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etna-2.0.0
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مشاهده بیشتر
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مشاهده بیشترتوضیحات
ETNA is the first python open source framework of Tinkoff.ru AI Center. It is designed to make working with time series simple, productive, and fun.
| ویژگی | مقدار |
|---|---|
| سیستم عامل | - |
| نام فایل | etna-2.0.0 |
| نام | etna |
| نسخه کتابخانه | 2.0.0 |
| نگهدارنده | [] |
| ایمیل نگهدارنده | [] |
| نویسنده | Andrey Alekseev |
| ایمیل نویسنده | ilekseev@gmail.com |
| آدرس صفحه اصلی | https://github.com/tinkoff-ai/etna |
| آدرس اینترنتی | https://pypi.org/project/etna/ |
| مجوز | Apache-2.0 |
<div align="center">
<img src="etna_logo.png" width="100%"/>
</div>
<h3 align="center">Predict your time series the easiest way</h3>
<p align="center">
<a href="https://pypi.org/project/etna/"><img alt="PyPI Version" src="https://img.shields.io/pypi/v/etna.svg" /></a>
<a href="https://pypi.org/project/etna/"><img alt="Python versions" src="https://img.shields.io/pypi/pyversions/etna.svg" /></a>
<a href="https://pepy.tech/project/etna"><img alt="Downloads" src="https://static.pepy.tech/personalized-badge/etna?period=total&units=international_system&left_color=grey&right_color=green&left_text=Downloads" /></a>
</p>
<p align="center">
<a href="https://codecov.io/gh/tinkoff-ai/etna"><img alt="Coverage" src="https://img.shields.io/codecov/c/github/tinkoff-ai/etna.svg" /></a>
<a href="https://github.com/tinkoff-ai/etna/actions/workflows/test.yml?query=branch%3Amaster++"><img alt="Test passing" src="https://img.shields.io/github/actions/workflow/status/tinkoff-ai/etna/test.yml?branch=master&label=tests" /></a>
<a href="https://github.com/tinkoff-ai/etna/actions/workflows/publish.yml"><img alt="Docs publish" src="https://img.shields.io/github/actions/workflow/status/tinkoff-ai/etna/publish.yml?label=docs" /></a>
<a href="https://github.com/tinkoff-ai/etna/blob/master/LICENSE"><img alt="License" src="https://img.shields.io/github/license/tinkoff-ai/etna.svg" /></a>
</p>
<p align="center">
<a href="https://t.me/etna_support"><img alt="Telegram" src="https://img.shields.io/badge/channel-telegram-blue" /></a>
<a href="https://github.com/tinkoff-ai/etna/discussions"><img alt="GitHub Discussions" src="https://img.shields.io/github/discussions/tinkoff-ai/etna" /></a>
<a href="https://github.com/tinkoff-ai/etna/graphs/contributors"><img alt="Contributors" src="https://img.shields.io/github/contributors/tinkoff-ai/etna.svg" /></a>
<a href="https://github.com/tinkoff-ai/etna/stargazers"><img alt="Stars" src="https://img.shields.io/github/stars/tinkoff-ai/etna?style=social" /></a>
</p>
<p align="center">
<a href="https://etna.tinkoff.ru">Homepage</a> |
<a href="https://etna-docs.netlify.app/">Documentation</a> |
<a href="https://github.com/tinkoff-ai/etna/tree/master/examples">Tutorials</a> |
<a href="https://github.com/tinkoff-ai/etna/blob/master/CONTRIBUTING.md">Contribution Guide</a> |
<a href="https://github.com/tinkoff-ai/etna/releases">Release Notes</a>
</p>
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](https://www.tinkoff.ru/eng/)
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](https://github.com/tinkoff-ai/etna/blob/master/CONTRIBUTING.md).
## Get started
Let's load and prepare the data.
