I have some dataframe object.
I want to see the code that recreates that dataframe object.
For example, here is my dataframe
str(ror)
# 'data.frame': 2 obs. of 2 variables:
# $ from: Factor w/ 2 levels "x","x1": 2 1
# $ to : Factor w/ 2 levels "x2","y": 1 2
I want to get the following code to be printed by calling some function such as: recreate(ror)
recreate(ror)
# data.frame(from = c('x1', 'x'), to = c('x2', 'y'))
I remember that there was a function to get this code from ror, but I cannot find the exact name of this function or exact term to search in google to find it?
Maybe this:
recreate <- function(DF) {
res <- textConnection("foo", "w")
dput(lapply(DF,
function(x) if(is.factor(x)) as.character(x) else x),
control = c("keepNA", "keepInteger"), file = res)
close(res)
foo <- sub("list", "data.frame", foo, fixed = TRUE)
parse(text = paste(foo, collapse = "\n"))[[1]]
}
newDF <- recreate(iris)
all.equal(eval(newDF), iris)
#[1] TRUE
print(newDF)
#data.frame(Sepal.Length = c(5.1, 4.9, 4.7, 4.6, 5, 5.4, 4.6,
# 5, 4.4, 4.9, 5.4, 4.8, 4.8, 4.3, 5.8, 5.7, 5.4, 5.1, 5.7,
# 5.1, 5.4, 5.1, 4.6, 5.1, 4.8, 5, 5, 5.2, 5.2, 4.7, 4.8, 5.4,
# 5.2, 5.5, 4.9, 5, 5.5, 4.9, 4.4, 5.1, 5, 4.5, 4.4, 5, 5.1,
# 4.8, 5.1, 4.6, 5.3, 5, 7, 6.4, 6.9, 5.5, 6.5, 5.7, 6.3, 4.9,
# 6.6, 5.2, 5, 5.9, 6, 6.1, 5.6, 6.7, 5.6, 5.8, 6.2, 5.6, 5.9,
# 6.1, 6.3, 6.1, 6.4, 6.6, 6.8, 6.7, 6, 5.7, 5.5, 5.5, 5.8,
# 6, 5.4, 6, 6.7, 6.3, 5.6, 5.5, 5.5, 6.1, 5.8, 5, 5.6, 5.7,
# 5.7, 6.2, 5.1, 5.7, 6.3, 5.8, 7.1, 6.3, 6.5, 7.6, 4.9, 7.3,
# 6.7, 7.2, 6.5, 6.4, 6.8, 5.7, 5.8, 6.4, 6.5, 7.7, 7.7, 6,
# 6.9, 5.6, 7.7, 6.3, 6.7, 7.2, 6.2, 6.1, 6.4, 7.2, 7.4, 7.9,
# 6.4, 6.3, 6.1, 7.7, 6.3, 6.4, 6, 6.9, 6.7, 6.9, 5.8, 6.8,
# 6.7, 6.7, 6.3, 6.5, 6.2, 5.9), Sepal.Width = c(3.5, 3, 3.2,
# 3.1, 3.6, 3.9, 3.4, 3.4, 2.9, 3.1, 3.7, 3.4, 3, 3, 4, 4.4,
# 3.9, 3.5, 3.8, 3.8, 3.4, 3.7, 3.6, 3.3, 3.4, 3, 3.4, 3.5,
# 3.4, 3.2, 3.1, 3.4, 4.1, 4.2, 3.1, 3.2, 3.5, 3.6, 3, 3.4,
# 3.5, 2.3, 3.2, 3.5, 3.8, 3, 3.8, 3.2, 3.7, 3.3, 3.2, 3.2,
# 3.1, 2.3, 2.8, 2.8, 3.3, 2.4, 2.9, 2.7, 2, 3, 2.2, 2.9, 2.9,
# 3.1, 3, 2.7, 2.2, 2.5, 3.2, 2.8, 2.5, 2.8, 2.9, 3, 2.8, 3,
# 2.9, 2.6, 2.4, 2.4, 2.7, 2.7, 3, 3.4, 3.1, 2.3, 3, 2.5, 2.6,
# 3, 2.6, 2.3, 2.7, 3, 2.9, 2.9, 2.5, 2.8, 3.3, 2.7, 3, 2.9,
# 3, 3, 2.5, 2.9, 2.5, 3.6, 3.2, 2.7, 3, 2.5, 2.8, 3.2, 3,
# 3.8, 2.6, 2.2, 3.2, 2.8, 2.8, 2.7, 3.3, 3.2, 2.8, 3, 2.8,
# 3, 2.8, 3.8, 2.8, 2.8, 2.6, 3, 3.4, 3.1, 3, 3.1, 3.1, 3.1,
# 2.7, 3.2, 3.3, 3, 2.5, 3, 3.4, 3), Petal.Length = c(1.4,
# 1.4, 1.3, 1.5, 1.4, 1.7, 1.4, 1.5, 1.4, 1.5, 1.5, 1.6, 1.4,
# 1.1, 1.2, 1.5, 1.3, 1.4, 1.7, 1.5, 1.7, 1.5, 1, 1.7, 1.9,
# 1.6, 1.6, 1.5, 1.4, 1.6, 1.6, 1.5, 1.5, 1.4, 1.5, 1.2, 1.3,
# 1.4, 1.3, 1.5, 1.3, 1.3, 1.3, 1.6, 1.9, 1.4, 1.6, 1.4, 1.5,
# 1.4, 4.7, 4.5, 4.9, 4, 4.6, 4.5, 4.7, 3.3, 4.6, 3.9, 3.5,
# 4.2, 4, 4.7, 3.6, 4.4, 4.5, 4.1, 4.5, 3.9, 4.8, 4, 4.9, 4.7,
# 4.3, 4.4, 4.8, 5, 4.5, 3.5, 3.8, 3.7, 3.9, 5.1, 4.5, 4.5,
# 4.7, 4.4, 4.1, 4, 4.4, 4.6, 4, 3.3, 4.2, 