朱莉娅数据框与Python pandas [英] Julia Dataframes vs Python pandas

问题描述

我当前正在使用python pandas，想知道是否有一种方法可以将熊猫的数据输出到茱莉亚Dataframes中，反之亦然. (我认为您可以使用Pycall从Julia中调用python，但是我不确定它是否适用于数据帧)是否有一种方法可以从python中调用Julia并将其纳入panda的数据帧中? (而不保存为csv等其他文件格式)

I am currently using python pandas and want to know if there is a way to output the data from pandas into julia Dataframes and vice versa. (I think you can call python from Julia with Pycall but I am not sure if it works with dataframes) Is there a way to call Julia from python and have it take in pandas dataframes? (without saving to another file format like csv)

除了超大型数据集和运行具有许多循环(例如神经网络)的事物外，使用Julia数据框比熊猫更有利吗?

When would it be advantageous to use Julia Dataframes than Pandas other than extremely large datasets and running things with many loops(like neural networks)?

推荐答案

因此为此开发了一个库

PyJulia是一个用于使用Python 2和3与Julia交互的库

PyJulia is a library used to interface with Julia using Python 2 and 3

https://github.com/JuliaLang/pyjulia

这是实验性的，但有些奏效

It is experimental but somewhat works

第二，朱莉娅还有pandas的前端，它是pandas.jl

Secondly Julia also has a front end for pandas which is pandas.jl

https://github.com/malmaud/Pandas.jl

它看起来只是熊猫的包装，但是您可以使用julia的并行功能执行多个功能.

It looks to be just a wrapper for pandas but you might be able to execute multiple functions using julia's parallel features.

至于哪个更好，根据此

As for the which is better so far pandas has faster I/O according to this reading csv in Julia is slow compared to Python

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