Number of rows based on frequency of one integer and position of another integer

Hello. I was wondering if someone could help me with this:

Let's say you have a 2000 x 2 matrix, where all the elements are integers. How can we count the number of rows that contain the number 10 in its first column and any number with the highest 5 integers in the second column?

In other words, the following but where X is the fifth highest number in the second column:

nnz(matrix(:,1) == 10 & matrix(:,2) > X);

EDIT -> Very importantly, the list with the highest 5 integers must be determined for each integer in the first column. So, if one wanted to do this for the number 10, it must be determining the highest 5 integers in the second column WHEN the integer in the first column is 10.

Thanks!

Answer 1

[Voss]

Get the set of unique numbers in the 2nd column:

col2_vals = unique(matrix(:,2));

The 5th highest is 4th from the end. So, to match any number within the highest 5:

nnz(matrix(:,1) == 10 & matrix(:,2) >= col2_vals(end-4));

[Neuro]

Thanks for your reply. Unfortunately, it doesn't seem to work. For instance, if you apply it to the following matrix, it doesn't give the correct results for matrix(:,1) == 3... and 4 and so on.

1	0
1	0
1	0
1	0
1	1
1	1
1	1
1	2
1	2
1	2
1	2
1	2
1	2
1	3
1	4
1	4
1	5
1	7
1	7
1	7
1	7
1	8
1	9
1	9
1	10
1	11
1	11
1	12
1	12
1	13
1	13
1	14
1	14
1	14
1	14
1	14
1	14
1	14
1	14
1	15
1	15
1	16
1	16
1	16
1	16
1	16
1	16
1	16
1	16
1	17
1	17
1	18
1	18
1	18
1	18
1	18
1	18
1	18
1	19
1	19
1	19
1	19
1	19
1	20
1	20
1	21
1	21
1	21
1	21
1	21
2	0
2	0
2	0
2	0
2	0
2	0
2	0
2	0
2	0
2	0
2	0
2	0
2	0
2	0
2	0
2	0
2	0
2	0
2	0
2	0
2	0
2	0
2	0
2	0
2	0
2	0
2	0
2	0
2	0
2	0
2	0
2	1
2	1
2	2
2	2
2	2
2	2
2	2
2	2
2	3
2	3
2	3
2	4
2	5
2	6
2	7
2	7
2	7
2	7
2	7
2	8
2	8
2	9
2	10
2	10
2	11
2	11
2	11
2	11
2	11
2	11
2	11
2	11
2	12
2	12
2	13
2	13
2	14
2	14
2	14
3	0
3	0
3	0
3	0
3	0
3	1
3	1
3	2
3	2
3	2
3	2
3	2
3	2
3	2
3	3
3	4
3	4
3	5
3	6
3	7
3	7
3	7
3	7
3	7
3	7
3	7
3	7
3	8
3	8
3	9
3	9
3	10
3	10
3	11
3	11
3	11
3	11
3	11
3	11
3	11
3	12
3	12
3	12
3	13
3	13
3	14
3	14
3	15
3	15
3	15
3	15
3	15
3	16
3	17
3	17
3	17
3	17
3	17
3	17
3	17
3	18
3	18
3	18
3	18
3	18
3	19
3	19
3	19
3	20
3	21
4	0
4	0
4	0
4	0
4	0
4	0
4	0
4	0
4	0
4	0
4	0
4	0
4	0
4	0
4	0
4	0
4	0
4	0
4	0
4	0
4	0
4	0
4	0
4	0
4	1
4	1
4	1
4	1
4	1
4	1
4	1
4	2
4	2
4	2
4	2
4	2
4	2
4	2
4	3
4	3
4	4
4	5
4	6
4	7
4	7
4	7
4	7
4	7
4	8
4	8
4	8
4	9
4	9
4	9
4	10
4	10
4	10
4	10
4	10
4	11
4	11
4	11
4	11
4	11
4	11
4	11
4	11
4	11
4	11
4	11
5	0
5	0
5	0
5	0
5	0
5	1
5	1
5	2
5	2
5	3
5	3
5	3
5	4
5	4
5	4
5	4
5	4
5	4
5	4
5	4
5	4
5	4
5	4
5	5
5	6
5	6
5	7
5	7
5	8
5	9
5	9
5	10
5	10
5	10
5	10
5	10
5	10
5	10
5	10
5	11
5	11
5	11
5	11
5	11
5	11
5	12
5	12
5	13
5	13
5	14
5	14
5	15
5	15
5	15
5	15
5	16
5	16
5	16
5	16
5	16
5	16
5	16
5	16
5	16
5	17
5	17
5	18
5	18
5	19
5	19
6	0
6	0
6	0
6	0
6	0
6	0
6	0
6	0
6	0
6	0
6	0
6	0
6	0
6	0
6	0
6	0
6	1
6	1
6	2
6	2
6	2
6	2
6	2
6	2
6	2
6	2
6	2
6	2
6	2
6	2
6	2
6	2
6	2
6	2
6	2
6	2
6	2
6	2
6	2
6	2
6	3
6	3
6	4
6	5
6	6
6	7
6	7
6	8
6	8
6	9
6	9
6	9
6	9
6	10
6	10
6	11
6	11
6	11
6	11
6	11
6	11
6	11
6	12
6	12
6	13
6	13
6	13
6	13
6	13
6	14
7	0
7	0
7	1
7	1
7	2
7	2
7	3
7	4
7	4
7	4
7	5
7	6
7	6
7	7
7	7
7	7
7	7
7	7
7	7
7	7
7	7
7	8
7	8
7	8
7	9
7	9
7	9
7	9
7	9
7	9
7	9
7	9
7	9
7	9
7	9
7	9
7	9
7	9
7	9
7	10
7	11
7	11
7	11
7	11
7	11
7	12
7	12
7	13
7	13
7	13
7	13
7	14
7	15
7	15
7	15
7	15
