# Help improving the speed of a DataFrames operation

**URL:** <https://discourse.julialang.org/t/help-improving-the-speed-of-a-dataframes-operation/107615>\
**Category:** Performance\
**Tags:** performance, query, dataframes\
**Created:** [December 14, 2023, 3:20pm UTC](https://discourse.julialang.org/t/help-improving-the-speed-of-a-dataframes-operation/107615 "2023-12-14T15:20:21Z")\
**Posts on this page:** 1\
**Showing post:** 18

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**Author:** ![abelsiqueira](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/abelsiqueira/32/47269_2.png) [@abelsiqueira](https://discourse.julialang.org/u/abelsiqueira)\
**Post date:** [December 18, 2023, 3:02pm UTC](https://discourse.julialang.org/t/help-improving-the-speed-of-a-dataframes-operation/107615/18 "2023-12-18T15:02:02Z")

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> @pdeffebach: I still think that a version with `leftjoin` and DataFramesMeta.jl’s `@with` is going to be the simplest and most effective.

See my comment above, for ~100k rows in each data frame, my VSCode crashed. Running on terminal gave me segfault.

> It’s hard to tell exactly without a full MWE

Is the code I put on the first post not working or do you mean a large case?

And once more, the context is another problem posted here: [Speeding up JuMP model creation with sets that depend on other indexes](https://discourse.julialang.org/t/speeding-up-jump-model-creation-with-sets-that-depend-on-other-indexes/107333)

I currently don’t use anything close to a data frame. Instead, I have a dictionary to compute the indexes that I have to sum for each row of `df_cons`.  
My expectations are that using a linear structure will be better (`df_cons`). However, computing the `incoming` column of the linear structure is proving to be slower than the dictionary approach.  
I.e., JuMP is slower because I have the dictionaries instead of the linear indexes, but computing the linear indexes are slower than JuMP, so maybe it is what it is.

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