4.2, 4.2, 4.3, 3,
# 4.1, 6, 5.1, 5.9, 5.6, 5.8, 6.6, 4.5, 6.3, 5.8, 6.1, 5.1,
# 5.3, 5.5, 5, 5.1, 5.3, 5.5, 6.7, 6.9, 5, 5.7, 4.9, 6.7, 4.9,
# 5.7, 6, 4.8, 4.9, 5.6, 5.8, 6.1, 6.4, 5.6, 5.1, 5.6, 6.1,
# 5.6, 5.5, 4.8, 5.4, 5.6, 5.1, 5.1, 5.9, 5.7, 5.2, 5, 5.2,
# 5.4, 5.1), Petal.Width = c(0.2, 0.2, 0.2, 0.2, 0.2, 0.4,
# 0.3, 0.2, 0.2, 0.1, 0.2, 0.2, 0.1, 0.1, 0.2, 0.4, 0.4, 0.3,
# 0.3, 0.3, 0.2, 0.4, 0.2, 0.5, 0.2, 0.2, 0.4, 0.2, 0.2, 0.2,
# 0.2, 0.4, 0.1, 0.2, 0.2, 0.2, 0.2, 0.1, 0.2, 0.2, 0.3, 0.3,
# 0.2, 0.6, 0.4, 0.3, 0.2, 0.2, 0.2, 0.2, 1.4, 1.5, 1.5, 1.3,
# 1.5, 1.3, 1.6, 1, 1.3, 1.4, 1, 1.5, 1, 1.4, 1.3, 1.4, 1.5,
# 1, 1.5, 1.1, 1.8, 1.3, 1.5, 1.2, 1.3, 1.4, 1.4, 1.7, 1.5,
# 1, 1.1, 1, 1.2, 1.6, 1.5, 1.6, 1.5, 1.3, 1.3, 1.3, 1.2, 1.4,
# 1.2, 1, 1.3, 1.2, 1.3, 1.3, 1.1, 1.3, 2.5, 1.9, 2.1, 1.8,
# 2.2, 2.1, 1.7, 1.8, 1.8, 2.5, 2, 1.9, 2.1, 2, 2.4, 2.3, 1.8,
# 2.2, 2.3, 1.5, 2.3, 2, 2, 1.8, 2.1, 1.8, 1.8, 1.8, 2.1, 1.6,
# 1.9, 2, 2.2, 1.5, 1.4, 2.3, 2.4, 1.8, 1.8, 2.1, 2.4, 2.3,
# 1.9, 2.3, 2.5, 2.3, 1.9, 2, 2.3, 1.8), Species = c("setosa",
# "setosa", "setosa", "setosa", "setosa", "setosa", "setosa",
# "setosa", "setosa", "setosa", "setosa", "setosa", "setosa",
# "setosa", "setosa", "setosa", "setosa", "setosa", "setosa",
# "setosa", "setosa", "setosa", "setosa", "setosa", "setosa",
# "setosa", "setosa", "setosa", "setosa", "setosa", "setosa",
# "setosa", "setosa", "setosa", "setosa", "setosa", "setosa",
# "setosa", "setosa", "setosa", "setosa", "setosa", "setosa",
# "setosa", "setosa", "setosa", "setosa", "setosa", "setosa",
# "setosa", "versicolor", "versicolor", "versicolor", "versicolor",
# "versicolor", "versicolor", "versicolor", "versicolor", "versicolor",
# "versicolor", "versicolor", "versicolor", "versicolor", "versicolor",
# "versicolor", "versicolor", "versicolor", "versicolor", "versicolor",
# "versicolor", "versicolor", "versicolor", "versicolor", "versicolor",
# "versicolor", "versicolor", "versicolor", "versicolor", "versicolor",
# "versicolor", "versicolor", "versicolor", "versicolor", "versicolor",
# "versicolor", "versicolor", "versicolor", "versicolor", "versicolor",
# "versicolor", "versicolor", "versicolor", "versicolor", "versicolor",
# "versicolor", "versicolor", "versicolor", "versicolor", "versicolor",
# "versicolor", "virginica", "virginica", "virginica", "virginica",
# "virginica", "virginica", "virginica", "virginica", "virginica",
# "virginica", "virginica", "virginica", "virginica", "virginica",
# "virginica", "virginica", "virginica", "virginica", "virginica",
# "virginica", "virginica", "virginica", "virginica", "virginica",
# "virginica", "virginica", "virginica", "virginica", "virginica",
# "virginica", "virginica", "virginica", "virginica", "virginica",
# "virginica", "virginica", "virginica", "virginica", "virginica",
# "virginica", "virginica", "virginica", "virginica", "virginica",
# "virginica", "virginica", "virginica", "virginica", "virginica",
# "virginica"))