal.Length Sepal.Width Petal.Length Petal.Width Species# 1 5.1 3.5 1.4 0.2 setosa# 2 4.9 3.0 1.4 0.2 setosa# 3 4.7 3.2 1.3 0.2 setosa# 4 4.6 3.1 1.5 0.2 setosa# 5 5.0 3.6 1.4 0.2 setosa# 6 5.4 3.9 1.7 0.4 setosastr(iris)# 'data.frame': 6 obs. of 5 variables:# $ Sepal.Length: num 5.1 4.9 4.7 4.6 5 5.4# $ Sepal.Width : num 3.5 3 3.2 3.1 3.6 3.9# $ Petal.Length: num 1.4 1.4 1.3 1.5 1.4 1.7# $ Petal.Width : num 0.2 0.2 0.2 0.2 0.2 0.4# $ Species : chr " setosa" " setosa" " setosa" " setosa" ...
more complex
dummy data:
test <- data.frame(a=1:5, b=as.character(6:10), c=letters[1:5], d=factor(letters[6:10]), e=Sys.time()+(1:5), stringsAsFactors = FALSE)
This:
dput_small2(test,'df2')
will print:
df2 <- read.table(sep="\t", text=" a b c d e 1 6 a f 2018-02-15 11:53:17 2 7 b g 2018-02-15 11:53:18 3 8 c h 2018-02-15 11:53:19 4 9 d i 2018-02-15 11:53:20 5 10 e j 2018-02-15 11:53:21", header=TRUE, stringsAsFactors=FALSE)df2$b <- as.character(df2$b)df2$d <- factor(df2$d)df2$e <- as.POSIXct(df2$e)
which in turn when executed will return :
# a b c d e# 1 1 6 a f 2018-02-15 11:53:17# 2 2 7 b g 2018-02-15 11:53:18# 3 3 8 c h 2018-02-15 11:53:19# 4 4 9 d i 2018-02-15 11:53:20# 5 5 10 e j 2018-02-15 11:53:21str(df2) # 'data.frame': 5 obs. of 5 variables:# $ a: int 1 2 3 4 5# $ b: chr "6" "7" "8" "9" ...# $ c: chr "a" "b" "c" "d" ...# $ d: Factor w/ 5 levels "f","g","h","i",..: 1 2 3 4 5# $ e: POSIXct, format: "2018-02-15 11:53:17" "2018-02-15 11:53:18" "2018-02-15 11:53:19" "2018-02-15 11:53:20" ...all.equal(df2,test)# [1] "Component āeā: Mean absolute difference: 0.4574251" # only some rounding error
tribble
solution
The read.table
option is very readable but not very general. with tribble
pretty much any data type can be handled (though factors need adhoc fixing).
This solution isn't so useful for OP's example but is great for list columns (see example below). To make use of the output, library tibble
is required.
Just as my first solution, it's a wrapper around dput
, but instead of 'dputting' columns, i'm 'dputting' elements.
dput_small3 <- function(df, name=as.character(substitute(df)), n= nrow(df), random=FALSE, seed = 1){ name if(random) { set.seed(seed) df <- df[sample(1:nrow(df),n),] } else { df <- head(df,n) } df1 <- lapply(df,function(col) if(is.factor(col)) as.character(col) else col) dputs <- sapply(df1,function(col){ col_dputs <- sapply(col,function(elt) paste(capture.output(dput(elt)),collapse="")) max_char <- max(nchar(unlist(col_dputs))) sapply(col_dputs,function(elt) paste(c(rep(" ",max_char-nchar(elt)),elt),collapse="")) }) lines <- paste(apply(dputs,1,paste,collapse=", "),collapse=",\n ") output <- paste0(name," <- tibble::tribble(\n ", paste0("~",names(df),collapse=", "), ",\n ",lines,"\n)") cat(output) sapply(names(df), function(x) if(is.factor(df[[x]])) cat(sep='','\n',name,'$',x,' <- factor(', name,'$',x,')')) invisible(NULL)}dput_small3(dplyr::starwars[c(1:3,11)],"sw",n=6,random=TRUE)# sw <- tibble::tribble(# ~name, ~height, ~mass, ~films,# "Lando Calrissian", 177L, 79, c("Return of the Jedi", "The Empire Strikes Back"),# "Finis Valorum", 170L, NA_real_, "The Phantom Menace",# "Ki-Adi-Mundi", 198L, 82, c("Attack of the Clones", "The Phantom Menace", "Revenge of the Sith"),# "Grievous", 216L, 159, "Revenge of the Sith",# "Wedge Antilles", 170L, 77, c("Return of the Jedi", "The Empire Strikes Back", "A New Hope"),# "Wat Tambor", 193L, 48, "Attack of the Clones"# )
The package datapasta
won't always work perfectly as it currently doesn't support all types, but it is clean and easy, i.e.,
# install.packages(c("datapasta"), dependencies = TRUE) datapasta::dpasta(Df)#> data.frame(#> A = c(2, 2, 2, 6, 7, 8),#> C = c(1L, 3L, 5L, NA, NA, NA),#> B = as.factor(c("A", "G", "N", NA, "L", "L"))#> )
We could set control to NULL to simplify:
dput(Df, control = NULL)# list(A = c(2, 2, 2, 6, 7, 8), B = c(NA, NA, NA, NA, 7, 9), C = c(1, 3, 5, NA, NA, NA))
Then wrap it with data.frame:
data.frame(dput(Df, control = NULL))
Edit: To avoid factor columns getting converted to numbers, we could convert them to character before calling dput:
dput_small <- function(d){ ix <- sapply(d, is.factor) d[ix] <- lapply(d[ix], as.character) dput(d, control = NULL) }