113 roadmap get metrics through sdk and visualise them in jupyter notebook

.env.dev

@@ -5,6 +5,6 @@ APP_NAME_CRON=Whitebox | Development
 DATABASE_URL=postgresql://postgres:postgres@localhost:5432/postgres
 
 VERSION=0.1.0
-METRICS_CRON=*/15 * * * *
+METRICS_CRON=*/3 * * * *
 
 MODEL_PATH=models

descriptive.json

@@ -0,0 +1 @@
+[{"id": "99d7c601-925b-4d58-96b3-8bca2bbdff19", "created_at": "2023-02-09T14:33:00.483453", "updated_at": "2023-02-09T14:33:00.483453", "model_id": "83539c2b-579f-4a2c-b7ba-02d31c9408d8", "timestamp": "2022-12-22T00:00:00", "feature_metrics": {"missing_count": {"sepal length (cm)": 0, "sepal width (cm)": 0, "petal length (cm)": 0, "petal width (cm)": 0, "target": 0}, "non_missing_count": {"sepal length (cm)": 10, "sepal width (cm)": 10, "petal length (cm)": 10, "petal width (cm)": 10, "target": 10}, "mean": {"sepal length (cm)": 5.679999999999999, "sepal width (cm)": 3.1, "petal length (cm)": 3.1799999999999997, "petal width (cm)": 0.97, "target": 0.7}, "minimum": {"sepal length (cm)": 4.8, "sepal width (cm)": 2.5, "petal length (cm)": 1.4, "petal width (cm)": 0.1, "target": 0.0}, "maximum": {"sepal length (cm)": 6.5, "sepal width (cm)": 3.9, "petal length (cm)": 5.6, "petal width (cm)": 2.1, "target": 2.0}, "sum": {"sepal length (cm)": 56.79999999999999, "sepal width (cm)": 31.0, "petal length (cm)": 31.799999999999997, "petal width (cm)": 9.7, "target": 7.0}, "standard_deviation": {"sepal length (cm)": 0.6779052703405954, "sepal width (cm)": 0.408248290463863, "petal length (cm)": 1.8262286579481526, "petal width (cm)": 0.7557924465236618, "target": 0.8232726023485646}, "variance": {"sepal length (cm)": 0.4595555555555558, "sepal width (cm)": 0.16666666666666666, "petal length (cm)": 3.335111111111111, "petal width (cm)": 0.5712222222222223, "target": 0.6777777777777778}}}, {"id": "4a7ca49b-ece6-45ac-a9cc-9560ab72cb73", "created_at": "2023-02-09T14:36:00.531345", "updated_at": "2023-02-09T14:36:00.531345", "model_id": "83539c2b-579f-4a2c-b7ba-02d31c9408d8", "timestamp": "2022-12-23T00:00:00", "feature_metrics": {"missing_count": {"sepal length (cm)": 0, "sepal width (cm)": 0, "petal length (cm)": 0, "petal width (cm)": 0, "target": 0}, "non_missing_count": {"sepal length (cm)": 20, "sepal width (cm)": 20, "petal length (cm)": 20, "petal width (cm)": 20, "target": 20}, "mean": {"sepal length (cm)": 5.819999999999999, "sepal width (cm)": 3.1050000000000004, "petal length (cm)": 