```python
import pandas as pd
from etna.datasets import TSDataset
# 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 = 14
# Make train/test split
train_ts, test_ts = ts.train_test_split(test_size=HORIZON)
```
Define transformations and model:
```python
from etna.models import CatBoostMultiSegmentModel
from etna.transforms import DateFlagsTransform
from etna.transforms import DensityOutliersTransform
from etna.transforms import FourierTransform
from etna.transforms import LagTransform
from etna.transforms import LinearTrendTransform
from etna.transforms import MeanTransform
from etna.transforms import SegmentEncoderTransform
from etna.transforms import TimeSeriesImputerTransform
from etna.transforms import TrendTransform
# Prepare transforms
transforms = [
DensityOutliersTransform(in_column="target", distance_coef=3.0),
TimeSeriesImputerTransform(in_column="target", strategy="forward_fill"),
LinearTrendTransform(in_column="target"),
TrendTransform(in_column="target", out_column="trend"),
LagTransform(in_column="target", lags=list(range(HORIZON, 122)), out_column="target_lag"),
DateFlagsTransform(week_number_in_month=True, out_column="date_flag"),
FourierTransform(period=360.25, order=6, out_column="fourier"),
SegmentEncoderTransform(),
MeanTransform(in_column=f"target_lag_{HORIZON}", window=12, seasonality=7),
MeanTransform(in_column=f"target_lag_{HORIZON}", window=7),
]
# Prepare model
model = CatBoostMultiSegmentModel()
```
Fit `Pipeline` and make a prediction:
```python
from etna.pipeline import Pipeline
# Create and fit the pipeline
pipeline = Pipeline(model=model, transforms=transforms, horizon=HORIZON)
pipeline.fit(train_ts)
# Make a forecast
forecast_ts = pipeline.forecast()
```
Let's plot the results:
```python
from etna.analysis import plot_forecast
plot_forecast(forecast_ts=forecast_ts, test_ts=test_ts, train_ts=train_ts, n_train_samples=50)
```
Print the metric value across the segments:
```python
from etna.metrics import SMAPE
metric = SMAPE(mode="macro")
metric_value = metric(y_true=test_ts, y_pred=forecast_ts)
>>> {'segment_b': 3.3017151519000967, 'segment_c': 5.270557433427279, 'segment_a': 5.272811627335398, 'segment_d': 4.689085450895735}
```
## Installation
ETNA is available on [PyPI](https://pypi.org/project/etna), so you can use `pip` to install it.
Install default version:
```bash
pip install --upgrade pip
pip install etna
```
The default version doesn't contain all the dependencies, because some of them are needed only for specific models, e.g. Prophet, PyTorch.
Available user extensions are the following:
* `prophet`
* `torch`
* `wandb`
Install extension:
```bash
pip install etna[extension-name]
```
Install all extensions:
```bash
pip install etna[all]
```
There are also developer extensions. All the extensions are listed in [`pyproject.toml`](https://github.com/tinkoff-ai/etna/blob/master/pyproject.toml#L93).
Without the appropriate extension you will get an `ImportError` trying to import the model that needs it.
For example, `etna.models.ProphetModel` needs `prophet` extension and can't be used without it.
### Configuration
ETNA supports configuration files. It means that library will check that all the specified packages are installed prior to script start and NOT during runtime.
To set up a configuration for your project you should create a `.etna` file at the project's root. To see the available options look at [`Settings`](https://github.com/tinkoff-ai/etna/blob/master/etna/settings.py#L68). There is an [example](https://github.com/tinkoff-ai/etna/tree/master/examples/configs/.etna) of configuration file.
## Tutorials
We have also prepared a set of tutorials for an easy introduction:
| Notebook | Interactive launch |
|:----------|------:|
| [Get started](https://github.com/tinkoff-ai/etna/tree/master/examples/get_started.ipynb) | [](https://mybinder.org/v2/gh/tinkoff-ai/etna/master?filepath=examples/get_started.ipynb) |
| [Backtest](https://github.com/tinkoff-ai/etna/tree/master/examples/backtest.ipynb) | [](https://mybinder.org/v2/gh/tinkoff-ai/etna/master?filepath=examples/backtest.ipynb) |
| [EDA](https://github.com/tinkoff-ai/etna/tree/master/examples/EDA.ipynb) | [](https://mybinder.org/v2/gh/tinkoff-ai/etna/master?filepath=examples/EDA.ipynb) |
| [Outliers](https://github.com/tinkoff-ai/etna/tree/master/examples/outliers.ipynb) | [](https://mybinder.org/v2/gh/tinkoff-ai/etna/master?filepath=examples/outliers.ipynb) |
