Julia advertises itself as solving the "two-language problem". This assumes that people first write exploratory code in python or something similar, and then re

Julia advertises itself as solving the "two-language problem". This assumes that people first write exploratory code in python or something similar, and then rewrite it in Fortran etc. So in this scenario, Julia takes marketshare from both. Personally, I find that many Fortran codes are still used because they have been build for many years, and they can't be rewritten easily. On the other hand, new data science projects start all the time, and the transition to Julia is easy (and worth it in my opinion). That means that in my experience, Julia is mostly competing for marketshare with NumPy/SciPy/SKLearn/Pandas/R/Matlab.