Among the many use cases Python covers, data analytics has become perhaps the biggest and most significant. The Python ecosystem is loaded with libraries, tools, and applications that make the work of scientific computing and data analysis fast and convenient.

But for the developers behind the Julia language — aimed specifically at “scientific computing, machine learning, data mining, large-scale linear algebra, distributed and parallel computing”—Python isn’t fast or convenient enough. Julia aims to give scientists and data analysts not only fast and convenient development, but also blazing execution speed. 

https://www.infoworld.com/article/3241107/julia-vs-python-which-is-best-for-data-science.html