| [Clustering](https://github.com/tinkoff-ai/etna/tree/master/examples/clustering.ipynb) | [](https://mybinder.org/v2/gh/tinkoff-ai/etna/master?filepath=examples/clustering.ipynb) |
| [Deep learning models](https://github.com/tinkoff-ai/etna/tree/master/examples/NN_examples.ipynb) | [](https://mybinder.org/v2/gh/tinkoff-ai/etna/master?filepath=examples/NN_examples.ipynb) |
| [Ensembles](https://github.com/tinkoff-ai/etna/tree/master/examples/ensembles.ipynb) | [](https://mybinder.org/v2/gh/tinkoff-ai/etna/master?filepath=examples/ensembles.ipynb) |
| [Custom Transform and Model](https://github.com/tinkoff-ai/etna/tree/master/examples/custom_transform_and_model.ipynb) | [](https://mybinder.org/v2/gh/tinkoff-ai/etna/master?filepath=examples/custom_transform_and_model.ipynb) |
| [Exogenous data](https://github.com/tinkoff-ai/etna/tree/master/examples/exogenous_data.ipynb) | [](https://mybinder.org/v2/gh/tinkoff-ai/etna/master?filepath=examples/exogenous_data.ipynb) |
| [Forecasting strategies](https://github.com/tinkoff-ai/etna/blob/master/examples/forecasting_strategies.ipynb) | [](https://mybinder.org/v2/gh/tinkoff-ai/etna/master?filepath=examples/forecasting_strategies.ipynb) |
| [Classification](https://github.com/tinkoff-ai/etna/blob/master/examples/classification.ipynb) | [](https://mybinder.org/v2/gh/tinkoff-ai/etna/master?filepath=examples/classification.ipynb) |
| [Hierarchical time series](https://github.com/tinkoff-ai/etna/blob/master/examples/hierarchical_pipeline.ipynb) | [](https://mybinder.org/v2/gh/tinkoff-ai/etna/master?filepath=examples/hierarchical_pipeline.ipynb) |
## Documentation
ETNA documentation is available [here](https://etna-docs.netlify.app/).
## Community
To ask the questions or discuss the library you can join our [telegram chat](t.me/etna_support).
[Discussions section](https://github.com/tinkoff-ai/etna/discussions) on github is also open for this purpose.
## Resources
- [Forecasting with ETNA: Fast and Furious](https://medium.com/its-tinkoff/forecasting-with-etna-fast-and-furious-1b58e1453809) on Medium
- [ETNA Regressors](https://medium.com/its-tinkoff/etna-regressors-d2722923e88e) on Medium
- [Time series forecasting with ETNA: first steps](https://medium.com/its-tinkoff/time-series-forecasting-with-etna-first-steps-dfaf90c5b919) on Medium
- [ETNA: Time Series Analysis. What, why and how?](https://medium.com/its-tinkoff/etna-time-series-analysis-what-why-and-how-e45557af4f6c) on Medium
- [Tabular Playground Series - Mar 2022 (7th place!)](https://www.kaggle.com/code/chikovalexander/tps-mar-2022-etna/notebook?scriptVersionId=91575908) on Kaggle
- [Store sales prediction with etna library](https://www.kaggle.com/dmitrybunin/store-sales-prediction-with-etna-library?scriptVersionId=81104235) on Kaggle
- [Tabular Playground Series - Jan 2022](https://www.kaggle.com/code/chikovalexander/tps-jan-2022-etna/notebook) on Kaggle
- [EDA notebook for Ubiquant Market Prediction](https://www.kaggle.com/code/martins0n/ubiquant-eda-toy-predictions-etna) on Kaggle
- [PyCon Russia September 2021 talk](https://youtu.be/VxWHLEFgXnE) on YouTube
- [ETNA Meetup Jun 2022](https://www.youtube.com/watch?v=N1Xy3EqY058&list=PLLrf_044z4JrSsjMd-3dF6VbBLPI_yOxG) on YouTube
- [DUMP May 2022 talk](https://youtu.be/12uuxepdtks) on YouTube
## Acknowledgments
### ETNA.Team
[Andrey Alekseev](https://github.com/iKintosh),
[Nikita Barinov](https://github.com/diadorer),
[Dmitriy Bunin](https://github.com/Mr-Geekman),
[Aleksandr Chikov](https://github.com/alex-hse-repository),
[Vladislav Denisov](https://github.com/v-v-denisov),
[Martin Gabdushev](https://github.com/martins0n),
[Sergey Kolesnikov](https://github.com/Scitator),
[Artem Makhin](https://github.com/Ama16),
[Ivan Mitskovets](https://github.com/imitskovets),
[Albina Munirova](https://github.com/albinamunirova),
[Julia Shenshina](https://github.com/julia-shenshina),
[Yuriy Tarasyuk](https://github.com/DBcreator),
[Konstantin Vedernikov](https://github.com/scanhex12)
### ETNA.Contributors
[WinstonDovlatov](https://github.com/WinstonDovlatov),
[mvakhmenin](https://github.com/mvakhmenin),
[Carlosbogo](https://github.com/Carlosbogo),
[Pacman1984](https://github.com/Pacman1984),
[looopka](https://github.com/looopka),
[Artem Levashov](https://github.com/soft1q),
[Aleksey Podkidyshev](https://github.com/alekseyen)
## License
Feel free to use our library in your commercial and private applications.
