mtabulate: Tabulate Frequency Counts for Multiple Vectors
In textshape: Tools for Reshaping Text
Description
Usage
Arguments
Value
Author(s)
References
See Also
Examples
Description
mtabulate - Similar to tabulate that works on
multiple vectors.
as_list - Convert a count matrix to a named list of elements. The
semantic inverse of mtabulate.
Usage
1
2
3
Arguments
vects
A vector, list, or
data.frame of named/unnamed vectors.
mat
A matrix of counts.
nm
A character vector of names to assign to the list.
Value
mtabulate - 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
number of columns in data.frame). If list of vectors is
named these will be the rownames of the dataframe.
as_list - Returns a list of elements.
Author(s)
Joran Elias and Tyler Rinker <tyler.rinker@gmail.com>.
References
https://stackoverflow.com/a/9961324/1000343
See Also
Examples
1
2
3
4
5
6
7
8
9
10
11
12
mtabulate(list(w=letters[1:10], x=letters[1:5], z=letters))
mtabulate(list(mtcars$cyl[1:10]))
## Dummy coding
mtabulate(mtcars$cyl[1:10])
mtabulate(CO2[, "Plant"])
dat <- data.frame(matrix(sample(c("A", "B"), 30, TRUE), ncol=3))
mtabulate(dat)
as_list(mtabulate(dat))
t(mtabulate(dat))
as_list(t(mtabulate(dat)))
Example output
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
4 6 8
1 3 5 2
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
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
A B
X1 4 6
X2 3 7
X3 3 7
$X1
[1] "A"
$X2
[1] "A"
$X3
[1] "A"
$<NA>
[1] "A"
$<NA>
[1] "B"
$<NA>
[1] "B"
$<NA>
[1] "B"
$<NA>
[1] "B"
$<NA>
[1] "B"
$<NA>
[1] "B"
$<NA>
[1] "A"
$<NA>
[1] "A"
$<NA>
[1] "A"
$<NA>
[1] "B"
$<NA>
[1] "B"
$<NA>
[1] "B"
$<NA>
[1] "B"
$<NA>
[1] "B"
$<NA>
[1] "B"
$<NA>
[1] "B"
$<NA>
[1] "A"
$<NA>
[1] "A"
$<NA>
[1] "A"
$<NA>
[1] "B"
$<NA>
[1] "B"
$<NA>
[1] "B"
$<NA>
[1] "B"
$<NA>
[1] "B"
$<NA>
[1] "B"
$<NA>
[1] "B"
X1 X2 X3
A 4 3 3
B 6 7 7
$A
[1] "X1" "X1" "X1" "X1" "X2" "X2" "X2" "X3" "X3" "X3"
$B
[1] "X1" "X1" "X1" "X1" "X1" "X1" "X2" "X2" "X2" "X2" "X2" "X2" "X2" "X3" "X3"
[16] "X3" "X3" "X3" "X3" "X3"
textshape documentation built on May 29, 2021, 1:07 a.m.
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Description Usage Arguments Value Author(s) References See Also Examples
Description
mtabulate - Similar to tabulate that works on
multiple vectors.
as_list - Convert a count matrix to a named list of elements. The
semantic inverse of mtabulate.
Usage
1 2 3 |
Arguments
vects |
A |
mat |
A matrix of counts. |
nm |
A character vector of names to assign to the list. |
Value
mtabulate - Returns a data.frame with
columns equal to number of unique elements and the number of rows equal to
the the original length of the vector,
list, or data.frame (length equals
number of columns in data.frame). If list of vectors is
named these will be the rownames of the dataframe.
as_list - Returns a list of elements.
Author(s)
Joran Elias and Tyler Rinker <tyler.rinker@gmail.com>.
References
https://stackoverflow.com/a/9961324/1000343
See Also
Examples
1 2 3 4 5 6 7 8 9 10 11 12 | mtabulate(list(w=letters[1:10], x=letters[1:5], z=letters))
mtabulate(list(mtcars$cyl[1:10]))
## Dummy coding
mtabulate(mtcars$cyl[1:10])
mtabulate(CO2[, "Plant"])
dat <- data.frame(matrix(sample(c("A", "B"), 30, TRUE), ncol=3))
mtabulate(dat)
as_list(mtabulate(dat))
t(mtabulate(dat))
as_list(t(mtabulate(dat)))
|
Example output
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
4 6 8
1 3 5 2
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
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
A B
X1 4 6
X2 3 7
X3 3 7
$X1
[1] "A"
$X2
[1] "A"
$X3
[1] "A"
$<NA>
[1] "A"
$<NA>
[1] "B"
$<NA>
[1] "B"
$<NA>
[1] "B"
$<NA>
[1] "B"
$<NA>
[1] "B"
$<NA>
[1] "B"
$<NA>
[1] "A"
$<NA>
[1] "A"
$<NA>
[1] "A"
$<NA>
[1] "B"
$<NA>
[1] "B"
$<NA>
[1] "B"
$<NA>
[1] "B"
$<NA>
[1] "B"
$<NA>
[1] "B"
$<NA>
[1] "B"
$<NA>
[1] "A"
$<NA>
[1] "A"
$<NA>
[1] "A"
$<NA>
[1] "B"
$<NA>
[1] "B"
$<NA>
[1] "B"
$<NA>
[1] "B"
$<NA>
[1] "B"
$<NA>
[1] "B"
$<NA>
[1] "B"
X1 X2 X3
A 4 3 3
B 6 7 7
$A
[1] "X1" "X1" "X1" "X1" "X2" "X2" "X2" "X3" "X3" "X3"
$B
[1] "X1" "X1" "X1" "X1" "X1" "X1" "X2" "X2" "X2" "X2" "X2" "X2" "X2" "X3" "X3"
[16] "X3" "X3" "X3" "X3" "X3"
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