# Fastest way to parse a string of numbers

**URL:** <https://discourse.julialang.org/t/fastest-way-to-parse-a-string-of-numbers/16720>\
**Category:** General Usage\
**Tags:** question, parsing\
**Created:** [October 24, 2018, 8:23am UTC](https://discourse.julialang.org/t/fastest-way-to-parse-a-string-of-numbers/16720 "2018-10-24T08:23:09Z")\
**Posts on this page:** 1\
**Showing post:** 9

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**Author:** ![jonjilla](https://avatars.discourse-cdn.com/v4/letter/j/7ba0ec/32.png) [@jonjilla](https://discourse.julialang.org/u/jonjilla)\
**Post date:** [October 27, 2018, 7:43am UTC](https://discourse.julialang.org/t/fastest-way-to-parse-a-string-of-numbers/16720/9 "2018-10-27T07:43:54Z")

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I was wondering more about a mixed string like in this question which hasn’t been answered yet

> [@Help with string mapping from input](https://discourse.julialang.org/t/help-with-string-mapping-from-input/16752):
>
> Hello I’m trying to import a custom text file that isn’t well aligned and a mixture of data types. The input data looks something like this inputtext = ["ABC=1,2,3,cats,dogs","DEF=1,apples,oranges,4,5,6.78,bananas","XYZ=Julia,R,Python,9.9999"] Currently, my code is very brute force manual and I was hoping that there was a better way to generate this, perhaps with some sort of mapping function ABC = DataFrame(a=Int64[],b=Int64[],c=Int64[],animal=String[],put=String[]) DEF = DataFrame(a=Int64…

For exampe, a string of mixed types like “1,apples,oranges,4,5,6.78,bananas”. Is there a way to map it into

Int,String,String,Int,Int,Float,String

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