# What features will I miss in Julia?

**URL:** <https://discourse.julialang.org/t/what-features-will-i-miss-in-julia/3577>\
**Category:** New to Julia\
**Created:** [May 7, 2017, 12:47pm UTC](https://discourse.julialang.org/t/what-features-will-i-miss-in-julia/3577 "2017-05-07T12:47:58Z")\
**Posts on this page:** 1\
**Showing post:** 32

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**Author:** ![MikeInnes](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/mikeinnes/32/3656_2.png) [@MikeInnes](https://discourse.julialang.org/u/MikeInnes)\
**Post date:** [May 14, 2017, 12:10pm UTC](https://discourse.julialang.org/t/what-features-will-i-miss-in-julia/3577/32 "2017-05-14T12:10:17Z")

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R is _really_ comprehensive for the basic batteries-included stuff. If you’re throwing some data into a data frame, plotting and data munging, and R is working for that, you should stick with it. Some progress has been made on DataFrames.jl over the last few years, but mostly on working out the fine details of the design, so it’s not there yet.

Of course, if you hit problems with R it’s very likely that Julia can solve them for you. Just want to set expectations.

You might also miss some of R’s more exciting language features, like implicit laziness and the [superassignment operator](https://cran.r-project.org/doc/manuals/R-intro.html#Scope), which assigns variables into the _calling_ function (reading about R always reminds me of [Intercal](https://en.wikipedia.org/wiki/INTERCAL)). These are _mostly_ really horrible for writing maintainable code, but a lot of the Hadleyverse uses them for really nice APIs over dataframes; Julia struggles here a bit and the macro-based versions are ugly.

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