ETNA is covered by [Apache 2.0](/LICENSE).
Read more about this license [here](https://choosealicense.com/licenses/apache-2.0/)
> Please note that `etna[prophet]` is covered by [GPL 2.0](https://www.gnu.org/licenses/old-licenses/gpl-2.0.html) due to pystan package.
نیازمندی
| مقدار | نام |
|---|---|
| >=0.24,<2 | scikit-learn |
| >=1.1,<2.0 | pandas |
| >=0.21 | catboost |
| ==1.1.5 | ruptures |
| >=0.53.1,<0.56.0 | numba |
| >=0.11.1,<0.12.0 | seaborn |
| >=0.12,<0.14 | statsmodels |
| >=1.8.0 | pmdarima |
| >=0.3.4,<0.4.0 | dill |
| >=0.10.2,<0.11.0 | toml |
| >=0.5.3,<0.6.0 | loguru |
| >=0.2.0,<0.3.0 | hydra-slayer |
| >=0.4.0,<0.5.0 | typer |
| >=2.1.1,<3.0.0 | omegaconf |
| >=0.13,<0.14 | holidays |
| >=1.5,<2.0 | boto3 |
| - | botocore |
| <1.8.0 | scipy |
| >=1.3.4,<2.0.0 | Bottleneck |
| - | numpy |
| - | joblib |
| - | plotly |
| - | hydra_slayer |
| - | matplotlib |
| - | typing_extensions |
| >=1.1.0,<2.0.0 | tbats |
| ==1.2.13 | Deprecated |
| ==1.2.9 | types-Deprecated |
| >=1.0,<2.0 | prophet |
| >=1.8.0,<1.12.0 | torch |
| >=0.9.0,<0.10.0 | pytorch-forecasting |
| - | pytorch-lightning |
| >=0.12.2,<0.13.0 | wandb |
| >=2.5.0,<3.0.0 | optuna |
| >=0.0.1,<0.0.2 | sphinx-mathjax-offline |
| >=0.8.2,<0.9.0 | nbsphinx |
| >=4.1,<5.0 | Sphinx |
| >=1.1.0,<2.0.0 | numpydoc |
| >=0.5.1,<0.6.0 | sphinx-rtd-theme |
| >=0.15.0,<0.16.0 | myst-parser |
| >=3.1.20,<4.0.0 | GitPython |
| >=6.2,<7.0 | pytest |
| >=5.4,<6.0 | coverage |
| >=2.11.1,<3.0.0 | pytest-cov |
| >=22.3.0,<23.0.0 | black[jupyter] |
| >=5.8.0,<6.0.0 | isort |
| >=3.9.2,<4.0.0 | flake8 |
| >=0.12.1,<0.13.0 | pep8-naming |
| >=22.4.25,<23.0.0 | flake8-bugbear |
| >=3.9.0,<4.0.0 | flake8-comprehensions |
| >=1.6.0,<2.0.0 | flake8-docstrings |
| >=0.950,<0.951 | mypy |
| >=6.0.0,<7.0.0 | types-PyYAML |
| >=2.0.0,<3.0.0 | codespell |
| >=8.0.1,<8.1 | click |
| >=2.13.0,<3.0.0 | semver |
| >=7.6.5,<8.0.0 | ipywidgets |
| - | jupyter |
| - | nbconvert |
| >=0.12.0,<0.13.0 | pyts |
| >=65.7.0,<66.0.0 | types-setuptools |
زبان مورد نیاز
| مقدار | نام |
|---|---|
| >=3.8.0,<3.11.0 | Python |
نحوه نصب
نصب پکیج whl etna-2.0.0:
pip install etna-2.0.0.whl
نصب پکیج tar.gz etna-2.0.0:
pip install etna-2.0.0.tar.gz