- Simplifies the process and reduces the amount of code involved in generating
descriptive frequencies and statistics tables with or without formatting.
Descriptive frequencies and statistics tables
> dtable(iris2)
$Freq
Dataset Demographic Group Freq Perc
1 data1 Color blue 47 31.3%
2 red 38 25.3%
3 orange 34 22.7%
4 yellow 31 20.7%
5 data1 Species virginica 52 34.7%
6 setosa 51 34.0%
7 versicolor 47 31.3%
8 data1 Attractiveness 2 34 22.7%
9 1 33 22.0%
10 4 33 22.0%
11 3 27 18.0%
12 5 23 15.3%
13 data1 LikelyToBuy -2 22 14.7%
14 4 17 11.3%
15 -3 15 10.0%
16 2 15 10.0%
17 -5 14 9.3%
18 5 14 9.3%
19 1 13 8.7%
20 -4 12 8.0%
21 -1 10 6.7%
22 0 10 6.7%
23 3 8 5.3%
24 data1 Sold FALSE 84 56.0%
25 TRUE 66 44.0%
$Desc
dataset variable vars n mean sd median trimmed mad min max range skew kurtosis se
1 data1 Sepal.Length 1 150 5.8 0.8 5.8 5.8 0.9 4.4 7.9 3.5 0.3 -0.6 0.1
2 data1 Sepal.Width 1 150 3.1 0.5 3.0 3.1 0.4 2.0 4.2 2.2 0.1 -0.3 0.0
3 data1 Petal.Length 1 150 3.7 1.8 4.2 3.7 2.0 1.0 6.7 5.7 -0.3 -1.5 0.1
4 data1 Petal.Width 1 150 1.2 0.8 1.3 1.2 1.0 0.1 2.4 2.3 -0.1 -1.4 0.1
5 data1 Attractiveness 1 150 2.9 1.4 3.0 2.8 1.5 1.0 5.0 4.0 0.1 -1.3 0.1
6 data1 LikelyToBuy 1 150 -0.1 3.2 0.0 -0.1 4.4 -5.0 5.0 10.0 0.1 -1.3 0.3
> dtable(iris2, neat = FALSE)
$Freq
Dataset Demographic Group Freq Prop
1 data1 Color blue 47 0.31333333
2 data1 Color red 38 0.25333333
3 data1 Color orange 34 0.22666667
4 data1 Color yellow 31 0.20666667
5 data1 Species virginica 52 0.34666667
6 data1 Species setosa 51 0.34000000
7 data1 Species versicolor 47 0.31333333
8 data1 Attractiveness 2 34 0.22666667
9 data1 Attractiveness 1 33 0.22000000
10 data1 Attractiveness 4 33 0.22000000
11 data1 Attractiveness 3 27 0.18000000
12 data1 Attractiveness 5 23 0.15333333
13 data1 LikelyToBuy -2 22 0.14666667
14 data1 LikelyToBuy 4 17 0.11333333
15 data1 LikelyToBuy -3 15 0.10000000
16 data1 LikelyToBuy 2 15 0.10000000
17 data1 LikelyToBuy -5 14 0.09333333
18 data1 LikelyToBuy 5 14 0.09333333
19 data1 LikelyToBuy 1 13 0.08666667
20 data1 LikelyToBuy -4 12 0.08000000
21 data1 LikelyToBuy -1 10 0.06666667
22 data1 LikelyToBuy 0 10 0.06666667
23 data1 LikelyToBuy 3 8 0.05333333
24 data1 Sold FALSE 84 0.56000000
25 data1 Sold TRUE 66 0.44000000
$Desc
dataset variable vars n mean sd median trimmed mad min max range skew kurtosis se
1 data1 Sepal.Length 1 150 5.821333 0.8316384 5.80 5.791667 0.88956 4.4 7.9 3.5 0.29617680 -0.5971863 0.06790299
2 data1 Sepal.Width 1 150 3.078000 0.4708795 3.00 3.070833 0.44478 2.0 4.2 2.2 0.13300939 -0.2897237 0.03844715
3 data1 Petal.Length 1 150 3.711333 1.7596727 4.25 3.718333 2.00151 1.0 6.7 5.7 -0.26074778 -1.4861990 0.14367667
