* Capture an additional exception type (`KeyError`) in recently adjusted `get_baseline_data` and `get_reporting_data` methods.
2.5.0
-----
* Add parameters to `get_baseline_data` and `get_reporting_data` to help make these methods a bit more correct for billing data. * Preserve nulls properly in `as_freq`. * Update jupyter version to be compatible with latest tornado version.
2.4.0
-----
* Fix for bug that occasionally leads to `LinAlgError: SVD did not converge` error when fitting caltrack hourly models by addressing multi-collinearity when only a single occupancy mode is detected
2.3.1
-----
* Hot fix for bug that occasionally leads to `LinAlgError: SVD did not converge` error when fitting caltrack hourly models by converting the weights from `np.float64` ton `np.float32`.
2.3.0
-----
* Fix bug where the model prediction includes features in the last row that should be null. * Fix in `transform.get_baseline_data` and `transform.get_reporting_data` to enable pulling a full year of data even with irregular billing periods
2.2.10
------
* Added option in `transform.as_freq` to handle instantaneous data such as temperature and other weather variables.