Rでデータフレームを再作成するコードを取得する方法は？

Question

私はいくつかのデータフレームオブジェクトを持っています。

私は、そのデータフレームオブジェクトを再現するコードを見たいと思います。 recreate(ror)

recreate(ror) 
# data.frame(from = c('x1', 'x'), to = c('x2', 'y')) 

私は機能があったことを覚えています。たとえば

は、ここで私のようないくつかの関数を呼び出すことによって印刷する次のコードを取得したい私のデータフレーム

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 

ですrorからこのコードを取得するには、この関数の正確な名前または正確な用語をGoogleで検索するために検索することができません。たぶん

Answer 1

この：？

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"))