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ETNA Time Series Library
Predict your time series the easiest way
Homepage | Documentation | Tutorials | Contribution Guide | Release Notes
ETNA is an easy-to-use time series forecasting framework. It includes built in toolkits for time series preprocessing, feature generation, a variety of predictive models with unified interface - from classic machine learning to SOTA neural networks, models combination methods and smart backtesting. ETNA is designed to make working with time series simple, productive, and fun.
ETNA is the first python open source framework of Tinkoff.ru Artificial Intelligence Center. The library started as an internal product in our company - we use it in over 10+ projects now, so we often release updates. Contributions are welcome - check our Contribution Guide.
Installation
ETNA is on PyPI, so you can use pip to install it.
pip install --upgrade pip
pip install etna
Get started
Here's some example code for a quick start.
import pandas as pd
from etna.datasets.tsdataset import TSDataset
from etna.models import ProphetModel
from etna.pipeline import Pipeline
# Read the data
df = pd.read_csv("examples/data/example_dataset.csv")
# Create a TSDataset
df = TSDataset.to_dataset(df)
ts = TSDataset(df, freq="D")
# Choose a horizon
HORIZON = 8
# Fit the pipeline
pipeline = Pipeline(model=ProphetModel(), horizon=HORIZON)
pipeline.fit(ts)
# Make the forecast
forecast_ts = pipeline.forecast()
Tutorials
We have also prepared a set of tutorials for an easy introduction:
| Notebook | Interactive launch |
|---|---|
| Get started |  |
| Backtest | |
| EDA | |
| Outliers | |
| Clustering | |
| Deep learning models | |
| Ensembles | |
Documentation
ETNA documentation is available here.
Resources
-
Forecasting with ETNA: Fast and Furious on Medium
-
Store sales prediction with etna library on Kaggle
-
PyCon Russia September 2021 talk on YouTube
Acknowledgments
ETNA.Team
Andrey Alekseev, Nikita Barinov, Dmitriy Bunin, Aleksandr Chikov, Vladislav Denisov, Martin Gabdushev, Sergey Kolesnikov, Artem Makhin, Ivan Mitskovets, Albina Munirova, Nikolay Romantsov, Julia Shenshina
ETNA.Contributors
Artem Levashov, Aleksey Podkidyshev, Carlosbogo
License
Feel free to use our library in your commercial and private applications.
ETNA is covered by Apache 2.0. Read more about this license here
2 maintainers
Metadata
2 maintainers
Release files for etna 1.5.0
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Total release size: 259.0 kB
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