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Utility library for working with CSV and other delimited files in the Julia programming language
Developer toolsJulia · PythonGitHub @JuliaDataSelf-installOwner unconfirmed
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CSV.jl reads and writes comma-separated and other delimited text data in Julia.
It implements the Tables.jl interface.
Install the registered release from the Julia REPL:
CSV.jl 1.0 requires Julia 1.10 or later. See the
0.10 to 1.0 migration guide before you update an
existing application.
Use CSV.read("input.csv", DataFrame) after you load DataFrames.jl. Use
CSV.Rows to process one row at a time, CSV.Chunks to process batches, or
CSV.lazy to index a source before you choose which cells to parse.Read the full README ↗CSV.jl reads and writes comma-separated and other delimited text data in Julia. It implements the Tables.jl interface.
Install the registered release from the Julia REPL:
] add CSV
CSV.jl 1.0 requires Julia 1.10 or later. See the 0.10 to 1.0 migration guide before you update an existing application.
using CSV
file = CSV.File("input.csv")
CSV.write("output.csv", file)
Use CSV.read("input.csv", DataFrame) after you load DataFrames.jl. Use
CSV.Rows to process one row at a time, CSV.Chunks to process batches, or
CSV.lazy to index a source before you choose which cells to parse. With
DataDecimals.jl loaded, types=Dict(:amount => DataDecimals.Decimal64{2})
reads a column as exact decimals; CSV.jl does not infer decimal types.
main branch.Use GitHub Issues for bug reports, feature requests, and questions.
The CSV.jl 1.0 internal rewrite contains substantial generative-AI contributions. Claude drove the initial rewrite. Codex performed review, fixes, documentation, and validation. Human maintainers must hand-review these changes and own the final approval.
load and save integration.