I really like julia. For certain problems matlab and python are unworkable. People complain about time to first plot, but that doesn't matter too much to me. The problem is that plotting in general is just not as robust or user friendly as Matlab or matplotlib in python. You can call matplotlib, But it feels like a second class citizen. Plotting just needs to be better with a clear preferred method. There are tons of options.
I agree, there are a variety of plotting library options in Julia but they aren't nearly as developed/robust as matlab (e.g. quiver plots). There are a number of plotting functions that have completely changed how they work across versions and generally lack descriptive documentation. There have been several occasions where I had to give up and export my data into matlab to generate a plot. I also think the image analysis libraries are underdeveloped.
All of these have some exceptions, but are for the most part true:
high energy physics
lots of computational bio
fluid dynamics
rendering
In general, python and matlab really struggle in problems where you want maximum performance, but the most efficient algorithms aren't vectorized. In some cases, this is solvable by writing python libraries in C/C++, but especially in scientific fields, the end users are often the same people writing the algorithms, so they don't gain much from a python library if they have to do all the hard work in C++ anyway. Julia gives them a way more productive dev experience while still having a good user experience.
indeed, the grants (in the millions $) given to rewrite C++ or Python just to handle array (because for loop sucks) and ends up making monorepo blobs is jaw dropping -- while it's almost free in Julia, with 1/100 of the line of code and more flexibility we can match and beat even C++ code...
