# Benchmarking ways to write/load DataFrames IndexedTables to disk

**URL:** <https://discourse.julialang.org/t/benchmarking-ways-to-write-load-dataframes-indexedtables-to-disk/8973>\
**Category:** Data\
**Created:** [February 10, 2018, 1:13pm UTC](https://discourse.julialang.org/t/benchmarking-ways-to-write-load-dataframes-indexedtables-to-disk/8973 "2018-02-10T13:13:55Z")\
**Posts on this page:** 1\
**Showing post:** 5

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**Author:** ![zhangliye](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/zhangliye/32/3208_2.png) [@zhangliye](https://discourse.julialang.org/u/zhangliye)\
**Post date:** [February 11, 2018, 3:00am UTC](https://discourse.julialang.org/t/benchmarking-ways-to-write-load-dataframes-indexedtables-to-disk/8973/5 "2018-02-11T03:00:03Z")

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It is a very useful benchmark! I am once suffered from this.  
I tried to use Julia for a data analysis project, which should process a large amount of CSV files. There are more than 3000 CSV files a day and we have to process about two-years’ data. At last, I used Dask in Python to do this.  
It would be useful to include the comparison of Pandas. Thanks for your work.

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