Evidently

- Supported custom list of Widgets for Tabs in Dashboard with help of verbose_level and include_widgets parameters
- Added parameter verbose_level: 0 - to create a Tab with the shortest list of Widgets, 1 - to create a full Tab
- Added parameter include_widgets : ["Widget Name 1", "Widget Name 2", etc]. This parameter overwrites verbose_level (if both are specified) and allows to set a custom list of Widgets
- Added Tab.list_widgets() method to list all the available Widgets for the current Tab
- Created Options entity to specify Widgets and Tabs customisable settings
- Created ColumnMapping entity instead column_mapping python dictionary

Removed PyYAML~=6.0 from the dependencies

- Added flake8 for code style checks
- Added mypy for object types checks
- Improved code style
- Added contribution guide

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.

* 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')

- 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