Whole Dataset Drift

.. DO NOT EDIT. .. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY. .. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE: .. "user-guide/general/exporting_results/examples/plot_export_outputs_to_json.py" .. LINE NUMBERS ARE GIVEN BELOW. .. only:: html .. note:: :class: sphx-glr-download-link-note Click :ref:`here ` to download the full example code .. rst-class:: sphx-glr-example-title .. _sphx_glr_user-guide_general_exporting_results_examples_plot_export_outputs_to_json.py: Export Outputs to JSON ********************** In this guide, we will demonstrate how to export the Check's and the Suite's output to JSON format. This enables to use the exported results as a serializeable object that can later be shared or reviewed in other Python scopes, and also enables working with the check's output (name, parameters, result value and result display) not only in a visual manner (e.g. by parsing the output JSON). **Structure:** * `Load Data <#load-data>`__ * `Run a Check <#run-a-check>`__ * `Export Check to JSON <#export-a-check-s-output-checkresult-to-a-json-format>`__ * `Export Suite to JSON <#exporting-a-suite-s-output-suiteresult-to-json>`__ .. GENERATED FROM PYTHON SOURCE LINES 22-24 Load Data ========= .. GENERATED FROM PYTHON SOURCE LINES 24-30 .. code-block:: default from deepchecks.tabular.datasets.classification import iris train_dataset, test_dataset = iris.load_data() model = iris.load_fitted_model() .. GENERATED FROM PYTHON SOURCE LINES 31-33 Run a Check =========== .. GENERATED FROM PYTHON SOURCE LINES 33-39 .. code-block:: default from deepchecks.tabular.checks import WholeDatasetDrift result = WholeDatasetDrift().add_condition_overall_drift_value_less_than( ).run(train_dataset, test_dataset, model) .. GENERATED FROM PYTHON SOURCE LINES 40-41 Observe CheckResult Display and Value .. GENERATED FROM PYTHON SOURCE LINES 41-44 .. code-block:: default result .. raw:: html

Whole Dataset Drift

.. GENERATED FROM PYTHON SOURCE LINES 45-47 .. code-block:: default result.value .. rst-class:: sphx-glr-script-out .. code-block:: none {'domain_classifier_auc': 0.4545454545454546, 'domain_classifier_drift_score': 0, 'domain_classifier_feature_importance': {'petal length (cm)': 1.0, 'sepal length (cm)': 0.0, 'sepal width (cm)': 0.0, 'petal width (cm)': 0.0}} .. GENERATED FROM PYTHON SOURCE LINES 48-60 Export a Check's Output (CheckResult) to a JSON Format ====================================================== Serialization of the output to a JSON format is possible using the ``to_json`` function. This function takes the check outputs and serializes it to a JSON string. The format of the check's output json includes all info required to reconstruct the check run and it's output: it's name, the parameters the check receives, one sentence summary of the check's purpose, it's result value and a json of the data relevant for displaying the check's outputs. See Check JSON Structure ------------------------ .. GENERATED FROM PYTHON SOURCE LINES 60-65 .. code-block:: default from deepchecks.core import CheckResult help(CheckResult.to_json) .. rst-class:: sphx-glr-script-out .. code-block:: none Help on function to_json in module deepchecks.core.check_result: to_json(self, with_display: bool = True, **kwargs) -> str Serialize result into a json string. Returned JSON string will have next structure: >> class CheckResultMetadata(TypedDict): >> type: str >> check: CheckMetadata >> value: Any >> header: str >> conditions_results: List[Dict[Any, Any]] >> display: List[Dict[str, Any]] >> class CheckMetadata(TypedDict): >> name: str >> params: Dict[Any, Any] >> summary: str Parameters ---------- with_display : bool whethere to include display items or not Returns ------- str .. GENERATED FROM PYTHON SOURCE LINES 66-70 .. code-block:: default # get output JSON serialized_output = result.to_json() .. GENERATED FROM PYTHON SOURCE LINES 71-77 .. code-block:: default import json # note - conditions_table key exists only if there are conditions that were defined on check json.loads(serialized_output).keys() .. rst-class:: sphx-glr-script-out .. code-block:: none dict_keys(['type', 'check', 'header', 'value', 'conditions_results', 'display']) .. GENERATED FROM PYTHON SOURCE LINES 78-80 Observe JSON Output ------------------- .. GENERATED FROM PYTHON SOURCE LINES 80-83 .. code-block:: default json.loads(serialized_output) .. rst-class:: sphx-glr-script-out .. code-block:: none {'type': 'CheckResult', 'check': {'name': 'Whole Dataset Drift', 'params': {'n_top_columns': 3, 'min_feature_importance': 0.05, 'max_num_categories_for_display': 10, 'show_categories_by': 'largest_difference', 'sample_size': 10000, 'random_state': 42, 'test_size': 0.3, 'min_meaningful_drift_score': 0.05}, 'summary': ' Calculate drift between the entire train and test datasets using a model trained to distinguish between them. Read More...'}, 'header': 'Whole Dataset Drift', 'value': {'domain_classifier_auc': {'dtype': 'float64', 'value': 0.4545454545454546}, 'domain_classifier_drift_score': 0, 'domain_classifier_feature_importance': {'petal length (cm)': 1.0, 'sepal length (cm)': 0.0, 'sepal width (cm)': 0.0, 'petal width (cm)': 0.0}}, 'conditions_results': [{'Status': 'PASS', 'Condition': 'Drift value is less than 0.25', 'More Info': 'Found drift value of: 0, corresponding to a domain classifier AUC of: 0.45'}], 'display': []} .. GENERATED FROM PYTHON SOURCE LINES 84-88 Display the CheckResult Output from a JSON ------------------------------------------ The serialized JSON can be used to reproduce the run in other Python scopes, by using the ``from_json`` function .. GENERATED FROM PYTHON SOURCE LINES 88-94 .. code-block:: default from deepchecks.utils.json_utils import from_json from_json(serialized_output) .. raw:: html

