Much of the data analysis I am interested in involves public transportation, especially the Chicago Transit Authority (CTA) and data collected from the CTA’s Bus Tracker APIs. The Bus Tracker APIs are a collection of APIs that provide access to the near-real-time locations and estimated arrival times of CTA buses. The APIs also provided access to data detailing the paths of all of the CTA’s bus routes, the geospatial location of bus stops, and more.

In my next post, I plan to introduce one of the major projects I am working on that involves analyzing bus location data …

In my first real post, I'm going to share a construct that I use often. Below is a recipe for splitting delimited text files into separate files based on a chosen column's values using pandas. Suppose for example, you had a dataset of all reported Bigfoot sightings in the US over a 50-year period, and that one of the columns in the dataset listed the state where the sightings occurred. The following script could split the dataset into separate files for each state with a Bigfoot sighting.

First, load the data. Change the delimeter as needed.

import pandas as pd …

I have been gradually developing skills as a programmer and data scientist since graduating from college two years ago. I started by teaching myself Python in my free time, because I thought it would be useful to know. Many people I knew were using it after all! My learning was initially haphazard. I learned and understood basic Python techniques, but my knowledge felt purposeless. It wasn’t until I tried to solve a major problem from my day-to-day life with Python (a story I'll share later) that my knowledge gained purpose. By applying Python to something personal, my Python skills …