3.560000000000001, "petal width (cm)": 1.1300000000000001, "target": 0.9}, "minimum": {"sepal length (cm)": 4.6, "sepal width (cm)": 2.5, "petal length (cm)": 1.4, "petal width (cm)": 0.1, "target": 0.0}, "maximum": {"sepal length (cm)": 7.2, "sepal width (cm)": 3.9, "petal length (cm)": 6.0, "petal width (cm)": 2.1, "target": 2.0}, "sum": {"sepal length (cm)": 116.39999999999999, "sepal width (cm)": 62.10000000000001, "petal length (cm)": 71.20000000000002, "petal width (cm)": 22.6, "target": 18.0}, "standard_deviation": {"sepal length (cm)": 0.7770389138802578, "sepal width (cm)": 0.3235900590497018, "petal length (cm)": 1.7922053453775881, "petal width (cm)": 0.7664683191173177, "target": 0.8522416262267904}, "variance": {"sepal length (cm)": 0.6037894736842108, "sepal width (cm)": 0.10471052631578948, "petal length (cm)": 3.2119999999999997, "petal width (cm)": 0.5874736842105264, "target": 0.7263157894736844}}}, {"id": "5a6f6f9f-98c7-4c7b-94ab-8fe6c60a3906", "created_at": "2023-02-09T14:39:00.626188", "updated_at": "2023-02-09T14:39:00.626188", "model_id": "83539c2b-579f-4a2c-b7ba-02d31c9408d8", "timestamp": "2022-12-24T00:00:00", "feature_metrics": {"missing_count": {"sepal length (cm)": 0, "sepal width (cm)": 0, "petal length (cm)": 0, "petal width (cm)": 0, "target": 0}, "non_missing_count": {"sepal length (cm)": 30, "sepal width (cm)": 30, "petal length (cm)": 30, "petal width (cm)": 30, "target": 30}, "mean": {"sepal length (cm)": 5.876666666666666, "sepal width (cm)": 3.2199999999999998, "petal length (cm)": 3.4433333333333334, "petal width (cm)": 1.0966666666666667, "target": 0.8333333333333334}, "minimum": {"sepal length (cm)": 4.6, "sepal width (cm)": 2.5, "petal length (cm)": 1.2, "petal width (cm)": 0.1, "target": 0.0}, "maximum": {"sepal length (cm)": 7.2, "sepal width (cm)": 4.0, "petal length (cm)": 6.1, "petal width (cm)": 2.5, "target": 2.0}, "sum": {"sepal length (cm)": 176.29999999999998, "sepal width (cm)": 96.6, "petal length (cm)": 103.3, "petal width (cm)": 32.9, "target": 25.0}, "standard_deviation": {"sepal length (cm)": 0.8041630188708883, "sepal width (cm)": 0.37268827688047546, "petal length (cm)": 1.8108263180169955, "petal width (cm)": 0.7967534699981061, "target": 0.8339078479367936}, "variance": {"sepal length (cm)": 0.6466781609195406, "sepal width (cm)": 0.13889655172413795, "petal length (cm)": 3.2790919540229884, "petal width (cm)": 0.634816091954023, "target": 0.6954022988505746}}}]

