[Daishiman]

The vast majority of code ever written is not performance-sensitive, but is very sensitive to getting produced rapidly.

If you need to quickly perform some statistical analysis, you'd be hard pressed to be more productive in anything else over Python+NumPy or R.

[pjmlp]

Statistical analysis is a domain I am more than happy not to care about, it was already enough what I had to bare with during my engineering degree.

Still, given that Python and R are just glue languages for C, C++ and Fortran libraries, I rather use the source directly, or bindings to typed languages.

Modern C++, .NET, Java or ML based languages are just as effective,.

And here is a fun fact, I have spent 4 years working for life sciences companies, where several researchers I got to know, would do statistical analysis in Excel + VBA, eventually using VB.NET as well for more complicated stuff.