How to group different sensor's data based on their similarities?

I have multiple sensors’ data over one year. I wanted to know if there are any unsupervised methods to divide and group sensors’ data that have close characteristics/behavior.

For example, if I have electricity consumption data for 1000 buildings stored in a table with 1000 columns, how I can divide or cluster these columns such that those that have close characteristics are placed in a specific group?

I appreciate your time in advance.

Thank you.

Time D1 D2 D3 D4 D5 Dn

____________________ _______ _______ _______ _______ _______ .... _______

01-Jan-2020 00:00:00 2.9675 32.502 23.454 3.5067 . .

01-Jan-2020 00:01:00 -6.298 -96.793 -64.711 -9.9581 . .

01-Jan-2020 00:02:00 -5.5285 -75.355 -54.29 -8.215 . .

01-Jan-2020 00:03:00 -1.4514 -34.475 -24.879 -3.468 . .

01-Jan-2020 00:04:00 3.9736 66.112 42.284 6.639 . .

01-Jan-2020 00:05:00 3.1481 64.577 41.262 6.9614 . .

01-Jan-2020 00:06:00 -44.042 -699.24 -414.33 -75.339 . .

01-Jan-2020 00:07:00 4.4172 69.015 37.355 6.6763 . .

01-Jan-2020 00:08:00 23.509 284.8 186.89 32.597 . .

01-Jan-2020 00:09:00 17.329 214.71 124.45 20.634 . .

[dpb]

Well, I guess that depends on what your definition of "group" or "cluster" really means...you can address the variables as

tTable(:,1:2:end)

or

tTable(:,"D"+[1:2:size(tmp,2)])

that would address D1, D3, D5, ... to whatever number of columns were in the timetable tTable assumig the same naming convention.

But, that still leaves unanswered just what you really want/mean...

[smoa]

Thank you dpb for your comment. I rephrased my post and I hope it makes more sense now.

What I meant by grouping is that if I have a table with 1000 columns, how I can separate columns that have close characteristics or behavior. For example, if I have electricity consumption of 1000 buildings (buildings can be different in terms of size, application, etc.), is there any unsupervised method that can look at all datasets and divide columns into certain groups such as group-1, group-2, …group-n?

[dpb]

The Statistics/Machine Learning TB has several cluster analysis tools you could try.

I've not researched nor used the ML Neural Net TB enough to know its capabilities in the arena.

[smoa]

Sure, I would look at them.

Thank you for suggestions.

[Walter Roberson]

principal component analysis, and cross-correlation might help

[smoa]

Thank you @Walter Roberson for your suggestions. I will try corr(x) to see their correlation and perhaps find those that are close to each other.