R - describe() output to a data frame - r

Question

I want to create a data frame using describe() function. Dataset under consideration is iris. The data frame should look like this:
Variable n missing unique Info Mean 0.05 0.1 0.25 0.5 0.75 0.9 0.95
Sepal.Length 150 0 35 1 5.843 4.6 4.8 5.1 5.8 6.4 6.9 7.255
Sepal.Width 150 0 23 0.99 3.057 2.345 2.5 2.8 3 3.3 3.61 3.8
Petal.Length 150 0 43 1 3.758 1.3 1.4 1.6 4.35 5.1 5.8 6.1
Petal.Width 150 0 22 0.99 1.199 0.2 0.2 0.3 1.3 1.8 2.2 2.3
Species 150 0 3
Is there a way out to coerce the output of describe() to data.frame type? When I try to coerce, I get an error as shown below:
library(Hmisc)
statistics <- describe(iris)
statistics[1]
first_vec <- statistics[1]$Sepal.Length
as.data.frame(first_vec)
#Error in as.data.frame.default(first_vec) : cannot coerce class ""describe"" to a data.frame
Thanks

Answer 1

The way to figure this out is to examine the objects with str():
data(iris)
library(Hmisc)
di <- describe(iris)
di
# iris
#
# 5 Variables 150 Observations
# -------------------------------------------------------------
# Sepal.Length
# n missing unique Info Mean .05 .10 .25 .50 .75 .90 .95
# 150 0 35 1 5.843 4.600 4.800 5.100 5.800 6.400 6.900 7.255
#
# lowest : 4.3 4.4 4.5 4.6 4.7, highest: 7.3 7.4 7.6 7.7 7.9
# -------------------------------------------------------------
# ...
# -------------------------------------------------------------
# Species
# n missing unique
# 150 0 3
#
# setosa (50, 33%), versicolor (50, 33%)
# virginica (50, 33%)
# -------------------------------------------------------------
str(di)
# List of 5
# $ Sepal.Length:List of 6
# ..$ descript : chr "Sepal.Length"
# ..$ units : NULL
# ..$ format : NULL
# ..$ counts : Named chr [1:12] "150" "0" "35" "1" ...
# .. ..- attr(*, "names")= chr [1:12] "n" "missing" "unique" "Info" ...
# ..$ intervalFreq:List of 2
# .. ..$ range: atomic [1:2] 4.3 7.9
# .. .. ..- attr(*, "Csingle")= logi TRUE
# .. ..$ count: int [1:100] 1 0 3 0 0 1 0 0 4 0 ...
# ..$ values : Named chr [1:10] "4.3" "4.4" "4.5" "4.6" ...
# .. ..- attr(*, "names")= chr [1:10] "L1" "L2" "L3" "L4" ...
# ..- attr(*, "class")= chr "describe"
# $ Sepal.Width :List of 6
# ...
# $ Species :List of 5
# ..$ descript: chr "Species"
# ..$ units : NULL
# ..$ format : NULL
# ..$ counts : Named num [1:3] 150 0 3
# .. ..- attr(*, "names")= chr [1:3] "n" "missing" "unique"
# ..$ values : num [1:2, 1:3] 50 33 50 33 50 33
# .. ..- attr(*, "dimnames")=List of 2
# .. .. ..$ : chr [1:2] "Frequency" "%"
# .. .. ..$ : chr [1:3] "setosa" "versicolor" "virginica"
# ..- attr(*, "class")= chr "describe"
# - attr(*, "descript")= chr "iris"
# - attr(*, "dimensions")= int [1:2] 150 5
# - attr(*, "class")= chr "describe"
We see that di is a list of lists. We can take it apart by looking at just the first sublist. You can convert that into a vector:
unlist(di[[1]])
# descript counts.n
# "Sepal.Length" "150"
# counts.missing counts.unique
# "0" "35"
# counts.Info counts.Mean
# "1" "5.843"
# counts..05 counts..10
# "4.600" "4.800"
# counts..25 counts..50
# "5.100" "5.800"
# counts..75 counts..90
# "6.400" "6.900"
# counts..95 intervalFreq.range1
# "7.255" "4.3"
# intervalFreq.range2 intervalFreq.count1
# "7.9" "1"
# ...
# values.H3 values.H2
# "7.6" "7.7"
# values.H1
# "7.9"
str(unlist(di[[1]]))
# Named chr [1:125] "Sepal.Length" "150" "0" "35" ...
# - attr(*, "names")= chr [1:125] "descript" "counts.n" "counts.missing" "counts.unique" ...
It is very, very long (125). The elements have been coerced to all be of the same (and most inclusive) type, namely, character. It seems you want the 2nd through 12th elements:
unlist(di[[1]])[2:12]
# counts.n counts.missing counts.unique counts.Info
# "150" "0" "35" "1"
# counts.Mean counts..05 counts..10 counts..25
# "5.843" "4.600" "4.800" "5.100"
# counts..50 counts..75 counts..90
# "5.800" "6.400" "6.900"
Now you have something you can start to work with. But notice that this only seems to be the case for numerical variables; the factor variable species is different:
unlist(di[[5]])
# descript counts.n counts.missing counts.unique
# "Species" "150" "0" "3"
# values1 values2 values3 values4
# "50" "33" "50" "33"
# values5 values6
# "50" "33"
In that case, it seems you only want elements two through four.
Using this process of discovery and problem solving, you can see how you'd take the output of describe apart and put the information you want into a data frame. However, this will take a lot of work. You'll presumably need to use loops and lots of if(){ ... } else{ ... } blocks. You might just want to code your own dataset description function from scratch.

Answer 2

You can do this by using the stat.desc function from the pastecs package:
library(pastecs)
summary_df <- stat.desc(mydata)
The summary_df is the dataframe you wanted. See more info here.

Answer 3

In R, you just have to use the summary(iris) function instead of describe(iris) function in Python.