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Data science tools

StatsForecast

A Python library for predicting future values in data over time, like sales or electricity use.

What it does

StatsForecast is a toolkit for programmers that predicts what comes next in time series. A time series is data recorded over time, such as daily sales, monthly passengers or hourly electricity use. It includes many well-known statistical forecasting methods, such as ARIMA, ETS and Theta. Some of them can automatically pick the best settings for each series.

Its makers say it is faster and more accurate than other Python options, and that it can handle millions of series at once. It can also give a range of likely outcomes instead of a single guess, spot unusual values (anomaly detection), and take outside factors like weather or prices into account.

It works with tools for spreading work across many computers, such as Spark, Dask and Ray. It also includes simple baseline methods for comparing results.

Who it's for

Data scientists and analysts who need to forecast demand, sales, energy use or other values that change over time.

Can I use it without coding?

Developers only. It is a Python library, so you need to write code to use it. New to this? Start here.

Can I run it?

Cost
FreeNothing to pay or sign up for.
Privacy
Runs on your own device: your data stays with you
API key
Not needed

Try it

Using Claude Code, Cursor or another AI coding assistant? Paste the prompt and it will walk you through the setup.New to this?

Before you install

  • Only download from the official GitHub page. Copies with similar names exist for many popular projects.
  • Plain-AyI is an independent guide and doesn't host or review the software it lists. Please check each project's official page before installing.
  • License (Apache-2.0): Permissive: free to use, change and share, including for business.
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