sql - Moving Average based on Timestamps in PostgreSQL

Question

I wanted to perform moving average through timestamps. I have two columns: Temperature and timestamps (time-date) and I want to perform the moving average based on every 15 minutes successive temperature observations. In other words, selecting data to perform the average based on 15 minutes time interval. Moreover, it is possible to have different number of observations for different time sequences. I meant all the window sizes are equal (15 minutes) but it is possible to have different number of observations in each window. For example: For a first window we have to calculate the average of n observation and for second window calculate the average of the observation for n+5 observation.

Data Sample:

ID   Timestamps          Temperature
1    2007-09-14 22:56:12 5.39
2    2007-09-14 22:58:12 5.34
3    2007-09-14 23:00:12 5.16
4    2007-09-14 23:02:12 5.54
5    2007-09-14 23:04:12 5.30
6    2007-09-14 23:06:12 5.20
7    2007-09-14 23:10:12 5.39
8    2007-09-14 23:12:12 5.34
9    2007-09-14 23:20:12 5.16
10   2007-09-14 23:24:12 5.54
11   2007-09-14 23:30:12 5.30
12   2007-09-14 23:33:12 5.20
13   2007-09-14 23:40:12 5.39
14   2007-09-14 23:42:12 5.34
15   2007-09-14 23:44:12 5.16
16   2007-09-14 23:50:12 5.54
17   2007-09-14 23:52:12 5.30
18   2007-09-14 23:57:12 5.20

Main Challenges:

How I can learn the code to discriminate every 15 minute while there are not exact 15 minutes time intervals due to different sampling frequency.

Answer 1

You can join your table with itself:

select l1.id, avg( l2.Temperature )
from l l1
inner join l l2 
   on l2.id <= l1.id and
      l2.Timestamps + interval '15 minutes' > l1.Timestamps
group by l1.id
order by id
;

Results:

| ID |            AVG |
-----------------------
|  1 |           5.39 |
|  2 |          5.365 |
|  3 | 5.296666666667 |
|  4 |         5.3575 |
|  5 |          5.346 |
|  6 | 5.321666666667 |
|  7 | 5.331428571429 |

Notice: Only 'hard work' is made. You should join result with original table or append new columns to query. I don't know your final query needed. Adapt this solution or ask for more help.