StringLengthOutOfBounds#
- class StringLengthOutOfBounds[source]#
Detect strings with length that is much longer/shorter than the identified “normal” string lengths.
- Parameters
- columnsUnion[Hashable, List[Hashable]] , default: None
Columns to check, if none are given checks all columns except ignored ones.
- ignore_columnsUnion[Hashable, List[Hashable]] , default: None
Columns to ignore, if none given checks based on columns variable
- num_percentilesint , default: 1000
Number of percentiles values to retrieve for the length of the samples in the string column. Affects the resolution of string lengths that is used to detect outliers.
- inner_quantile_rangeint , default: 94
The int upper percentile [0-100] defining the inner percentile range. E.g. for 98 the range would be 2%-98%.
- outlier_factorint , default: 4
Strings would be defined as outliers if their length is outlier_factor times more/less than the values inside the inner quantile range.
- min_length_differenceint , default: 5
The minimum length difference to be considered as outlier.
- min_length_ratio_differenceint , default: 0.5
Used to calculate the minimum length difference to be considered as outlier. (calculated form this times the average of the normal lengths.)
- min_unique_value_ratiofloat , default: 0.01
Min
- min_unique_valuesint , default: 100
Minimum unique values in column to calculate string length outlier
- n_top_columnsint , optional
amount of columns to show ordered by feature importance (date, index, label are first)
- outlier_length_to_showint , default: 50
Maximum length of outlier to show in results. If an outlier is longer it is trimmed and added ‘…’
- samples_per_range_to_showint , default: 3
Number of outlier samples to show in results per outlier range found.
- __init__(columns: Optional[Union[Hashable, List[Hashable]]] = None, ignore_columns: Optional[Union[Hashable, List[Hashable]]] = None, num_percentiles: int = 1000, inner_quantile_range: int = 94, outlier_factor: int = 4, min_length_difference: int = 5, min_length_ratio_difference: float = 0.5, min_unique_value_ratio: float = 0.01, min_unique_values: int = 100, n_top_columns: int = 10, outlier_length_to_show: int = 50, samples_per_range_to_show: int = 3, **kwargs)[source]#
- __new__(*args, **kwargs)#
Methods
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Add new condition function to the check. |
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Add condition - require column's number of string length outliers to be less or equal to the threshold. |
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Add condition - require column's ratio of string length outliers to be less or equal to threshold. |
Remove all conditions from this check instance. |
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Run conditions on given result. |
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Return check configuration (conditions' configuration not yet supported). |
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Return check object from a CheckConfig object. |
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Return check metadata. |
Name of class in split camel case. |
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Return parameters to show when printing the check. |
Remove given condition by index. |
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Run check. |
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Run check. |
