Interactive data visualizations and plotting in Julia

Powerful convenience for Julia visualizations and data analysis

In-memory tabular data in Julia

Optimization functions for Julia

A Julia package for probability distributions and associated functions.

Forward Mode Automatic Differentiation for Julia

Statically sized arrays for Julia

Julia implementation of Data structures

HTTP for Julia

A benchmarking framework for the Julia language

Physical quantities with arbitrary units

Generalized linear models in Julia

Basic statistics for Julia

Convert julia objects to LaTeX equations, arrays or other environments.

Fast, continuous interpolation of discrete datasets in Julia

Error propagation calculator and library for physical measurements. It supports real and complex numbers with uncertainty, arbitrary precision calculations, operations with arrays, and numerical integration.

I was gonna maintain this package, but then I got high

A Julia package for evaluating distances (metrics) between vectors.

Combine ingredients for a plot

Types with default field values, keyword constructors and (un-)pack macros

Print data in formatted tables.

A data structure for mathematical optimization problems

Heterogeneous programming in Julia

Plotting for Julia based on GR, a framework for visualisation applications

Special mathematical functions in Julia

Root finding functions for Julia

Efficient implementation of struct arrays in Julia

Reusable array functionality for Julia's various GPU backends.

JSON parsing and printing

MacroTools provides a library of tools for working with Julia code and expressions.

An interface for tables in Julia

Hypothesis tests for Julia

An alternative interface for dictionaries in Julia, for improved productivity and performance

Calculus functions in Julia

Julia bindings to the FFTW library for fast Fourier transforms

Adaptive 1d numerical Gauss–Kronrod integration in Julia

AD-backend agnostic system defining custom forward and reverse mode rules. This is the light weight core to allow you to define rules for your functions in your packages, without depending on any particular AD system.

Specifying, fitting, and evaluating statistical models in Julia

Fast non-allocating calculations of gradients, Jacobians, and Hessians with sparsity support

Mathematical functions related to statistics.