mtabulate. qdapTools 1.3.1

Usage

mtabulate(vects)

Arguments

vects: A vector, list, or data.frame of named/unnamed vectors.

Value

Returns a data.frame with columns equal to number of unique elements and the number of rows equal to the the original length of the vector, list, or data.frame (length equals ncols in data.frame). If list of vectors is named these will be the rownames of the dataframe.

Description

Similar to tabulate that works on multiple vectors.

References

http://stackoverflow.com/a/9961324/1000343

Examples

mtabulate(list(w=letters[1:10], x=letters[1:5], z=letters))

  a b c d e f g h i j k l m n o p q r s t u v w x y z
w 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
x 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
z 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1

mtabulate(list(mtcars$cyl[1:10]))

  4 6 8
1 3 5 2


## Dummy coding
mtabulate(mtcars$cyl[1:10])

   4 6 8
1  0 1 0
2  0 1 0
3  1 0 0
4  0 1 0
5  0 0 1
6  0 1 0
7  0 0 1
8  1 0 0
9  1 0 0
10 0 1 0

mtabulate(CO2[, "Plant"])

   Qn1 Qn2 Qn3 Qc1 Qc3 Qc2 Mn3 Mn2 Mn1 Mc2 Mc3 Mc1
1    1   0   0   0   0   0   0   0   0   0   0   0
2    1   0   0   0   0   0   0   0   0   0   0   0
3    1   0   0   0   0   0   0   0   0   0   0   0
4    1   0   0   0   0   0   0   0   0   0   0   0
5    1   0   0   0   0   0   0   0   0   0   0   0
6    1   0   0   0   0   0   0   0   0   0   0   0
7    1   0   0   0   0   0   0   0   0   0   0   0
8    0   1   0   0   0   0   0   0   0   0   0   0
9    0   1   0   0   0   0   0   0   0   0   0   0
10   0   1   0   0   0   0   0   0   0   0   0   0
11   0   1   0   0   0   0   0   0   0   0   0   0
12   0   1   0   0   0   0   0   0   0   0   0   0
13   0   1   0   0   0   0   0   0   0   0   0   0
14   0   1   0   0   0   0   0   0   0   0   0   0
15   0   0   1   0   0   0   0   0   0   0   0   0
16   0   0   1   0   0   0   0   0   0   0   0   0
17   0   0   1   0   0   0   0   0   0   0   0   0
18   0   0   1   0   0   0   0   0   0   0   0   0
19   0   0   1   0   0   0   0   0   0   0   0   0
20   0   0   1   0   0   0   0   0   0   0   0   0
21   0   0   1   0   0   0   0   0   0   0   0   0
22   0   0   0   1   0   0   0   0   0   0   0   0
23   0   0   0   1   0   0   0   0   0   0   0   0
24   0   0   0   1   0   0   0   0   0   0   0   0
25   0   0   0   1   0   0   0   0   0   0   0   0
26   0   0   0   1   0   0   0   0   0   0   0   0
27   0   0   0   1   0   0   0   0   0   0   0   0
28   0   0   0   1   0   0   0   0   0   0   0   0
29   0   0   0   0   0   1   0   0   0   0   0   0
30   0   0   0   0   0   1   0   0   0   0   0   0
31   0   0   0   0   0   1   0   0   0   0   0   0
32   0   0   0   0   0   1   0   0   0   0   0   0
33   0   0   0   0   0   1   0   0   0   0   0   0
34   0   0   0   0   0   1   0   0   0   0   0   0
35   0   0   0   0   0   1   0   0   0   0   0   0
36   0   0   0   0   1   0   0   0   0   0   0   0
37   0   0   0   0   1   0   0   0   0   0   0   0
38   0   0   0   0   1   0   0   0   0   0   0   0
