interpreTS.utils package#
Submodules#
interpreTS.utils.data_conversion module#
- interpreTS.utils.data_conversion.convert_to_time_series(data)#
Convert input data to a TimeSeriesData object.
Parameters#
- datapd.DataFrame, pd.Series, or np.ndarray
The data to be converted into a TimeSeriesData object.
Returns#
- TimeSeriesData
An instance of TimeSeriesData wrapping the input data.
Raises#
- TypeError
If the input data is not of type pd.DataFrame, pd.Series, or np.ndarray.
Examples#
>>> import pandas as pd >>> data = pd.Series([1, 2, 3, 4, 5]) >>> ts_data = convert_to_time_series(data)
interpreTS.utils.data_validation module#
- interpreTS.utils.data_validation.validate_time_series_data(data, require_datetime_index=False)#
Validate if the input data is suitable for time series processing.
Parameters#
- datapd.Series, pd.DataFrame, or np.ndarray
The time series data to be validated.
- require_datetime_indexbool, optional
If True, validation will ensure the data has a DateTime index (for time-based operations).
Returns#
- bool
True if the data is valid; raises an error otherwise.
Raises#
- TypeError
If data is not a pd.Series, pd.DataFrame, or np.ndarray.
- ValueError
If the data contains NaN values or lacks a DateTime index when required.