Hackernoon logoHow I Used Python To Make Big Data Seem Small by@masseybr

How I Used Python To Make Big Data Seem Small

Brendan M. Hacker Noon profile picture

@masseybrBrendan M.

I work as an astrophysics research assistant. This job entails managing and manipulating large datasets. In order to accomplish this, I have to take subsets that mirror the larger dataset. In order to get my computer to be able to run my code without reaching a run time error, I have to take a subset of 10% of the original particles. This gives me a similar image to the original, while still being able to be run on my laptop. To do this, I use numpy.random. An example of how to do this is shown below.

Image of my code.

After I take the random particles, I create a mask of only 10% of the particles. This allows me to get my code to run in a quicker manner and allows me to maintain an accurate depiction of the dataset. These snapshots of the dataset provide valuable information and allows me to more quickly draw conclusions.

I hope you take the time to try this method out for yourself! Happy coding!

Thank you for reading!

Tags

Join Hacker Noon

Create your free account to unlock your custom reading experience.