utils.validation.check_y

utils.validation.check_y(y, series_id='`y`')

Validate that y is a pandas Series without missing values.

This function ensures that the input time series meets the basic requirements for forecasting: it must be a pandas Series and must not contain any NaN values.

Parameters

Name	Type	Description	Default
y	Any	Time series values to validate.	required
series_id	str	Identifier of the series used in error messages. Defaults to “y”.	'y'

Raises

Name	Type	Description
	TypeError	If y is not a pandas Series.
	ValueError	If y contains missing (NaN) values.

Examples

>>> import pandas as pd
>>> import numpy as np
>>> from spotforecast2_safe.utils.validation import check_y
>>>
>>> # Valid series
>>> y = pd.Series([1, 2, 3, 4, 5])
>>> check_y(y)  # No error
>>>
>>> # Invalid: not a Series
>>> try:
...     check_y([1, 2, 3])
... except TypeError as e:
...     print(f"Error: {e}")
Error: `y` must be a pandas Series with a DatetimeIndex or a RangeIndex. Found <class 'list'>.
>>>
>>> # Invalid: contains NaN
>>> y_with_nan = pd.Series([1, 2, np.nan, 4])
>>> try:
...     check_y(y_with_nan)
... except ValueError as e:
...     print(f"Error: {e}")
Error: `y` has missing values.