7	16
7	16
7	16
7	17
7	17
7	17
7	17
7	17
7	17
7	17
7	17
7	17
7	17
7	17
8	0
8	0
8	0
8	0
8	0
8	0
8	0
8	0
8	0
8	0
8	0
8	0
8	0
8	0
8	0
8	0
8	0
8	0
8	0
8	1
8	1
8	2
8	2
8	2
8	3
8	3
8	4
8	4
8	4
8	4
8	4
8	4
8	5
8	6
8	6
8	6
8	6
8	7
8	7
8	7
8	7
8	7
8	7
8	7
8	8
8	8
8	9
8	9
8	10
8	10
8	10
8	10
8	10
8	10
8	11
8	11
8	11
8	12
8	12
8	13
8	13
8	14
8	14
8	14
8	15
8	15
8	16
8	16
8	16
8	16
9	0
9	0
9	0
9	0
9	0
9	0
9	0
9	0
9	1
9	1
9	2
9	2
9	2
9	3
9	3
9	4
9	4
9	4
9	4
9	4
9	4
9	4
9	4
9	5
9	6
9	6
9	6
9	6
9	6
9	6
9	6
9	6
9	6
9	7
9	7
9	7
9	8
9	8
9	8
9	8
9	9
9	9
9	9
9	10
9	10
9	11
9	11
9	12
9	13
9	13
9	14
9	14
9	14
9	14
9	14
9	14
9	14
9	14
9	14
9	14
9	14
9	15
9	15
9	15
9	16
9	16
9	16
9	16
9	17
9	17
10	0
10	0
10	0
10	0
10	0
10	0
10	0
10	0
10	0
10	0
10	0
10	0
10	0
10	0
10	0
10	0
10	0
10	0
10	0
10	0
10	0
10	0
10	0
10	1
10	1
10	2
10	2
10	2
10	2
10	2
10	3
10	3
10	4
10	4
10	4
10	4
10	4
10	4
10	4
10	4
10	4
10	4
10	4
10	4
10	4
10	4
10	5
10	6
10	6
10	6
10	7
10	7
10	7
10	7
10	7
10	7
10	7
10	8
10	8
10	9
10	9
10	10
10	10
10	11
10	12
10	12
10	13
10	13
10	14
10	14
11	0
11	0
11	0
11	1
11	2
11	2
11	2
11	3
11	4
11	4
11	4
11	5
11	7
11	7
11	7
11	7
11	7
11	8
11	8
11	8
11	9
11	9
11	9
11	9
11	9
11	9
11	9
11	9
11	9
11	9
11	9
11	9
11	9
11	10
11	10
11	10
11	10
11	11
11	11
11	12
11	12
11	13
11	13
11	13
11	13
11	14
11	14
11	15
11	15
11	16
11	16
11	17
11	17
11	17
11	18
11	18
11	19
11	19
11	20
11	20
11	21
11	21
11	21
11	22
11	23
11	23
11	23
11	23
11	23
11	23
12	0
12	0
12	0
12	0
12	0
12	0
12	0
12	0
12	0
12	0
12	0
12	0
12	0
12	0
12	0
12	0
12	0
12	1
12	1
12	2
12	2
12	2
12	2
12	2
12	2
12	2
12	2
12	3
12	3
12	4
12	4
12	4
12	4
12	5
12	6
12	7
12	8
12	8
12	9
12	10
12	10
12	11
12	11
12	11
12	12
12	12
12	12
12	12
12	13
12	13
12	13
12	13
12	14
12	14
12	15
12	15
12	15
12	16
12	16
12	16
12	16
12	16
12	16
12	17
12	17
12	17
12	17
12	18
12	18
12	19
13	0
13	0
13	0
13	0
13	0
13	0
13	0
13	1
13	2
13	2
13	2
13	3
13	3
13	4
13	4
13	4
13	5
13	6
13	7
13	7
13	7
13	7
13	8
13	9
13	9
13	10
13	10
13	11
13	11
13	11
13	12
13	12
13	12
13	12
13	12
13	12
13	12
13	12
13	13
13	13
13	13
13	13
13	14
13	14
13	15
13	15
13	16
13	16
13	16
13	16
13	17
13	17
13	17
13	18
13	18
13	18
13	19
13	19
13	19
13	19
13	20
13	20
13	20
13	21
13	21
13	21
13	21
13	21
13	21
13	21
14	0
14	0
14	0
14	0
14	0
14	0
14	0
14	0
14	0
14	0
14	0
14	0
14	0
14	0
14	0
14	1
14	1
14	2
14	2
14	2
14	2
14	2
14	2
14	2
14	2
14	2
14	2
14	2
14	2
14	2
14	2
14	2
14	2
14	2
14	2
14	2
14	2
14	2
14	2
14	2
14	2
14	2
14	2
14	2
14	2
14	3
14	3
14	3
14	4
14	4
14	5
14	6
14	7
14	8
14	8
14	8
14	8
14	8
14	9
14	10
14	10
14	11
14	12
14	12
14	12
14	12
14	13
14	13
14	13
14	13
15	0
15	0
15	0
15	0
15	0
15	0
15	0
15	0
15	0
15	0
15	1
15	2
15	2
15	2
15	2
15	3
15	3
15	4
15	4
15	5
15	6
15	6
15	7
15	7
15	7
15	8
15	9
15	9
15	10
15	10
15	10
15	11
15	11
15	11
15	11
15	11
15	12
15	12
15	12
15	12
15	12
15	12
15	13
15	13
15	14
15	14
15	15
15	15
15	15
15	15
15	15
15	15
15	15
15	15
15	16
15	17
15	17
15	17
15	17
15	17
15	18
15	18
15	18
15	18
15	18
15	19
15	19
15	20
15	20
15	20
16	0
16	0
16	0
16	0
16	0
16	0
16	1
16	1
16	2
16	2
16	2
16	2
16	2
16	2
16	2
16	2
16	2
16	2
16	2
16	2
16	2
16	2
16	2
16	2
16	2
16	2
16	3
16	3
16	4
16	4
16	4
16	4
16	4
16	5
16	6
16	7
16	7
16	8
16	8
16	9
16	9
16	9
16	10
16	10
16	11
16	11
16	12
16	12
16	12
16	13
16	13
16	13
16	13
16	14
16	14
16	14
16	14
16	15
16	16
16	16
16	17
16	17
16	17
16	18
16	18
16	18
16	18
16	18
16	19
16	20

