You are actually right but you are missing the point. Python doesn't compete with Fortran, it supplements it. With tools such as f2py, it is very easy to call fortran code from python (and there are tools that make it easy to call C/C++). This combination really potentializes both languages: bottlenecks use Fortran/C/C++ and the rest python. This combination is already popular: numpy/scipy is basically that.
I don't think that being easy is python's main advantage. Using a dynamic environment were you can type code that gets executed immediately and were you can explore the data is a really big help. On the other hand, the same could be done with R, Matlab, Octave or Scilab and it is done. In some ways these languages are better suited than python because they were designed to do math, or more specifically matrices/arrays very well and might have better syntax for that. But then doing anything else increasingly becomes a pain once the problem becomes larger or more complex and that's where, IMHO, python gains an advantage. Better module/OOP environment, better GUI,etc.
By the way, I work on scientific computing, using spectral element methods in computational fluid dynamics and I also work on a wind tunnel and I do lot's of data acquisition and processing. Right now I use C++ for lower level stuff (and bottlenecks) and R. I have been seriously considering switching to Python to have an easier environment to maintain.