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

Pint is a Python package to define, operate and manipulate physical quantities: the product of a numerical value and a unit of measurement. It allows arithmetic operations between them and conversions from and to different units.

This package provides optimized tools for group-indexing operations: aggregated sum and more.

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

pyvistaqt is a helper module for pyvista to enable you to plot using Qt by placing a vtk-widget into a background renderer. This can be quite useful when you desire to update your plot in real-time.

Vaex is a high performance Python library for lazy Out-of-Core DataFrames (similar to Pandas), to visualize and explore big tabular datasets. This package provides the core modules of Vaex.

Plotnine is a Python implementation of the Grammar of Graphics. It is a powerful graphics concept for creating plots and visualizations in a structured and declarative manner. It is inspired by the R package ggplot2 and aims to provide a similar API and functionality in Python.

This package provides a Python package for calculating tissue-specificity metrics for gene expression.

Scikit-Optimize, or skopt, is a simple and efficient library to minimize (very) expensive and noisy black-box functions. It implements several methods for sequential model-based optimization. skopt aims to be accessible and easy to use in many contexts.

This package provides accelerated simulations and potentials of solids.

This package implements a functionality to create and manipulate plot legends for matplotlib.

This package is an implementation of the Promises/A+ specification and test suite in Python.

An efficient Python implementation of the Apriori algorithm, which uncovers hidden structures in categorical data

This package provides utilities for exploratory analysis of large scale genetic variation data.

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

This package provides tools to easily search and download French data from INSEE and IGN APIs. This data includes more than 150 000 macroeconomic series, a dozen datasets of local french data, numerous sources available on insee.fr, geographical limits of administrative areas taken from IGN as well as key metadata and SIRENE database containing data on all French compagnies.

The SciPy library is one of the core packages that make up the SciPy stack. It provides many user-friendly and efficient numerical routines such as routines for numerical integration and optimization.

This package provides fast numerical derivatives for analytic functions with arbitrary round-off error and error propagation.

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

This package provides a Python library for calculating Evapotranspiration using various standard methods.

Anndata is a package for simple (functional) high-level APIs for data analysis pipelines. In this context, it provides an efficient, scalable way of keeping track of data together with learned annotations and reduces the code overhead typically encountered when using a mostly object-oriented library such as scikit-learn.

PyMCubes is an implementation of the marching cubes algorithm to extract iso-surfaces from volumetric data. The volumetric data can be given as a three-dimensional NumPy array or as a Python function f(x, y, z).

Optimized einsum can significantly reduce the overall execution time of einsum-like expressions by optimizing the expression's contraction order and dispatching many operations to canonical BLAS, cuBLAS, or other specialized routines. Optimized einsum is agnostic to the backend and can handle NumPy, Dask, PyTorch, Tensorflow, CuPy, Sparse, Theano, JAX, and Autograd arrays as well as potentially any library which conforms to a standard API. See the documentation for more information.

This is a package for image processing with Dask arrays. Features:

• Provides support for loading image files.

• Implements commonly used N-D filters.

• Includes a few N-D Fourier filters.

• Provides some functions for working with N-D label images.

• Supports a few N-D morphological operators.