Julia DataFrames 1.0 Released With An Improved Solution For Data Analysis – Analytics India Magazine

After the current launches of Julia 1.6 and JuliaSim for scientific machine studying within the cloud, Julia Computing has now launched DataFrames version 1.0. DataFrames.jl model 1.Zero gives Julia customers with a totally built-in, new and improved answer for information evaluation in Julia.

Julia Computing took to Twitter to announce the most recent launch. They tweeted, “DataFrames.jl 1.0 Release: Check out the new DataFrames.jl! The much anticipated 1.0 release has arrived, providing better, faster tools for working with tabular data in Julia https://dataframes.juliadata.org/stable/ #julialang”

DataFrames.jl gives a set of instruments for working with tabular information in Julia. Its design and performance are much like these of pandas (in Python) and information.body, information.desk and dplyr (in R), making it an incredible common objective information science device, particularly for these coming to Julia from R or Python. DataFrames.jl performs a central function within the Julia Data ecosystem, and has tight integrations with a variety of various libraries. 

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DataFrames.jl work properly with a variety of codecs, together with CSVs (utilizing CSV.jl), Apache Arrow (utilizing Arrow.jl) Stata, SPSS, and SAS recordsdata (utilizing StatFiles.jl), and studying and writing parquet recordsdata (utilizing Parquet.jl).

It may also be acknowledged that DataFrames.jl is a superb common objective device for information manipulation and wrangling. In addition to offering a secure API, there are vital efficiency enhancements on this launch that embody multi-threading and quicker joins, improved inference and extra.


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Ambika Choudhury

Ambika Choudhury

A Technical Journalist who loves writing about Machine Learning and Artificial Intelligence. A lover of music, writing and studying one thing out of the field. Contact: [email protected]

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