Back in the Real World


Wow! This blog has gathered some dust, innit? Need to pass through a hi power vacuum.

I have returned to this site after finally completing university!! Computer Science and Engineering degree, can’t get any more hacker than that! This means that now I have more free time to devote into other endeavors in my life…until I get a 9 to 5.

Space Rock Data

Insofar my time spent these past months, I was diving deep into the specialization field known as data science. Data science is an interdisciplinary field where scientists discern insights based on analyzing large datasets. In layman’s terms, we can predict the weather after looking at clouds for an entire day.

Humorous analogies aside, I was embroiled in a little project involving meteorites.

Of course not thinking about apocalyptic scenarios.

Meteorites are pieces of broken of space rocks, be it from asteroids or a planet’s surface, that end up falling down to Earth without burning out. I found a public dataset hosted by NASA in which holds details of registered meteorites.

Even meteorites have names.

As you can see, there is a LOT of data to chew on. Luckily I parsed through this beefy dataset with the programming language of Python. Most of the parsing involved cleaning up the dataset by eliminating any rows with missing values and other disqualifying criteria. Once the data was cleaned up, I sunk my fangs into analysis.

The Fun Part

This is where the fun starts. As far as meteorites go, they either fall down from Earth for us to witness in spectacular fashion, or we find them buried in our backyards. Of the former, we have Sikhote-Alin, the world’s largest fallen meteorite in terms of mass clocking in at a whopping 23 tons! Fell down straight to the Sikhote-Alin mountains in the then Soviet Russia in 1947.

Location of Sikhote-Alin.

Dialing back a couple of decades to 1920, a farmer found a whopper of a meteorite in his own farm as he was plowing the field in Namimbia, Africa. The meteorite known as Hoba was estimated to be 59 tons in mass and hypothesized to have landed on Earth over 80,000 years ago!

Location of Hoba

Now of course, with such meteorites, huge or tiny, there must be some intrinsic value to these meteorites! Hence why I developed functions to categorize the meteorites in generalized groups and assign them each a price based on their category and mass.

Meteorite money

Meteorites have three main classifications based on their composition: Stone, Stony-Iron and Iron. Of the Stone category, meteorites can originate from the Moon or Mars. These meteorites are extremely rare and highly sought after for scientific research. After all, it saves us the trip from collecting such rocks! The lunar and Martian meteorites are initially priced at $1,000 per gram. As for the other meteorites, I have conjured up a price guide after scouring for sources on the matter:

NOTE: These prices are NOT definitive because I am leaving out other pricing considerations.
Look at that $422k big boy!

Another Fun Part

And after creating two new columns of data, more data analysis is done! It just writes for itself!!

Stone is in style!
Lunar and Martian meteorites are as rare as they come.
The mean, or average, price of fallen meteorites is $797,683.60

Finishing up

This project took me two weeks to complete, and I learned a lot about the process of data science. Of course, this project can be a beginning to something more ambitious such as making a full blown website with the dataset! For a more detailed report, I will leave a link here. So for now, I got other projects cooking up unrelated to computers.

That is all! And as always… HACK TO THE FUTURE!!


A tropical monk i.e. an ocean man living through cyberspace.

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