Whole Dataset Drift

.. GENERATED FROM PYTHON SOURCE LINES 95-99 Exporting a Suite's Output (SuiteResult) to JSON ================================================ Run Suite and Save to JSON -------------------------- .. GENERATED FROM PYTHON SOURCE LINES 99-104 .. code-block:: default from deepchecks.tabular.suites import full_suite suite = full_suite() .. GENERATED FROM PYTHON SOURCE LINES 105-109 .. code-block:: default suite_result = suite.run(train_dataset=train_dataset, test_dataset=test_dataset, model=model) suite_json = suite_result.to_json() .. rst-class:: sphx-glr-script-out .. code-block:: none Full Suite: | | 0/36 [Time: 00:00] Full Suite: |# | 1/36 [Time: 00:00, Check=Train Test Performance] Full Suite: |#### | 4/36 [Time: 00:00, Check=Train Test Prediction Drift] Full Suite: |###### | 6/36 [Time: 00:01, Check=Weak Segments Performance] Full Suite: |#################### | 20/36 [Time: 00:01, Check=Train Test Samples Mix] Full Suite: |########################## | 26/36 [Time: 00:02, Check=Special Characters] Full Suite: |################################## | 34/36 [Time: 00:02, Check=Feature Label Correlation] .. GENERATED FROM PYTHON SOURCE LINES 110-112 Observe Suite's JSON Strucutre ------------------------------ .. GENERATED FROM PYTHON SOURCE LINES 112-117 .. code-block:: default from deepchecks.core import SuiteResult help(SuiteResult.to_json) .. rst-class:: sphx-glr-script-out .. code-block:: none Help on function to_json in module deepchecks.core.suite: to_json(self, with_display: bool = True, **kwargs) Return check result as json. Parameters ---------- with_display : bool, default True whether to include serialized `SuiteResult.display` items into the output or not Returns ------- str .. GENERATED FROM PYTHON SOURCE LINES 118-119 Suite name: .. GENERATED FROM PYTHON SOURCE LINES 119-122 .. code-block:: default json.loads(suite_json)['name'] .. rst-class:: sphx-glr-script-out .. code-block:: none 'Full Suite' .. GENERATED FROM PYTHON SOURCE LINES 123-124 Results is an array of CheckResult JSON's, let's see how many checks ran in suite: .. GENERATED FROM PYTHON SOURCE LINES 124-127 .. code-block:: default len(json.loads(suite_json)['results']) .. rst-class:: sphx-glr-script-out .. code-block:: none 55 .. GENERATED FROM PYTHON SOURCE LINES 128-131 Lets observe a specific check's output, which is similar to the `Check output's JSON Structure <#export-a-check-s-output-checkresult-to-a-json-format>`__ we saw before for each check .. GENERATED FROM PYTHON SOURCE LINES 131-133 .. code-block:: default json.loads(suite_json)['results'][0] .. rst-class:: sphx-glr-script-out .. code-block:: none {'type': 'CheckResult', 'check': {'name': 'Train Test Performance', 'params': {'reduce': 'mean'}, 'summary': 'Summarize given model performance on the train and test datasets based on selected scorers. Read More...'}, 'header': 'Train Test Performance', 'value': '[{"Dataset":"Train","Class":0,"Metric":"F1","Value":1.0,"Number of samples":37},{"Dataset":"Train","Class":1,"Metric":"F1","Value":1.0,"Number of samples":37},{"Dataset":"Train","Class":2,"Metric":"F1","Value":1.0,"Number of samples":38},{"Dataset":"Train","Class":0,"Metric":"Precision","Value":1.0,"Number of samples":37},{"Dataset":"Train","Class":1,"Metric":"Precision","Value":1.0,"Number of samples":37},{"Dataset":"Train","Class":2,"Metric":"Precision","Value":1.0,"Number of samples":38},{"Dataset":"Train","Class":0,"Metric":"Recall","Value":1.0,"Number of samples":37},{"Dataset":"Train","Class":1,"Metric":"Recall","Value":1.0,"Number of samples":37},{"Dataset":"Train","Class":2,"Metric":"Recall","Value":1.0,"Number of samples":38},{"Dataset":"Test","Class":0,"Metric":"F1","Value":1.0,"Number of samples":13},{"Dataset":"Test","Class":1,"Metric":"F1","Value":0.9285714286,"Number of samples":13},{"Dataset":"Test","Class":2,"Metric":"F1","Value":0.9090909091,"Number of samples":12},{"Dataset":"Test","Class":0,"Metric":"Precision","Value":1.0,"Number of samples":13},{"Dataset":"Test","Class":1,"Metric":"Precision","Value":0.8666666667,"Number of samples":13},{"Dataset":"Test","Class":2,"Metric":"Precision","Value":1.0,"Number of samples":12},{"Dataset":"Test","Class":0,"Metric":"Recall","Value":1.0,"Number of samples":13},{"Dataset":"Test","Class":1,"Metric":"Recall","Value":1.0,"Number of samples":13},{"Dataset":"Test","Class":2,"Metric":"Recall","Value":0.8333333333,"Number of samples":12}]', 'conditions_results': [{'Status': 'FAIL', 'Condition': 'Train-Test scores relative degradation is less than 0.1', 'More Info': '2 scores failed. Found max degradation of 16.67% for metric Recall and class 2.'}], 'display': [{'type': 'plotly', 'payload': '{"data":[{"alignmentgroup":"True","bingroup":"x","histfunc":"sum","hovertemplate":"Dataset=Train
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