# Julia is unable to load CSV files from the Kaggle competition

**URL:** <https://discourse.julialang.org/t/julia-is-unable-to-load-csv-files-from-the-kaggle-competition/12830>\
**Category:** Performance\
**Tags:** question, package, csv\
**Created:** [August 2, 2018, 4:34pm UTC](https://discourse.julialang.org/t/julia-is-unable-to-load-csv-files-from-the-kaggle-competition/12830 "2018-08-02T16:34:18Z")\
**Posts on this page:** 1\
**Showing post:** 5

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**Author:** ![xiaodai](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/xiaodai/32/15937_2.png) [@xiaodai](https://discourse.julialang.org/u/xiaodai)\
**Post date:** [August 3, 2018, 5:25am UTC](https://discourse.julialang.org/t/julia-is-unable-to-load-csv-files-from-the-kaggle-competition/12830/5 "2018-08-03T05:25:12Z")

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> [@Benchmarking ways to write/load DataFrames IndexedTables to disk](https://discourse.julialang.org/t/benchmarking-ways-to-write-load-dataframes-indexedtables-to-disk/8973):
>
> Update 2018-Feb-19: added R feather and Pandas; thanks to @zhangliye for the pandas code For Julia, JLD.jl has the fastest write-solution and I have used it via the ultra-convenient FileIO.jl. However for interop with other packages, the slightly slower Feather.jl is also a good choice, also it may be arguable that you read data more often than you write, so Feather.jl’s superior read-speed will be essential. However, R’s feather is faster than Julia’s. The read and write speed seem to scale …

Check out the post for “inspiration”, I often find that using R’s data.table’s `fread` is the fastest.

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