preprocessing.outlier.manual_outlier_removal

preprocessing.outlier.manual_outlier_removal(
    data,
    column,
    lower_threshold=None,
    upper_threshold=None,
    verbose=False,
)

Manual outlier removal function.

Parameters

Name	Type	Description	Default
data	pd.DataFrame	The input dataset.	required
column	str	The column name in which to perform manual outlier removal.	required
lower_threshold	float \| None	The lower threshold below which values are considered outliers. If None, no lower threshold is applied.	`None`
upper_threshold	float \| None	The upper threshold above which values are considered outliers. If None, no upper threshold is applied.	`None`
verbose	bool	Whether to print additional information.	`False`

Returns

Name	Type	Description
	tuple[pd.DataFrame, int]	tuple[pd.DataFrame, int]: A tuple containing the modified dataset with outliers marked as NaN and the number of outliers marked.

Examples

>>> from spotforecast2_safe.data.fetch_data import fetch_data
>>> from spotforecast2_safe.preprocessing.outlier import manual_outlier_removal
>>> data = fetch_data()
>>> data, n_manual_outliers = manual_outlier_removal(
...     data,
...     column='ABC',
...     lower_threshold=50,
...     upper_threshold=700,
...     verbose=True