Evidently

Latest version: v0.6.7

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0.1.30.dev0

Not secure
1. Supported dashboard visualization in Google Colab
2. Supported dashboard visualization in python Pylab
3. Added a parameter mode for dashboard.show(), which can take the following options:
- auto - the default option. Ideally, you will not need to specify the value for mode and use the default. But, if it does not work (in case we failed to determine the environment automatically), consider setting the correct value explicitly.
- nbextention - to show the UI using nbextension. Use this option to display dashboards in jupyter notebooks (should work automatically).
- inline - to insert the UI directly into the cell. Use this option for Google Colab, Kaggle Kernels and Deepnote. For Google Colab this should work automatically, for Kaggle Kernels and Deepnote option should be specified explicitly.

0.1.28.dev0

Not secure
* Supported dashboard visualization in Google Colab
* Supported dashboard visualization in python Pylab
* Added a parameter to switch on pylab visualization model: dashboard.show(mode='pylab')

0.1.27.dev0

Not secure
- Added a way to calculate metrics with moving window
- Added metrics logging to Prometheus
- Added an example of Data Drift Monitoring with Prometheus and Grafana
- Added a config for Data drift dashboard at Grafana

0.1.26.dev0

Not secure
Fix for https://github.com/evidentlyai/evidently/issues/61

0.1.25.dev0

Not secure
- Added the source code for the UI (now it can be built from the source)
- Created utils.py with helper functions
- Added config for Pylint
- Added some unit tests

0.1.23.dev0

Not secure
Added the following options to configure data drift report:
- 'drift_conf_level' confidence level for the individual features (default value = 0.95)
- 'drift_features_share' - share of the drifted features to detect dataset drift (default value = 0.5)
- 'xbins' - the custom bins to plot in the datadrift table
- 'nbinsx' - the custom number of bins to plot in the datadrift table

If share of the features drifted at the 'drift_conf_level' confidence level is higher than the 'drift_features_share' threshold, than Dataset drift will be detected. Otherwise Dataset drift will not be detected.

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