pyts is a Python package for time series classification. It aims to make time series classification easily accessible by providing preprocessing and utility tools, and implementations of state-of-the-art algorithms. Most of these algorithms transform time series, thus pyts provides several tools to perform these transformations.

PyQtGraph is a Pure-python graphics library for PyQt5, PyQt6, PySide2 and PySide6. It is intended for use in mathematics, scientific or engineering applications.

xarray-dataclasses is a Python package that makes it easy to create xarray's DataArray and Datase objects that are "typed" (i.e. fixed dimensions, data type, coordinates, attributes, and name) using the Python's dataclass.

Scikit-survival is a Python module for survival analysis built on top of scikit-learn. It allows doing survival analysis while utilizing the power of scikit-learn, e.g., for pre-processing or doing cross-validation.

This package provides miscellaneous tools for data analysis and scientific computing.

This package provides a lightweight Python library for abstracting tensor operations. It provides an automatic dispatch mechanism that means you can write backend agnostic code that works for any library that provides a numpy compatible API.

This package provides a framework for building scientific applications. It aims to bring state of the art software design practices to scientific computing, with the goal of providing a strong skeleton on which to build scientific codes by steering the implementation towards usability and maintainability.

Snakemake aims to reduce the complexity of creating workflows by providing a clean and modern domain specific specification language (DSL) in Python style, together with a fast and comfortable execution environment.

DecayLanguage implements a language to describe and convert particle decays between digital representations, effectively making it possible to interoperate several fitting programs. Particular interest is given to programs dedicated to amplitude analyses.

This package provides accelerated simulations and potentials of solids.

Polars is an analytical query engine written for DataFrames. It is designed to be fast, easy to use and expressive.

Plotly's Python graphing library makes interactive,publication-quality graphs online. Examples of how to make line plots, scatter plots, area charts, bar charts, error bars, box plots, histograms, heatmaps, subplots, multiple-axes, polar charts, and bubble charts.

PyVista is...

• Pythonic VTK: a high-level API to the Visualization Toolkit (VTK);

• mesh data structures and filtering methods for spatial datasets;

• 3D plotting made simple and built for large/complex data geometries.

This package provides a Pythonic, well-documented interface exposing VTK's powerful visualization backend to facilitate rapid prototyping, analysis, and visual integration of spatially referenced datasets.

This package provides tooling to help with the propagation of uncertainty when disaggregating data, using the maximum entropy principle.

Bottleneck is a collection of fast, NaN-aware NumPy array functions written in C.

nibabel is a library that provides read and write access to common neuroimaging file formats, including: ANALYZE (plain, SPM99, SPM2 and later), GIFTI, NIfTI1, NIfTI2, CIFTI-2, MINC1, MINC2, AFNI BRIK/HEAD, ECAT and Philips PAR/REC. In addition, NiBabel also supports FreeSurfer’s MGH, geometry, annotation and morphometry files, and provides some limited support for DICOM.

This package provides an extremely lightweight compatibility layer between dataframe libraries.

• full API support: cuDF, Modin, pandas, Polars, PyArrow

• lazy-only support: Dask, DuckDB, Ibis, PySpark, SQLFrame

Formulaic is a high-performance implementation of Wilkinson formulas for Python.

Pingouin is a statistical package written in Python 3 and based mostly on Pandas and NumPy. Its features include

• ANOVAs: N-ways, repeated measures, mixed, ancova

• Pairwise post-hocs tests (parametric and non-parametric) and pairwise correlations

• Robust, partial, distance and repeated measures correlations

• Linear/logistic regression and mediation analysis

• Bayes Factors

• Multivariate tests

• Reliability and consistency

• Effect sizes and power analysis

• Parametric/bootstrapped confidence intervals around an effect size or a correlation coefficient

• Circular statistics

• Chi-squared tests

• Plotting: Bland-Altman plot, Q-Q plot, paired plot, robust correlation, and more

Modin uses Ray or Dask to provide an effortless way to speed up your pandas notebooks, scripts, and libraries. Unlike other distributed DataFrame libraries, Modin provides seamless integration and compatibility with existing pandas code.

beren provides a REST client for Orthanc, a DICOM server.

This package provides a Python Software Development Kit for the Model Context Protocol (MCP).

This package provides a git URL parsing module which supports parsing and rewriting of remote git URLs from various hosting providers.

DukPy is a simple JavaScript interpreter for Python built on top of duktape engine without any external dependency. It comes with a bunch of common transpilers built-in for convenience:

• CoffeeScript

• BabelJS

• TypeScript

• JSX

• LESS