Class swarmauri_standard.measurements.MissingnessMeasurement.MissingnessMeasurement
swarmauri_standard.measurements.MissingnessMeasurement.MissingnessMeasurement
Bases: MeasurementCalculateMixin
, MeasurementBase
A metric that evaluates the percentage of missing values in a dataset.
Missingness is calculated as the ratio of missing values to total values, expressed as a percentage. This metric helps identify data quality issues and incompleteness in datasets.
ATTRIBUTE | DESCRIPTION |
---|---|
type |
Type identifier for the metric
TYPE:
|
unit |
Unit of measurement (percentage)
TYPE:
|
value |
Stores the calculated missingness score
TYPE:
|
measurements |
List of measurements to analyze
TYPE:
|
type
class-attribute
instance-attribute
type = 'MissingnessMeasurement'
unit
class-attribute
instance-attribute
unit = '%'
measurements
class-attribute
instance-attribute
measurements = []
model_config
class-attribute
instance-attribute
model_config = ConfigDict(
extra="allow", arbitrary_types_allowed=True
)
id
class-attribute
instance-attribute
id = Field(default_factory=generate_id)
members
class-attribute
instance-attribute
members = None
owners
class-attribute
instance-attribute
owners = None
host
class-attribute
instance-attribute
host = None
default_logger
class-attribute
default_logger = None
logger
class-attribute
instance-attribute
logger = None
name
class-attribute
instance-attribute
name = None
resource
class-attribute
instance-attribute
resource = Field(default=MEASUREMENT.value, frozen=True)
version
class-attribute
instance-attribute
version = '0.1.0'
value
class-attribute
instance-attribute
value = None
calculate_missingness
calculate_missingness(data)
Calculates the missingness score for different data types.
PARAMETER | DESCRIPTION |
---|---|
data
|
Input data which can be a pandas DataFrame, List, or Dictionary
TYPE:
|
RETURNS | DESCRIPTION |
---|---|
float
|
Missingness score as a percentage (0-100)
TYPE:
|
RAISES | DESCRIPTION |
---|---|
ValueError
|
If an unsupported data type is provided |
Source code in swarmauri_standard/measurements/MissingnessMeasurement.py
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|
get_column_missingness
get_column_missingness(df)
Calculate missingness scores for individual columns in a DataFrame.
PARAMETER | DESCRIPTION |
---|---|
df
|
Input DataFrame
TYPE:
|
RETURNS | DESCRIPTION |
---|---|
Dict[str, float]
|
Dict[str, float]: Dictionary mapping column names to their missingness scores |
RAISES | DESCRIPTION |
---|---|
ValueError
|
If input is not a pandas DataFrame |
Source code in swarmauri_standard/measurements/MissingnessMeasurement.py
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|
calculate
calculate()
Calculate method required by MeasurementCalculateMixin. Uses the measurements list to calculate missingness.
RETURNS | DESCRIPTION |
---|---|
float
|
Missingness score as a percentage (0-100)
TYPE:
|
Source code in swarmauri_standard/measurements/MissingnessMeasurement.py
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|
add_measurement
add_measurement(measurement)
Adds a measurement to the internal list of measurements.
PARAMETER | DESCRIPTION |
---|---|
measurement
|
A numerical value or None to be added to the list of measurements.
TYPE:
|
Source code in swarmauri_standard/measurements/MissingnessMeasurement.py
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|
register_model
classmethod
register_model()
Decorator to register a base model in the unified registry.
RETURNS | DESCRIPTION |
---|---|
Callable
|
A decorator function that registers the model class.
TYPE:
|
Source code in swarmauri_base/DynamicBase.py
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|
register_type
classmethod
register_type(resource_type=None, type_name=None)
Decorator to register a subtype under one or more base models in the unified registry.
PARAMETER | DESCRIPTION |
---|---|
resource_type
|
The base model(s) under which to register the subtype. If None, all direct base classes (except DynamicBase) are used.
TYPE:
|
type_name
|
An optional custom type name for the subtype.
TYPE:
|
RETURNS | DESCRIPTION |
---|---|
Callable
|
A decorator function that registers the subtype.
TYPE:
|
Source code in swarmauri_base/DynamicBase.py
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|
model_validate_toml
classmethod
model_validate_toml(toml_data)
Validate a model from a TOML string.
Source code in swarmauri_base/TomlMixin.py
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|
model_dump_toml
model_dump_toml(
fields_to_exclude=None, api_key_placeholder=None
)
Return a TOML representation of the model.
Source code in swarmauri_base/TomlMixin.py
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|
model_validate_yaml
classmethod
model_validate_yaml(yaml_data)
Validate a model from a YAML string.
Source code in swarmauri_base/YamlMixin.py
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|
model_dump_yaml
model_dump_yaml(
fields_to_exclude=None, api_key_placeholder=None
)
Return a YAML representation of the model.
Source code in swarmauri_base/YamlMixin.py
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model_post_init
model_post_init(logger=None)
Assign a logger instance after model initialization.
Source code in swarmauri_base/LoggerMixin.py
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update
update(value)
Update the measurement value based on new information.
This should be used internally by the calculate
method or other logic.
Source code in swarmauri_base/measurements/MeasurementCalculateMixin.py
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