pandarallel allows any Pandas user to take advantage of their multi-core computer, while Pandas uses only one core. pandarallel also offers nice progress bars (available on Notebook and terminal) to get an rough idea of the remaining amount of computation to be done.

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.

python-pydicom is a Python library for reading and writing DICOM medical imaging data. It can read, modify and write DICOM data.

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.

Hist is an analyst-friendly front-end for boost-histogram.

Deepdish is a Python library to load and save HDF5 files. The primary feature of deepdish is its ability to save and load all kinds of data as HDF5. It can save any Python data structure, offering the same ease of use as pickling or numpy.save, but with the language interoperability offered by HDF5.

This package implements sparse arrays of arbitrary dimension on top of numpy and scipy.sparse. Sparse array is a matrix in which most of the elements are zero. python-sparse generalizes the scipy.sparse.coo_matrix and scipy.sparse.dok_matrix layouts, but extends beyond just rows and columns to an arbitrary number of dimensions. Additionally, this project maintains compatibility with the numpy.ndarray interface rather than the numpy.matrix interface used in scipy.sparse. These differences make this project useful in certain situations where scipy.sparse matrices are not well suited, but it should not be considered a full replacement. It lacks layouts that are not easily generalized like compressed sparse row/column(CSR/CSC) and depends on scipy.sparse for some computations.

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 a Python interface for the SCS (Splitting conic solver) library.

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 TDDA Python module provides command-line and Python API support for the overall process of data analysis, through tools that perform reference testing, constraint discovery for data, automatic inference of regular expressions from text data and automatic test generation.

Thi package implements a functionality for mean-preserving interpolation of 1D data (for example, time series) with splines.

pynetdicom is a Python package that implements the DICOM networking protocol. It allows the easy creation of DICOM SCUs and SCPs.

This package provides a Python interface to the QDLDL LDL factorization routine for quasi-definite linear system.

This package contains colormaps for commonly-used oceanographic variables. Most of the colormaps started from matplotlib colormaps, but have now been adjusted using the viscm tool to be perceptually uniform.

A Snakemake executor plugin for running SLURM jobs.

pyfma provides an implementation of fused multiply-add which computes (x*y) + z with a single rounding. This is useful for dot products, matrix multiplications, polynomial evaluations (e.g., with Horner's rule), Newton's method for evaluating functions, convolutions, artificial neural networks etc.

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

Clarabel.rs is a Rust implementation of an interior point numerical solver for convex optimization problems using a novel homogeneous embedding.

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

Xarray (formerly xray) makes working with labelled multi-dimensional arrays simple, efficient, and fun!

Xarray introduces labels in the form of dimensions, coordinates and attributes on top of raw NumPy-like arrays, which allows for a more intuitive, more concise, and less error-prone developer experience. The package includes a large and growing library of domain-agnostic functions for advanced analytics and visualization with these data structures.

Pandas is a Python package providing fast, flexible, and expressive data structures designed to make working with structured (tabular, multidimensional, potentially heterogeneous) and time series data both easy and intuitive. It aims to be the fundamental high-level building block for doing practical, real world data analysis in Python.

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.

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