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https://github.com/JuliaData/CSV.jl

Utility library for working with CSV and other delimited files in the Julia programming language
https://github.com/JuliaData/CSV.jl

csv julia

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Utility library for working with CSV and other delimited files in the Julia programming language

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README 

        

# CSV



[![CI](https://github.com/JuliaData/CSV.jl/actions/workflows/ci.yml/badge.svg?branch=main)](https://github.com/JuliaData/CSV.jl/actions/workflows/ci.yml)

[![codecov](https://codecov.io/gh/JuliaData/CSV.jl/branch/master/graph/badge.svg)](https://codecov.io/gh/JuliaData/CSV.jl)

[![deps](https://juliahub.com/docs/CSV/deps.svg)](https://juliahub.com/ui/Packages/CSV/HHBkp?t=2)

[![version](https://juliahub.com/docs/CSV/version.svg)](https://juliahub.com/ui/Packages/CSV/HHBkp)

[![pkgeval](https://juliahub.com/docs/CSV/pkgeval.svg)](https://juliahub.com/ui/Packages/CSV/HHBkp)

[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.8004128.svg)](https://doi.org/10.5281/zenodo.8004128)



*A fast, flexible delimited file reader/writer for Julia.*



## Installation



The package is registered in the [`General`](https://github.com/JuliaRegistries/General) registry and so can be installed at the REPL with `] add CSV`.



## Documentation



- [**STABLE**][docs-stable-url] — **most recently tagged version of the documentation.**

- [**LATEST**][docs-latest-url] — *in-development version of the documentation.*



## Project Status



The package is tested against Julia `1.0`, current stable release, and nightly on Linux, OS X, and Windows.



## Contributing and Questions



Contributions are very welcome, as are feature requests and suggestions. Please open an

[issue][issues-url] if you encounter any problems or would just like to ask a question.



[docs-latest-img]: https://img.shields.io/badge/docs-latest-blue.svg

[docs-latest-url]: https://JuliaData.github.io/CSV.jl/latest



[docs-stable-img]: https://img.shields.io/badge/docs-stable-blue.svg

[docs-stable-url]: https://JuliaData.github.io/CSV.jl/stable



[ci-img]: https://github.com/JuliaData/CSV.jl/workflows/CI/badge.svg

[ci-url]: https://github.com/JuliaData/CSV.jl/actions?query=workflow%3ACI+branch%3Amaster



[codecov-img]: https://codecov.io/gh/JuliaData/CSV.jl/branch/master/graph/badge.svg

[codecov-url]: https://codecov.io/gh/JuliaData/CSV.jl



[issues-url]: https://github.com/JuliaData/CSV.jl/issues



## Alternatives



There are several other packages for reading CSV files in Julia, which may suit your needs better:



* The standard library contains [DelimitedFiles.jl](https://docs.julialang.org/en/v1/stdlib/DelimitedFiles/), at least until Julia 1.8.

  This returns a `Matrix` rather than a [Tables.jl](https://github.com/JuliaData/Tables.jl)-style container, thus works best for files of homogeneous element type. 

  On large files, CSV.jl will be much faster.



* [CSVFiles.jl](https://github.com/queryverse/CSVFiles.jl) uses the [FileIO.jl](https://github.com/JuliaIO/FileIO.jl)'s `load` / `save` API,

  but otherwise has similar goals. Like CSV.jl, it works with [Tables.jl](https://github.com/JuliaData/Tables.jl) objects such as DataFrames.



* [DLMReader.jl](https://github.com/sl-solution/DLMReader.jl) also aims to be fast for large files,

  closely associated with [InMemoryDatasets.jl](https://github.com/sl-solution/InMemoryDatasets.jl).



* [Pandas.jl](https://github.com/JuliaPy/Pandas.jl) wraps Python's [pandas](https://pandas.pydata.org) library (using [PyCall.jl](https://github.com/JuliaPy/PyCall.jl)).

  This is a closer cousin of [DataFrames.jl](https://github.com/JuliaData/DataFrames.jl), but builds in the ability to read/write CSV files.