Today was my first day of Metis Data Science Bootcamp. Having moved form California to New Jersey for this opportunity just a day ago, I felt a little bit jet-lagged (3-hour difference means you think you still have 3 hours of sleep, but you don’t) and tired. My commute from New Jersey to Metis in New York City was smooth and I found the WeWork building (the space where Metis is) pretty easily just a short and splendid walk away from the NYC Penn Station.

Right away our first day at Metis became intense. After important announcements, introductions, and rules were laid out, we dove right into working on our very first project. The tool of choice for the project is none other than Python Pandas library.

I have encountered Pandas before, but only briefly. Just as I felt then, I still feel now that this particular tool is a bit of an oddball when it comes to programmatic consistency. I used to be comfortable with accessing entries in a data structure, but now I always second-guess myself as plugging in indices does not always work with Pandas, and one has to resort to something like .loc or .iloc. Also, it is never clear when any Pandas function needs a set of parenthesis or not. I am sure there is an underlying logic to all of this, but I just don’t see it now.

Needless to say, at the end of the workday my team and I were pretty exhausted from just two exercises in Pandas! We have been warned during the introductory period today that such feelings are to be expected, so I am hoping at some point we will break the discomfort we definitely felt during the completion of the exercise.

Looking forward to what’s going to happen next!