My last day as an Intern at Enthought, India.

For those of you who don't know about Enthought, which is probably all of you, it's provides "Scientific Computing Solutions" and I have been lucky enough to land an internship in the India office. It's been an amazing two months during which I have personally accomplished a lot! Two projects that I have wanted to work on for a very long time finally bore fruit over the last two month.

The first was my interest in making a map that showed the locations of universities around the world where astronomical research is pursued. I wanted to,  and will in the near future, add information about admission deadlines, application fees, expected GPA/GRE/TOEFL scores and what not for the universities and a way for people to select a date range or score range to decide what places to apply to. The months I spent looking and deciding on what universities to apply to could've been put to better use had there been a better way than to visit each department to look for the aforementioned details. While the list is of course not complete, the website is hosted off of Github and you can create an issue or submit a PR if you want/suggest any changes. Here is the latest blog post in which I talk about it, which in itself links to a couple of more blog posts, and the website in itself is hosted here.

Secondly, I wanted to make a network/graph that depicted collaborations between universities. Checkout the website to get an idea of what I have in mind. At the bottom of that page, there is a bouncy, touchy, network graph. In that graph, each dot/node represents a researcher at a university/lab. The lonely triangles, squares, pentagons and what not that you see floating around independent of one another are individual papers. The lines in those shapes represent the fact that the researchers of this paper collaborated with one another. Now, roughly in the middle of the graph, there is a biggish blob, containing a lot of dots/nodes. If you look closely, you can say that this mess is actually made up of individual squares/triangles/pentagons/etc sharing one or maybe two nodes/edges. This means that researchers at these common universities are more collaborative than the rest of the lonely dots/nodes/universities. I want to quantify this network to learn more things about it but that'll take some more time. Again, if you have any comments/suggestions/corrections that you would like to suggest, you can open an issue/Pull Request on the Github repository that hosts this work.

I just wanted to highlight those two things because they are what I am most proud of. There are a couple of more things that I worked on but those are relatively incomplete so I'll try working on them next month to bring them to a satisfiable checkpoint and then write about them! And I'll keep mum about what I did here at the company because I really don't want to get into trouble because I don't know what's acceptable and what's not!

And I have learnt a great deal about Python in the last two months. It's been a steep learning curve and there have been days when I felt like I was rolling back down the hill instead of making progress or even staying at the same location! But still, having reached the summit, it all feels worth the effort because what I can see from here is spectacular. I have been a little lazy because I haven't written about these new Python quirks I have learnt but I will slowly start doing that starting next month. Anyway, I guess that's all for now. Later.

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