4 data1 Petal.Width 1 150 1.174667 0.7531755 1.30 1.159167 1.03782 0.1 2.4 2.3 -0.08662647 -1.4141391 0.06149652
5 data1 Attractiveness 1 150 2.860000 1.3904275 3.00 2.825000 1.48260 1.0 5.0 4.0 0.10018684 -1.3024980 0.11352793
6 data1 LikelyToBuy 1 150 -0.080000 3.2159836 0.00 -0.100000 4.44780 -5.0 5.0 10.0 0.08977883 -1.2869603 0.26258396
> dtable(iris2, as.list = T)
$Freq
$Freq[[1]]
Dataset Demographic Group Freq Perc
1 data1 Color blue 47 31.3%
2 red 38 25.3%
3 orange 34 22.7%
4 yellow 31 20.7%
$Freq[[2]]
Dataset Demographic Group Freq Perc
1 data1 Species virginica 52 34.7%
2 setosa 51 34.0%
3 versicolor 47 31.3%
$Freq[[3]]
Dataset Demographic Group Freq Perc
1 data1 Attractiveness 2 34 22.7%
2 1 33 22.0%
3 4 33 22.0%
4 3 27 18.0%
5 5 23 15.3%
$Freq[[4]]
Dataset Demographic Group Freq Perc
1 data1 LikelyToBuy -2 22 14.7%
2 4 17 11.3%
3 -3 15 10.0%
4 2 15 10.0%
5 -5 14 9.3%
6 5 14 9.3%
7 1 13 8.7%
8 -4 12 8.0%
9 -1 10 6.7%
10 0 10 6.7%
11 3 8 5.3%
$Freq[[5]]
Dataset Demographic Group Freq Perc
1 data1 Sold FALSE 84 56.0%
2 TRUE 66 44.0%
$Desc
$Desc[[1]]
dataset variable vars n mean sd median trimmed mad min max range skew kurtosis se
1 data1 Sepal.Length 1 150 5.8 0.8 5.8 5.8 0.9 4.4 7.9 3.5 0.3 -0.6 0.1
$Desc[[2]]
dataset variable vars n mean sd median trimmed mad min max range skew kurtosis se
1 data1 Sepal.Width 1 150 3.1 0.5 3 3.1 0.4 2 4.2 2.2 0.1 -0.3 0
$Desc[[3]]
dataset variable vars n mean sd median trimmed mad min max range skew kurtosis se
1 data1 Petal.Length 1 150 3.7 1.8 4.2 3.7 2 1 6.7 5.7 -0.3 -1.5 0.1
$Desc[[4]]
dataset variable vars n mean sd median trimmed mad min max range skew kurtosis se
1 data1 Petal.Width 1 150 1.2 0.8 1.3 1.2 1 0.1 2.4 2.3 -0.1 -1.4 0.1
$Desc[[5]]
dataset variable vars n mean sd median trimmed mad min max range skew kurtosis se
1 data1 Attractiveness 1 150 2.9 1.4 3 2.8 1.5 1 5 4 0.1 -1.3 0.1
$Desc[[6]]
dataset variable vars n mean sd median trimmed mad min max range skew kurtosis se
1 data1 LikelyToBuy 1 150 -0.1 3.2 0 -0.1 4.4 -5 5 10 0.1 -1.3 0.3
- Used to help predict whether to create a descriptive frequencies table,
descriptive statistics table, or both for each variable
> dvariable(iris2)
variable class mode type
1 Sepal.Length numeric numeric double
2 Sepal.Width numeric numeric double
3 Petal.Length numeric numeric double
4 Petal.Width numeric numeric double
5 Species factor numeric integer
6 Color character character character
7 Attractiveness integer numeric integer
8 LikelyToBuy integer numeric integer
9 Sold logical logical logical
React
Typescript
Django
Laravel
Facebook
Microsoft
Google
Alibaba
D3
Tencent