I think you're overestimating the amount of people using Numpy. There's no way it's more popular than Django, scientific computing is mainly academic anyways.
In addition the majority of scientist don't install numpy from pipy because it almost never works. Many use the numpy that comes with the distribution(example Ubuntu), a Python distribution (ActiveState, PythonXY, Enthought, Anaconda), or binary installers in Windows. So I would say that numpy usage numbers are a lot higher than what was shown in the other comment.
I am sorry, and at risk of downvotes, web dev is a much faster (dare I say it more fickle) crowd than science. Python is not a whole lot better than Golang, Ruby and of course, Node.js at this use case. Absolute numbers are not persuasive to me here. There are far fewer scientists than web devs (your stats imply ~ 1:2). Indeed I would venture to suggest that your data means that numpy punches well above its weight relative to other languages' science:webdev ratios. Let's not forget that Numpy and its direct linear ancestor, Numeric, has been dominant for more than a decade. Show me the Python web framework which can say the same. Flask/Bottle/Pyramid/Django/Tornado - pick your fashion.
Another point (to the grandparent posts): putting Numpy into a "science" pidgeon hole is erroneous. It is massively used in finance, engineering, bioinformatics, and statistics.
... and there can still be more scientists using Python than web devs using it.
Python web development is niche, despite the good frameworks. If you look at job postings, it's eclipsed by RoR, .NET, Java... maybe even PHP.
> Let's not forget that Numpy and its direct linear ancestor, Numeric, has been dominant for more than a decade. Show me the Python web framework which can say the same.
Django was released almost 10 years ago, and I remember it was already popular, a lot of people migrated from Plone.
The point is that Python's USP is Numpy. Python's USP is not web dev. If Python were to disappear there are many, many credible web dev alternatives. Not true Numpy. Take that from an R, Julia, C user. Numpy has the perfect combo of speed wrapped in an expressive language. I don't see that anywhere else.
And I think django tends to have more downloads than numpy. For django I tend to have a separate virtualenv so I know what to deploy on the server (so that's at least 2 downloads, plus one more for every new project I start). When I use python to calculate something/analyze data I don't care about deploying, and I think the scientific crowd is less likely to care about best practices in general.
Just a thought, not so certain myself how important it really is, but:
The web dev world also might mostly abandon Python very fast, vs once you got a foothold in academia there is a good chance you're going to keep that for years. Having a language in the universities' curricula gives exposure for a long time.
