forecastbox
Forecast containers, evaluation metrics, and cross-validation for time series.
Installation
pip install -e ".[dev]"
Quick Start
import numpy as np
import pandas as pd
from forecastbox import Forecast
from forecastbox.metrics import mae, rmse
from forecastbox.datasets import load_dataset
# Create a forecast
fc = Forecast(
point=np.array([100.5, 101.2, 102.0]),
index=pd.date_range('2024-01', periods=3, freq='MS'),
model_name='MyModel',
horizon=3
)
# Evaluate
actual = np.array([100.8, 100.9, 103.1])
print(f"MAE: {mae(actual, fc.point):.2f}")
print(f"RMSE: {rmse(actual, fc.point):.2f}")
# Load dataset
data = load_dataset('macro_brazil')
print(data['ipca'].head())
License
MIT
1 maintainer
Metadata
1 maintainer
Release files for forecastbox 0.1.0
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| forecastbox-0.1.0.tar.gz | 224.5 kB | Details |
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| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| forecastbox-0.1.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 505.5 kB
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| Tags | Python 3 |
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