drift.json

@@ -0,0 +1 @@
+[{"id": "b3381df8-56b4-43f6-aa72-523427b7d723", "created_at": "2023-02-09T14:33:00.456240", "updated_at": "2023-02-09T14:33:00.456240", "model_id": "83539c2b-579f-4a2c-b7ba-02d31c9408d8", "timestamp": "2022-12-22T00:00:00", "concept_drift_summary": {"concept_drift_summary": {"column_name": "target", "column_type": "cat", "stattest_name": "chi-square p_value", "drift_score": 0.3896307449384165, "drift_detected": false, "stattest_threshold": 0.05}, "column_correlation": {"column_name": "target", "current": {}, "reference": {}}}, "data_drift_summary": {"number_of_columns": 4, "number_of_drifted_columns": 0, "share_of_drifted_columns": 0.0, "dataset_drift": false, "drift_by_columns": {"petal length (cm)": {"column_name": "petal length (cm)", "column_type": "num", "stattest_name": "K-S p_value", "drift_score": 0.7588302830810655, "drift_detected": false, "threshold": 0.05}, "petal width (cm)": {"column_name": "petal width (cm)", "column_type": "num", "stattest_name": "K-S p_value", "drift_score": 0.7588302830810655, "drift_detected": false, "threshold": 0.05}, "sepal length (cm)": {"column_name": "sepal length (cm)", "column_type": "num", "stattest_name": "K-S p_value", "drift_score": 0.8382225197478262, "drift_detected": false, "threshold": 0.05}, "sepal width (cm)": {"column_name": "sepal width (cm)", "column_type": "num", "stattest_name": "K-S p_value", "drift_score": 0.9540265350498883, "drift_detected": false, "threshold": 0.05}}}},{"id": "6f74de30-9a5c-4a88-9e02-0a7d8777e242", "created_at": "2023-02-09T14:36:00.506190", "updated_at": "2023-02-09T14:36:00.506190", "model_id": "83539c2b-579f-4a2c-b7ba-02d31c9408d8", "timestamp": "2022-12-23T00:00:00", "concept_drift_summary": {"concept_drift_summary": {"column_name": "target", "column_type": "cat", "stattest_name": "chi-square p_value", "drift_score": 0.6738389777139696, "drift_detected": false, "stattest_threshold": 0.05}, "column_correlation": {"column_name": "target", "current": {}, "reference": {}}}, "data_drift_summary": {"number_of_columns": 4, "number_of_drifted_columns": 0, "share_of_drifted_columns": 0.0, "dataset_drift": false, "drift_by_columns": {"petal length (cm)": {"column_name": "petal length (cm)", "column_type": "num", "stattest_name": "K-S p_value", "drift_score": 0.9797880018857934, "drift_detected": false, "threshold": 0.05}, "petal width (cm)": {"column_name": "petal width (cm)", "column_type": "num", "stattest_name": "K-S p_value", "drift_score": 0.9325945507895383, "drift_detected": false, "threshold": 0.05}, "sepal length (cm)": {"column_name": "sepal length (cm)", "column_type": "num", "stattest_name": "K-S p_value", "drift_score": 0.8957682983065736, "drift_detected": false, "threshold": 0.05}, "sepal width (cm)": {"column_name": "sepal width (cm)", "column_type": "num", "stattest_name": "K-S p_value", "drift_score": 0.7450045755465691, "drift_detected": false, "threshold": 0.05}}}}, {"id": "78453a39-faa0-4aa7-bb30-8e4e1b91fef4", "created_at": "2023-02-09T14:39:00.608156", "updated_at": "2023-02-09T14:39:00.608156", "model_id": "83539c2b-579f-4a2c-b7ba-02d31c9408d8", "timestamp": "2022-12-24T00:00:00", "concept_drift_summary": {"concept_drift_summary": {"column_name": "target", "column_type": "cat", "stattest_name": "chi-square p_value", "drift_score": 0.32175216781613775, "drift_detected": false, "stattest_threshold": 0.05}, "column_correlation": {"column_name": "target", "current": {}, "reference": {}}}, "data_drift_summary": {"number_of_columns": 4, "number_of_drifted_columns": 0, "share_of_drifted_columns": 0.0, "dataset_drift": false, "drift_by_columns": {"petal length (cm)": {"column_name": "petal length (cm)", "column_type": "num", "stattest_name": "K-S p_value", "drift_score": 0.692577574430372, "drift_detected": false, "threshold": 0.05}, "petal width (cm)": {"column_name": "petal width (cm)", "column_type": "num", "stattest_name": "K-S p_value", "drift_score": 0.692577574430372, "drift_detected": false, "threshold": 0.05}, "sepal length (cm)": {"column_name": "sepal length (cm)", "column_type": "num", "stattest_name": "K-S p_value", "drift_score": 0.8799325977736985, "drift_detected": false, "threshold": 0.05}, "sepal width (cm)": {"column_name": "sepal width (cm)", "column_type": "num", "stattest_name": "K-S p_value", "drift_score": 0.1333377862549532, "drift_detected": false, "threshold": 0.05}}}}]

examples/notebooks/plot_functions.py

@@ -0,0 +1,28 @@
+import pandas as pd
+import seaborn as sns
+
+
+def desriptive_statistics_plot(report, timestep):
+    df = pd.DataFrame.from_dict(report[timestep]["feature_metrics"])
+    df = df.drop(["target"])
+    df["class"] = df.index
+    df_pivot = pd.melt(df, id_vars="class", var_name="statistics", value_name="value")
+    gfg = sns.catplot(
+        x="statistics",
+        y="value",
+        hue="class",
+        data=df_pivot,
+        kind="bar",
+        orient="v",
+        aspect=7 / 3,
+        palette="Spectral",
+    )
+    sns.set_theme(style="whitegrid")
+    gfg.set(
+        xlabel="",
+        ylabel="",
+        title="Descriptive Statistics for "
+        + report[timestep]["timestamp"].strip("T00:00:00"),
+    )
+
+    return gfg