TableTraits defines a generic interface for tabular data.

This package provides a set of tools for working with tabular data in Julia. Its design and functionality are similar to those of Pandas from Python or data.frame, data.table and dplyr from R, making it a great general purpose data science tool, especially for those coming to Julia from R or Python.

BufferedStreams.jl provides buffering for IO operations. It can wrap any IO type automatically making incremental reading and writing faster.

This package provides tools to express a design pattern for dealing with large/ nested structures, as in machine learning and optimisation. For large machine learning models it can be cumbersome or inefficient to work with parameters as one big, flat vector, and structs help in managing complexity; but it is also desirable to easily operate over all parameters at once, e.g. for changing precision or applying an optimiser update step.

This package provides these irrational constants:

• twoπ = 2π

• fourπ = 4π

• halfπ = π / 2

• quartπ = π / 4

• invπ = 1 / π

• twoinvπ = 2 / π

• fourinvπ = 4 / π

• inv2π = 1 / (2π)

• inv4π = 1 / (4π)

• sqrt2 = √2

• sqrt3 = √3

• sqrtπ = √π

• sqrt2π = √2π

• sqrt4π = √4π

• sqrthalfπ = √(π / 2)

• invsqrt2 = 1 / √2

• invsqrtπ = 1 / √π

• invsqrt2π = 1 / √2π

• loghalf = log(1 / 2)

• logtwo = log(2)

• logten = log(10)

• logπ = log(π)

• log2π = log(2π)

• log4π = log(4π)

PositiveFactorizations is a package for computing a positive definite matrix decomposition (factorization) from an arbitrary symmetric input. The motivating application is optimization (Newton or quasi-Newton methods), in which the canonical search direction -H/g (H being the Hessian and g the gradient) may not be a descent direction if H is not positive definite.

This package provides a convenient function form of the conditional ifelse. It is similar to Core.ifelse but it is extendable.

This package provides a collection of colorschemes.

This package provides a collection of useful bit-twiddling tricks, ready to use as functions, with detailed documentation and example real-world use cases.

This package provides an interface to line search algorithms implemented in Julia.

This package provides an alternative interface for dictionaries in Julia, for improved productivity and performance.

The Tables.jl package provides simple, yet powerful interface functions for working with all kinds tabular data.

PlotThemes is a package to spice up the plots made with Plots.jl.

This package contains the testset from Julia, packaged into a loadable module.

This is a small package to make it easier to type LaTeX equations in string literals in the Julia language.

This package provides Julia implementation for reading and writing FITS files, based on the cfitsio library.

This package provides tools for working with the basic calculus operations of differentiation and integration. The Calculus package produces approximate derivatives by several forms of finite differencing or produces exact derivative using symbolic differentiation. It can also be used to compute definite integrals by different numerical methods.

This Julia package provides several utilities for working with tree-like data structures. Most importantly, it defines the children method that any package that contains such a data structure may import and extend in order to take advantage of any generic tree algorithm in this package.

This package provides some common helper functions that make it easier to implement various Base.show functions for types that participate in the TableTraits.jl ecosystem.

This package provides a canonical set of default initial values and identity elements for Julia.

This is a twin package to ImageCore with functions that are used among many of the packages in JuliaImages. The main purpose of this package is to reduce unnecessary compilation overhead from external dependencies.

This package enables the Markdown / MkDocs backend of Documenter.jl.

This minimalistic package serves as the foundation for other SIMD packages in Julia.

Configurations.jl provides a macro @option to let you define structs to represent options/configurations, and serialize between different option/configuration file formats such as TOML.