A bike share provider in the United States wanted to uncover bike share usage patterns. Data (> 10 million rows) from Chicago, New York City, and Washington, DC were analyzed and appropriate descriptive statistics computed utilizing Python , ATOM (IDE), and JSON data formats. If you would like a copy of the .py file please contact me.
This project was done as part of my course work at Udacity (www.udacity.com) for the Data Analyst Nano Degree (DAND).
Roll forward to 2018. I received the Data Analyst Nano Degree (DAND) from Udacity. I learned how to extract, wrangle and organize data. I uncovered patterns and insights using advanced statistical analysis, drew meaningful conclusions, and clearly communicated critical findings. I learned Python, R, SQL (refreshed SQL, I used to work for Oracle) and Tableau.
When I graduated from U of C, I went to work for Honeywell Information Systems (HIS) as a pre sales support analyst helping them market mainframe computers. I was amazed at how much money HIS invested in training me! I intimately learned how computers worked from a hardware and software perspective and ended up learning 5 programming languages (Fortran, Cobol, Pl1, and 2 assembler languages), 3 database systems, and 2 operating systems.
I graduated from the University of Calgary, in Alberta, Canada in 1977 in business. I took more computing science courses than I needed to as electives. My 4 year GPA was 3.3 and my 4th year GPA was 3.7. I returned to U of C many years later and took a molecular biology high intensity course. We extracted, cut, and ligated a Green Fluorescent Protein (GFP) into e Coli. Pretty cool to manipulate nature to create a glowing organism! This was part of my training for my life sciences company (United Bioinformatica Inc.).