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

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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 . .
  6 Comments
smoa
smoa on 25 Jun 2022
Edited: smoa on 25 Jun 2022
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.

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