Complaining about 1-based indexing in Julia is so... 4 years old! Just use OffsetArrays, and you can use 0 based, or whatever base floats your boat (start underwater with -5, for example!)
Back 5.5 years ago, I used to complain about the 1 based indexing and the column-major structure of matrices in Julia (both like Fortran), however, those issues have been solved by OffsetArrays and PermutedDimsArrays, giving far more flexibility that is possible in most other languages.
It's silly to keep bringing up the issue of one based indexing, when you can use any integer as the base, just like Fortran 90 (so you can index by -5..5, for example).
For some things, 0 based does make things easier, sure, but you can do that easily in Julia (and more!)
One thing that is pretty great about Pluto.jl, is how responsive the author is (Fons van der Plas, or @fonsp on GitHub).
I've been able to get great suggestions from him (as well as the fast growing community of Pluto users) on Zulip discussion group for Julia (https://julialang.zulipchat.com)
I've also switched to using Pluto, shortly after seeing the presentation during JuliaCon. It is still rough around the edges, but I've found it a lot easier to deal with than Jupyter, quite frankly.
You'll also save a lot of effort in future endeavors, IMO.
Remember, once you've switched to Julia, Python is still only a `using PyCall` and `pyimport` away!
I'm having a lot of fun with Pluto.jl and PlutoUI.jl this past week, it's so easy to use and add interactivity. There are still some rough edges, but that's what PRs are made for!
I haven't seen that at all - many Julia programmers are (or were) also Python programmers.
I think there is a lot of respect in the Julia community for Python & the Python ecosystem.
There have even been a number of Julia talks at various PyCons over the past few years.
Python's ecosystem is great - but Julia's is growing incredibly fast, and in some cases Julia has already surpassed what is available in other languages (for example, take a look at the whole differential equations ecosystem: https://github.com/JuliaDiffEq).
Also, Python's ecosystem is only a 'pyimport(name)' away (using the PyCall.jl package). Same thing is true for R and a number of other languages (RCall.jl, JavaCall.jl, etc.)
I've been using SymPy, QisKit, matplotlib and other Python packages with no problem in Julia.
I've been using Julia for non-scientific computing programs for almost 5 years now, and (especially now that it is stable since the 1.0 release) have found it well suited for general programming as well.
Having a language that is easy to write (like Python), runs fast (like C/C++), and incredibly flexible & expressive (like Lisp) makes programming fun again!
I've been programming in the Julia language for the past 4.5 years, and as somebody who has lived through the problems with Julia's name (getting incessantly teased by coworkers, friends, even my wife and kids, because of how much I like the Julia language and tend to gush about my enthusiasm for it), I think @StefanKarpinski really has hit the nail on the head here.
His suggestion of "Ballet" is very good, it still conveys all of the grace, elegance and beauty of ballet. Also, ballet dancers of all genders are pretty kickass athletes as well as incredible artists and performers.
Come to think about it, maybe I shouldn't recomend them changing from "Ballerina" to "Ballet", because if I came up with a new language, "Ballet" would definitely be pretty cool, and I'd want to use it myself!