# Getting julia support to Kaggle

**URL:** <https://discourse.julialang.org/t/getting-julia-support-to-kaggle/2121>\
**Category:** Community\
**Tags:** statistics\
**Created:** [February 15, 2017, 4:57pm UTC](https://discourse.julialang.org/t/getting-julia-support-to-kaggle/2121 "2017-02-15T16:57:53Z")\
**Posts on this page:** 1\
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**Author:** ![kevbonham](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/kevbonham/32/216165_2.png) [@kevbonham](https://discourse.julialang.org/u/kevbonham)\
**Post date:** [February 15, 2017, 4:57pm UTC](https://discourse.julialang.org/t/getting-julia-support-to-kaggle/2121/1 "2017-02-15T16:57:53Z")

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Not precisely where this discussion should sit, but this seems a good place to start.

[Kaggle.com](http://kaggle.com) is a neat site for data science, hosting competitions in data analysis and machine learning, as well as instructional material and learning resources. Users can also post code and descriptive text in jupyter notebooks and run them as “kernels” on Kaggle’s servers.

The site hosts predominantly python and R code, but in principle it supports julia code. That said, it’s clear this isn’t actively supported, since the jupyter notebooks don’t give a julia option, and even scripts that run their example code fail out with an error when `using DataFrames` ([see here](https://www.kaggle.com/product-feedback/28409#post159596) for kaggle discussion).

I’m wondering if it would be worth it for someone at julia computing or someone with more knowledge than me to reach out to Kaggle and offer some support - they don’t currently have the user demand to work hard on their end, but it seems like it could be a useful avenue to increase interest among users in using julia for data science.

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