Rate of change calculation
I've got a dataset (column) which is basic time-series dataset containing the volume of fluid in a vessel with observations every 5 minutes. I want to create a calculation to determine the average per-day rate of change of fluid in the vessel. I've uploaded an example of the raw data The basic idea would be:
Rate of Change = (Average Fluid Volume on Day N) - (Average Fluid Volume on Day N-1)
Thoughts on how I could Beast Mode this?
Comments
-
So I believe the only way you could pull this off would be to create a SQL transform to first group your data and add a previous day volume column.
You could accomplish this with the following two transforms:
SELECT CAST(`Timestamp` AS DATE) AS 'Day', AVG(`Fluid Volume`) AS 'Avg Volume'
FROm testingdata
GROUP BY CAST(`Timestamp` AS DATE)And then:
SELECT CAST(a.`Timestamp` AS DATE) AS 'Day', AVG(a.`Fluid Volume`) AS 'Avg Volume', (SELECT b.`Avg Volume` FROM transform_data_1 as b WHERE b.`Day` = DATE_SUB(CAST(a.`Timestamp` AS DATE), INTERVAL 1 DAY) ) AS 'Previous Volume'
FROm testingdata AS a
GROUP BY CAST(a.`Timestamp` AS DATE)That will give you Day, Avg Volume, Previous Volume.
From there you can subtract Avg V- Prev V and then create your average rate of change Beast Mode.
Let me know if you have any other questions,
ValiantSpur
**Please mark "Accept as Solution" if this post solves your problem
**Say "Thanks" by clicking the "heart" in the post that helped you.1
Categories
- 10.6K All Categories
- 8 Connect
- 918 Connectors
- 250 Workbench
- 477 Transform
- 1.8K Magic ETL
- 69 SQL DataFlows
- 478 Datasets
- 218 Visualize
- 260 Beast Mode
- 2.1K Charting
- 12 Variables
- 19 Automate
- 356 APIs & Domo Developer
- 89 Apps
- 3 Workflows
- 20 Predict
- 5 Jupyter Workspaces
- 15 R & Python Tiles
- 249 Distribute
- 65 Domo Everywhere
- 243 Scheduled Reports
- 21 Manage
- 42 Governance & Security
- 191 Product Ideas
- 1.2K Ideas Exchange
- 11 Community Forums
- 27 Getting Started
- 14 Community Member Introductions
- 55 Community News
- 4.5K Archive