How often do you get excited when your phone vibrates and an email notification shows up? If you're like me, not very. Much like how I only seem to receive spam calls on my phone, almost all of the emails I receive on a daily basis are not important to …

This is a short post, showcasing my solution to problem 22 on Project Euler. I worked on this problem over lunch with a few co-workers, and they found the solution useful. If you find this article, I hope it is useful to you as well.

The prompt for this exercise …

The Advent of Code 2019 challenge is open. These are my solutions to the problems presented on day 1.

Part one

Asks us to figure out how much fuel is required to lift a given spacecraft module if we know its' mass.

import math
import sys

def calculate_fuel_cost(mass):
    return …

This is part of a series of articles on how to work with large data

The first method I want to explore when working with large data, since we cannot use RAM, is to use a database for our dataset. Databases are a staple of data processing and analysis, and …

Here's a question: how do you analyze data that is too big to fit into memory?

Those of you that have worked with pandas before are probably intimately familiar with the following syntax, which reads csv file into a DataFrame variable

import pandas as pd
df = pd.read_csv('dataset.csv …

Here's a hypothetical situation. Suppose you're starting a new project and you want to use the requests library. Installing requests also installs the libraries that it depends on. Should you be explicit and pin the versions of all installed libraries (equivalent to the output of pip freeze)

certifi==2018.4 …

If you're like me, you dislike doing repetitive tasks when a script could have just as easily done the work for you. For example, starting a jupyter server on my local machine requires me to do the following:

1. open a terminal
2. source the virtual environment I use for jupyter work …