# Examples

## Sample notebooks

Here you can find simple examples on toy datasets to quickly explore what Evidently can do right out of the box. Each example shows how to create a default Evidently dashboard, a JSON profile and an HTML report.

| Report                                                | Jupyter notebook                                                                                                                                    | Colab notebook                                                                    | Data source                                                                            |
| ----------------------------------------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------- | --------------------------------------------------------------------------------- | -------------------------------------------------------------------------------------- |
| Data Drift + Categorical Target Drift (Multiclass)    | [link](https://github.com/evidentlyai/evidently/blob/main/examples/sample_notebooks/multiclass_target_and_data_drift_iris.ipynb)                    | [link](https://colab.research.google.com/drive/1Dd6ZzIgeBYkD_4bqWZ0RAdUpCU0b6Y6H) | Iris plants sklearn.datasets                                                           |
| Data Drift + Categorical Target Drift (Binary)        | [link](https://github.com/evidentlyai/evidently/blob/main/examples/sample_notebooks/binary_target_and_data_drift_breast_cancer.ipynb)               | [link](https://colab.research.google.com/drive/1gpzNuFbhoGc4-DLAPMJofQXrsX7Sqsl5) | Breast cancer sklearn.datasets                                                         |
| Data Drift + Numerical Target Drift                   | [link](https://github.com/evidentlyai/evidently/blob/main/examples/sample_notebooks/numerical_target_and_data_drift_california_housing.ipynb)       | [link](https://colab.research.google.com/drive/1TGt-0rA7MiXsxwtKB4eaAGIUwnuZtyxc) | California housing sklearn.datasets                                                    |
| Regression Performance                                | [link](https://github.com/evidentlyai/evidently/blob/main/examples/sample_notebooks/regression_performance_bike_sharing_demand.ipynb)               | [link](https://colab.research.google.com/drive/1ONgyDXKMFyt9IYUwLpvfxz9VIZHw-qBJ) | Bike sharing UCI: [link](https://archive.ics.uci.edu/ml/datasets/bike+sharing+dataset) |
| Classification Performance (Multiclass)               | [link](https://github.com/evidentlyai/evidently/blob/main/examples/sample_notebooks/classification_performance_multiclass_iris.ipynb)               | [link](https://colab.research.google.com/drive/1pnYbVJEHBqvVmHUXzG-kw-Fr6PqhzRg3) | Iris plants sklearn.datasets                                                           |
| Probabilistic Classification Performance (Multiclass) | [link](https://github.com/evidentlyai/evidently/blob/main/examples/sample_notebooks/probabilistic_classification_performance_multiclass_iris.ipynb) | [link](https://colab.research.google.com/drive/1UkFaBqOzBseB_UqisvNbsh9hX5w3dpYS) | Iris plants sklearn.datasets                                                           |
| Classification Performance (Binary)                   | [link](https://github.com/evidentlyai/evidently/blob/main/examples/sample_notebooks/classification_performance_breast_cancer.ipynb)                 | [link](https://colab.research.google.com/drive/1b2kTLUIVJkKJybYeD3ZjpaREr_9dDTpz) | Breast cancer sklearn.datasets                                                         |
| Probabilistic Classification Performance (Binary)     | [link](https://github.com/evidentlyai/evidently/blob/main/examples/sample_notebooks/probabilistic_classification_performance_breast_cancer.ipynb)   | [link](https://colab.research.google.com/drive/1sE2H4mFSgtNe34JZMAeC3eLntid6oe1g) | Breast cancer sklearn.datasets                                                         |
| Data Quality                                          | [link](https://github.com/evidentlyai/evidently/blob/main/examples/sample_notebooks/data_quality_bike_sharing_demand.ipynb)                         | [link](https://colab.research.google.com/drive/1XDxs4k2wNHU9Xbxb9WI2rOgMkZFavyRd) | Bike sharing UCI: [link](https://archive.ics.uci.edu/ml/datasets/bike+sharing+dataset) |

## Tutorials

To better understand potential use cases for Evidently (such as model evaluation and monitoring), refer to the **detailed tutorials** accompanied by the blog posts.

| Title                                                            | Jupyter notebook                                                                                                                     | Colab notebook                                                                    | Blog post                                                                                                                                           | Data source                                                                                            |
| ---------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------ | --------------------------------------------------------------------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------ |
| Monitor production model decay                                   | [link](https://github.com/evidentlyai/evidently/blob/main/examples/data_stories/bicycle_demand_monitoring.ipynb)                     | [link](https://colab.research.google.com/drive/1xjAGInfh_LDenTxxTflazsKJp_YKmUiD) | [How to break a model in 20 days. A tutorial on production model analytics.](https://evidentlyai.com/blog/tutorial-1-model-analytics-in-production) | Bike sharing UCI: [link](https://archive.ics.uci.edu/ml/datasets/bike+sharing+dataset)                 |
| Compare two models before deployment                             | [link](https://github.com/evidentlyai/evidently/blob/main/examples/data_stories/ibm_hr_attrition_model_validation.ipynb)             | [link](https://colab.research.google.com/drive/12AyNh3RLSEchNx5_V-aFJ1_EnLIKkDfr) | [What Is Your Model Hiding? A Tutorial on Evaluating ML Models.](https://evidentlyai.com/blog/tutorial-2-model-evaluation-hr-attrition)             | HR Employee Attrition: [link](https://www.kaggle.com/pavansubhasht/ibm-hr-analytics-attrition-dataset) |
| Evaluate and visualize historical drift                          | [link](https://github.com/evidentlyai/evidently/blob/main/examples/integrations/mlflow_logging/historical_drift_visualization.ipynb) | [link](https://colab.research.google.com/drive/12AyNh3RLSEchNx5_V-aFJ1_EnLIKkDfr) | [How to detect, evaluate and visualize historical drifts in the data.](https://evidentlyai.com/blog/tutorial-3-historical-data-drift)               | Bike sharing UCI: [link](https://archive.ics.uci.edu/ml/datasets/bike+sharing+dataset)                 |
| Create a custom report (tab) with PSI widget for drift detection | [link](https://github.com/evidentlyai/evidently/blob/main/examples/data_stories/california_housing_custom_PSI_widget_and_tab.ipynb)  | [link](https://colab.research.google.com/drive/1FuXId8p-lCP9Ho_gHeqxAdoxHRuvY9d0) | ---                                                                                                                                                 | California housing sklearn.datasets                                                                    |

## Integrations

To see how to integrate Evidently in your prediction pipelines and use it with other tools, refer to the **integrations**.

{% content-ref url="integrations" %}
[integrations](https://docs-old.evidentlyai.com/v0.1.57/integrations)
{% endcontent-ref %}