Losant documentation says:
“Historical graphs allow for data to be aggregated according to a number of rules (based on time ranges, mathematical functions and the combination of data from multiple sources)”
I Would you like to know which rules apply to this aggregation of data?
For example,
what mathematical functions? What kind of data combination?
Here’s a screenshot showing the configuration of a Time-Series Graph:
The first highlighted field is the Resolution (5 minutes), which controls how often a data point is displayed on the graph. The second highlighted field is the Aggregation, which controls how to combine data points if there are multiple in each 5 minute resolution window. In the above screenshot, I selected Mean, so the data points are averaged together.
The primary purpose of Resolution and Aggregation is to reduce the number of points on the graph. It’s often impossible or impractical to show raw data. For example, if you want to view 30 days worth of data and your device is reporting one per minute, that results in 43,200 data points. That more data than you have pixels to display it, so we need to reduce the data by aggregating multiple data points together.
All of our available aggregations can be found here: https://docs.losant.com/references/aggregations/
Losant University also has a chapter that covers aggregations that I would highly recommend (course 4, chapter 3). Losant University is available here: https://www.losant.com/university
