preprocessing.checking.get_exog_dtypes

preprocessing.checking.get_exog_dtypes(exog)

Extract and store the data types of exogenous variables.

This function returns a dictionary mapping column names to their data types. For Series, uses the series name as the key. For DataFrames, uses all column names.

Parameters

Name	Type	Description	Default
exog	Union[pd.Series, pd.DataFrame]	Exogenous variable/s (Series or DataFrame).	required

Returns

Name	Type	Description
	Dict[str, type]	Dictionary mapping variable names to their pandas dtypes.

Examples

import numpy as np
import pandas as pd

from spotforecast2_safe.preprocessing.checking import get_exog_dtypes

# DataFrame with mixed types
exog_df = pd.DataFrame({
    "temp": pd.Series([20.5, 21.3, 22.1], dtype="float64"),
    "day": pd.Series([1, 2, 3], dtype="int64"),
})
dtypes = get_exog_dtypes(exog_df)
print(dtypes["temp"])
print(dtypes["day"])
assert dtypes["temp"] == np.dtype("float64")
assert dtypes["day"] == np.dtype("int64")

# Series
exog_series = pd.Series([1.0, 2.0, 3.0], name="temperature", dtype="float64")
dtypes_series = get_exog_dtypes(exog_series)
print(dtypes_series)
assert dtypes_series == {"temperature": np.dtype("float64")}

float64
int64
{'temperature': dtype('float64')}