itp
sensor_data from PostgreSQL. Follow the instructions to get started. Document the steps you took to create the database. A screenshot of the terminal or cmd prompt is fine. Make sure your database includes the person and device tables. Optionally create some views.To create an sqlite database for the itp sensor data I used the following steps:
Check to make sure that the data is correctly imported
sqlite> SELECT * FROM sensor_data LIMIT 10;
device measurement reading recorded_at
---------- ----------- ------- -------------------
rootcellar humidity 67 2019-11-28 07:46:28
rootcellar temperature 44.1 2019-11-28 07:46:28
basement humidity 53 2019-11-28 07:46:34
basement temperature 53.8 2019-11-28 07:46:34
loft humidity 70.8 2019-11-28 07:47:14
loft temperature 41.72 2019-11-28 07:47:14
basement humidity 53 2019-11-28 07:47:45
basement temperature 53.8 2019-11-28 07:47:45
basement humidity 53 2019-11-28 07:48:36
basement temperature 53.8 2019-11-28 07:48:36
Create a view and check the weekly moving average temperature of kitchen.
sqlite> CREATE VIEW kitchen_temps AS SELECT * FROM sensor_data WHERE measurement LIKE 'temperature' AND device LIKE 'kitchen';
sqlite> SELECT *, AVG(reading) OVER(ORDER BY recorded_at ROWS BETWEEN 6 PRECEDING AND CURRENT ROW) as weekly_avg from kitchen_temps LIMIT 10;
device measurement reading recorded_at weekly_avg
------- ----------- ------- ------------------- ----------------
kitchen temperature 73.22 2015-12-26 20:58:28 73.22
kitchen temperature 73.04 2015-12-26 20:59:28 73.13
kitchen temperature 73.04 2015-12-26 21:00:29 73.1
kitchen temperature 73.76 2015-12-26 21:02:31 73.265
kitchen temperature 71.6 2015-12-26 21:03:32 72.932
kitchen temperature 70.16 2015-12-26 21:04:32 72.47
kitchen temperature 69.26 2015-12-26 21:05:33 72.0114285714286
kitchen temperature 68.72 2015-12-26 21:06:33 71.3685714285714
kitchen temperature 68.18 2015-12-26 21:07:34 70.6742857142857
kitchen temperature 67.82 2015-12-26 21:08:34 69.9285714285714