39   0   0   0   0   1   0   0   0   0   0   0   0
40   0   0   0   0   1   0   0   0   0   0   0   0
41   0   0   0   0   1   0   0   0   0   0   0   0
42   0   0   0   0   1   0   0   0   0   0   0   0
43   0   0   0   0   0   0   0   0   1   0   0   0
44   0   0   0   0   0   0   0   0   1   0   0   0
45   0   0   0   0   0   0   0   0   1   0   0   0
46   0   0   0   0   0   0   0   0   1   0   0   0
47   0   0   0   0   0   0   0   0   1   0   0   0
48   0   0   0   0   0   0   0   0   1   0   0   0
49   0   0   0   0   0   0   0   0   1   0   0   0
50   0   0   0   0   0   0   0   1   0   0   0   0
51   0   0   0   0   0   0   0   1   0   0   0   0
52   0   0   0   0   0   0   0   1   0   0   0   0
53   0   0   0   0   0   0   0   1   0   0   0   0
54   0   0   0   0   0   0   0   1   0   0   0   0
55   0   0   0   0   0   0   0   1   0   0   0   0
56   0   0   0   0   0   0   0   1   0   0   0   0
57   0   0   0   0   0   0   1   0   0   0   0   0
58   0   0   0   0   0   0   1   0   0   0   0   0
59   0   0   0   0   0   0   1   0   0   0   0   0
60   0   0   0   0   0   0   1   0   0   0   0   0
61   0   0   0   0   0   0   1   0   0   0   0   0
62   0   0   0   0   0   0   1   0   0   0   0   0
63   0   0   0   0   0   0   1   0   0   0   0   0
64   0   0   0   0   0   0   0   0   0   0   0   1
65   0   0   0   0   0   0   0   0   0   0   0   1
66   0   0   0   0   0   0   0   0   0   0   0   1
67   0   0   0   0   0   0   0   0   0   0   0   1
68   0   0   0   0   0   0   0   0   0   0   0   1
69   0   0   0   0   0   0   0   0   0   0   0   1
70   0   0   0   0   0   0   0   0   0   0   0   1
71   0   0   0   0   0   0   0   0   0   1   0   0
72   0   0   0   0   0   0   0   0   0   1   0   0
73   0   0   0   0   0   0   0   0   0   1   0   0
74   0   0   0   0   0   0   0   0   0   1   0   0
75   0   0   0   0   0   0   0   0   0   1   0   0
76   0   0   0   0   0   0   0   0   0   1   0   0
77   0   0   0   0   0   0   0   0   0   1   0   0
78   0   0   0   0   0   0   0   0   0   0   1   0
79   0   0   0   0   0   0   0   0   0   0   1   0
80   0   0   0   0   0   0   0   0   0   0   1   0
81   0   0   0   0   0   0   0   0   0   0   1   0
82   0   0   0   0   0   0   0   0   0   0   1   0
83   0   0   0   0   0   0   0   0   0   0   1   0
84   0   0   0   0   0   0   0   0   0   0   1   0


dat <- data.frame(matrix(sample(c("A", "B"), 30, TRUE), ncol=3))
mtabulate(dat)

   A B
X1 4 6
X2 4 6
X3 8 2

t(mtabulate(dat))

  X1 X2 X3
A  4  4  8
B  6  6  2

counts2list(mtabulate(dat))

      X1  X2  X3 
 [1,] "A" "A" "A"
 [2,] "A" "A" "A"
 [3,] "A" "A" "A"
 [4,] "A" "A" "A"
 [5,] "B" "B" "A"
 [6,] "B" "B" "A"
 [7,] "B" "B" "A"
 [8,] "B" "B" "A"
 [9,] "B" "B" "B"
[10,] "B" "B" "B"
attr(,"names")
 [1] "X1" "X2" "X3" NA   NA   NA   NA   NA   NA   NA   NA   NA   NA   NA   NA   NA   NA   NA   NA   NA   NA   NA   NA   NA  
[25] NA   NA   NA   NA   NA   NA

Author

Joran Elias and Tyler Rinker .

Tabulate Frequency Counts for Multiple Vectors