[PR #2640] Added Darts: A Time Series Forecasting Library #1956

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GiteaMirror · 2025-11-06T13:26:35-06:00

GiteaMirror commented

2025-11-06 13:26:35 -06:00

📋 Pull Request Information

Original PR: https://github.com/vinta/awesome-python/pull/2640
Author: @rfeverts
Created: 1/5/2025
Status: 🔄 Open

Base: master ← Head: add-darts

📝 Commits (2)

a514228 Added Pycobra: A library for ensemble learning and visualization
d152022 Added Darts: A library for time series forecasting

📊 Changes

1 file changed (+3 additions, -0 deletions)

View changed files

📝 README.md (+3 -0)

📄 Description

This pull request adds Darts, a Python library for time series forecasting, to the Machine Learning section of the Awesome Python list.

Why Darts?

Darts provides an intuitive and flexible API for time series forecasting.
Supports both traditional models (ARIMA, Exponential Smoothing) and advanced deep learning methods (RNNs, Transformers).
Enables seamless integration with pandas, simplifying time series data manipulation.

Key Features

Combines statistical and deep learning approaches for forecasting.
Built-in tools for backtesting, benchmarking, and visualizing models.
Pre-trained models included for quick deployment and experimentation.
Darts is a valuable addition to the Machine Learning section, catering to practitioners and researchers working on time series problems.

Anyone who agrees with this pull request could submit an Approve review to it.

Example usage:
Example fitting a model.txt
Example importing and preparing Data.txt

References
Darts Documentation
Pandas Documentation

_{🔄 This issue represents a GitHub Pull Request. It cannot be merged through Gitea due to API limitations.}

## 📋 Pull Request Information **Original PR:** https://github.com/vinta/awesome-python/pull/2640 **Author:** [@rfeverts](https://github.com/rfeverts) **Created:** 1/5/2025 **Status:** 🔄 Open **Base:** `master` ← **Head:** `add-darts` --- ### 📝 Commits (2) - [`a514228`](https://github.com/vinta/awesome-python/commit/a5142283bdf9dc7afc379b0fbeb7221e76581df3) Added Pycobra: A library for ensemble learning and visualization - [`d152022`](https://github.com/vinta/awesome-python/commit/d15202230e9580ad8a2f7b1db6ab293dfac2eca6) Added Darts: A library for time series forecasting ### 📊 Changes **1 file changed** (+3 additions, -0 deletions) <details> <summary>View changed files</summary> 📝 `README.md` (+3 -0) </details> ### 📄 Description This pull request adds Darts, a Python library for time series forecasting, to the Machine Learning section of the Awesome Python list. **Why Darts?** - Darts provides an intuitive and flexible API for time series forecasting. - Supports both traditional models (ARIMA, Exponential Smoothing) and advanced deep learning methods (RNNs, Transformers). - Enables seamless integration with pandas, simplifying time series data manipulation. **Key Features** - Combines statistical and deep learning approaches for forecasting. - Built-in tools for backtesting, benchmarking, and visualizing models. - Pre-trained models included for quick deployment and experimentation. - Darts is a valuable addition to the Machine Learning section, catering to practitioners and researchers working on time series problems. Anyone who agrees with this pull request could submit an *Approve* review to it. Example usage: [Example fitting a model.txt](https://github.com/user-attachments/files/18312042/Example.fitting.a.model.txt) [Example importing and preparing Data.txt](https://github.com/user-attachments/files/18312043/Example.importing.and.preparing.Data.txt) References [Darts Documentation](https://github.com/unit8co/darts) [Pandas Documentation](https://pandas.pydata.org/) --- <sub>🔄 This issue represents a GitHub Pull Request. It cannot be merged through Gitea due to API limitations.</sub>

GiteaMirror added the pull-request label 2025-11-06 13:26:35 -06:00

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Reference: github-starred/awesome-python#1956