tsfresh automatically extracts relevant features from time series data.
Open source
24 alternativesModin
Modin scales Pandas data workflows by changing a single line of code in a project.
About Modin
Modin is an open source Python library that works as a drop-in replacement for pandas. Its stated purpose is to speed up pandas workflows by scaling them to use all available CPU cores. The source says it works especially well on larger datasets, where pandas can become slow or run out of memory. Switching to Modin requires changing only the pandas import statement in a project.
Modin can be installed with pip on Linux, Windows, and macOS, or from conda-forge. It supports Ray, Dask, and MPI through unidist as compute engines, and it detects which installed engines to use for scheduling. Since version 0.30.0, the default Ray install omits the dashboard and cluster launcher, which must be installed separately if needed. The source does not provide benchmark results beyond showing speedup charts.
Key features
- Drop-in replacement for pandas that uses all available CPU cores
- Requires changing only the pandas import statement in existing code
- Supports Ray, Dask, and MPI (through unidist) as compute engines
- Automatically detects installed engines and uses them for scheduling
- Installable with pip on Linux, Windows, and macOS
- Installable from conda-forge, including a modin-all package with three engines
Best for: Python users who already run pandas workflows on larger datasets and want to reduce runtime without rewriting their code.
Good for
- Changing the import statement is the only code change described for switching from pandas.
- Supports several compute engines, so users can choose one that fits their setup.
- Released as open source, with the repository publicly available on GitHub.
Watch out for
- The MPI option requires a working MPI implementation to be installed beforehand, or installation may fail.
- The Ray dashboard and cluster launcher are not installed by default since version 0.30.0.
- The source describes Modin as working especially well on larger datasets, so its benefit on smaller datasets is not stated.
Modin at a glance
- Category
- AI & Machine Learning › AI Data & Analytics
- Type
- Open-source project
- Pricing
- Not confirmed. Check the site
- Open source
- Yes · Source code
- Language
- English
- Last checked
- Oct 6, 2026 · Online when checked
- Listed
- Oct 5, 2026
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Modin FAQ
How do I install Modin with a specific compute engine?
The source recommends pip install "modin[ray]" for Ray, "modin[dask]" for Dask, and "modin[mpi]" for MPI through unidist. Installing "modin[all]" with pip installs Modin with Ray and Dask engines.
What do I need to change in existing pandas code to use Modin?
The source says that simply replacing the import statement is enough to use Modin, with no other changes to the workflow described.
Do I need anything extra to install Modin with MPI?
Yes. The source states that a working MPI implementation must be installed beforehand, otherwise installing modin[mpi] may fail.
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