[Neuro]

I found the problem. the last 5 digits on column 2 have to be defined every time based on the integer selected on column 2. For instance, if this is the code:

nnz(matrix(:,1) == 10 & matrix(:,2) >= col2_vals(end-4));

Then, those last 5 numbers in column 2 must be determined for the last 5 numbers for the vector that has number 10 in column 1.

[Voss]

idx = matrix(:,1) == 10;
col2_vals = unique(matrix(idx,2)); % now: unique values of column 2 where column 1 is 10
nnz(matrix(idx,2) >= col2_vals(end-4));

[Neuro]

Thanks @Benjamin This solves my problem! :)

Answer 2

[David Hill]

r=unique(matrix(:,2));
r=r(end-4:end);
n=nnz(matrix(:,1)==10&ismember(matrix(:,2),r));

[Neuro]

Thanks for the help. Unfortunately, it doesn't work. For instance, if I try:

r = unique(matrix(:,2));

r = r(end-4:end);

result = nnz(matrix(:,1) == 2 & ismember(matrix(:,2),r));

It gives me incorrect results if the matrix were the one I copy-pasted below.

[David Hill]

r=unique(matrix(matrix(:,1)==10,2));
r=r(end-4:end);
n=nnz(matrix(:,1)==10&ismember(matrix(:,2),r));

[Neuro]

Thanks @David Hill, but it gives me an error message:

Error using unique (line 117)

Invalid input. Valid flags are 'rows', 'first', 'last', 'stable', 'sorted', 'legacy'.