User guide

Interested in learning more about energy_analysis_toolbox ? Check the notebooks below to get started on specific topics, or head over to the API reference for a complete overview of the package.

Common use cases of |eat|

• Resampling timeseries using eat
  • Resampling power data
    • Example data
    • Upsampling
    • Downsampling
    • Changing the resampling default arguments
    • Conclusion about power resampling
  • Resampling Energy data
    • Conclusion about energy resampling
  • Resampling energy index data
  • Resampling temperature data
    • Example data
    • Simple over or sub-sampling
• Accessing the energy_analysis_toolbox from the Pandas API
• On a Series
  • Transforming the power to energy
  • Resampling to a fixed frequency
  • Detective interval with power over a threshold
  • Filling data holes
• Using eat for thermosensitivity analysis: Real data
• Thermo-sensitivity analysis
  • Modeling the Weekly energy
  • Conclusion of Weekly Analysis
• Modeling the Daily energy
• Adding the school holidays
  • Conclusion of Daily Analysis
  • Automatic Day categorisation
  • Conclusion of Automatic Day categorisation
• Conclusion
  • Discussion / Next steps
• Using eat for thermosensitivity analysis: Synthetic data
• Thermo-sensitivity analysis
• Automatic calibration of the degree days model
  • Fitting thermo-sensitivity model
  • Accessing the performance of the calibration
• Automatic detection of the type of thermo sensitivity
• Conclusion
  • Implemented features
  • Discussion
• Categorical thermo-sensitivity
  • Using no category
  • Using Categories
• Automatic detection of the category to use
• Conclusion