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glassbox.inspector.report

Data classes for the EDA report: EDAReport, OutlierInfo, MissingInfo, NumericStats, CategoricalStats.

FeatureType

Bases: Enum

Enumerates possible statistical data types for features.

CollinearityPair dataclass 

CollinearityPair(feature_a, feature_b, score, metric)

Represents an association or correlation between two features.

OutlierInfo dataclass 

OutlierInfo(count, lower_bound, upper_bound)

Stores outlier bounds and count for a single feature.

MissingInfo dataclass 

MissingInfo(count, percentage)

Stores missing values count and percentage.

NumericStats dataclass 

NumericStats(mean, median, std, skew, kurt)

Stores basic summary statistics for a numerical feature.

CategoricalStats dataclass 

CategoricalStats(mode, cardinality)

Stores summary statistics for a categorical feature.

EDAReport dataclass 

EDAReport(
    feature_types,
    missing_values,
    outliers_info,
    summary_stats,
    collinearity_map,
)

Container for the complete Exploratory Data Analysis report.

to_json 

to_json()

Serialize the entire EDA report down to a JSON string.

Returns:

Type Description
str

JSON representation of the report.
Source code in glassbox/inspector/report.py 
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def to_json(self) -> str:
    """
    Serialize the entire EDA report down to a JSON string.

    Returns
    -------
    str
        JSON representation of the report.
    """

    class EnumEncoder(json.JSONEncoder):
        def default(self, obj):
            if isinstance(obj, Enum):
                return obj.name
            if isinstance(obj, float) and np.isnan(obj):
                return None
            return super().default(obj)

    # We need to handle nan to null if missing, but json.dumps handles nan by default to NaN.
    # But JSON standard doesn't support NaN, so let's allow it standard.
    return json.dumps(dataclasses.asdict(self), cls=EnumEncoder)