Comments on text and visualisations

[czgdp1807]

1. https://github.com/numpy/numpyorg-benchmarks/tree/main/nbody_problem#numpy-benchmarks - It would be great if some more explanation can be added here like what is meant by realistic situation, the metrics used (time and memory, etc), which libraries, languages are used for comparison. I think that the motivation here is to measure performance of NumPy in algorithmic solutions of hard problems.
2. https://github.com/numpy/numpyorg-benchmarks/tree/main/nbody_problem#usage - I would suggest to remove sudo from all the commands. Ideally, users should install the dependencies in their environments not requiring sudo access. If it's a compulsory requirement then it should be mentioned in the README.
3. https://github.com/numpy/numpyorg-benchmarks/tree/main/nbody_problem#writing-benchmarks - Good points are highlighted here.
4. https://github.com/numpy/numpyorg-benchmarks/tree/main/nbody_problem/images - The graph is good here. It would look better if we use line graphs to show trends of how time varies with varying scale (nParticles). Putting all of the data in one line graph would show how every technology (libraries, languages, compilers) compare with each other.
5. https://github.com/numpy/numpyorg-benchmarks/blob/main/nbody_problem/nbody_concept.md - The explanation has technical details but can be presented in a better way via PDFs and if that's not possible then screenshots of equations will also work.
6. https://github.com/numpy/numpyorg-benchmarks/tree/main/nbody_problem/data - May be README file explaining the format of the data will be good here.