Python is sufficiently readable, and with the right extension, it is sufficiently fast for vast majority of the purposes. For Julia to truly gain momentum, I think it needs a "killer app/library". However, I'm not sure what it would be that would not already be built for Python.
My personal killer app would be a significantly revamped plotting library/app. While matplotlib is great, it is fundamentally based on imaged-based plotting. The next generation of data visualization, imo, will likely be interactive. Having an interactive plotting library that allows you to produce publication-quality plots faster and simpler (think of all the time spent aligning text manually..) could be a big deal, but it could also not matter as no one else wants the same things I do.
Have a look at Makie.jl[1] in Julia. I've been using it for exploring large data sets recently. Ticks your boxes. Jupyter version is image based though, as Jupyter is inherently static. You could use Pluto.jl[2] to build a reactive page.
Thanks for the link. Makie.jl looks interesting. I didn't find it last time I looked into Julia. I'll get it a shot at some point to see how usable it is.
My personal killer app would be a significantly revamped plotting library/app. While matplotlib is great, it is fundamentally based on imaged-based plotting. The next generation of data visualization, imo, will likely be interactive. Having an interactive plotting library that allows you to produce publication-quality plots faster and simpler (think of all the time spent aligning text manually..) could be a big deal, but it could also not matter as no one else wants the same things I do.