Apps Market - Heat Map


In this article you're going to learn how to visualize you're consumption on a thermal matrix using the Heat Map app. 

Contents of this article: 




This external app allows to visualize and analyse consumption data from all our devices through a thermal matrix. Thus, we can visualize hourly our consumption for a selected period, identifying patters.



  • Devices with data. 
  • Install the Heat Map on your account from the Apps market.
  • 15 min, 30 min or daily frequency data.


How does it work?  

  1. Device selector: select the device you want to visualize its consumption in a thermal map. 
  2. Parameter: select which parameter you want to visualize the thermal map
  3. Dates: select the date range indicating from and to dates
  4. Frequency: select the sampling frequency which you are going to visualize the data. This selector will filter the parameters which appear on number 2. 
  5. Type: the application allows specify your own color range for the thermal map (selecting "custom" option) or using the default colors (selecting "thermal" option)
  6. Export data through excel: the app allows to download all the thermal matrix through excel
  7. Legend: legend which shows the color range used to represent the consumption matrix, indicating which colors indicate the maximum values and which colors indicated the minimum values.     


Using the app: Analysis Screen

Once we have filled all the previous gaps and clicked on "update", it will appear 3 different zones showing the obtained results:  

Thermal matrix: it shows the consumption range for each frequency as the range of colours set. In this matrix, it can be obtained which hours of the day represent more consumption and which have a lower consumption. Moving on with the cursor above the graph, we can see the value and the corresponding time stamp.   

Statistics: graph which represents the maximum, minimum, average, median and standard deviation values.

Summary table: summary table where are represented the maximum, minimum, average, median and standard deviation values for each of the daily hours.

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