Data Driven Finance Analyst Soccer Fanatic
View My LinkedIn Profile
# Welcome to My Portfolio
My final write up for Ian Steffensen 21 Days To Data project covering New York City crime data.
In this case study from Data Analytics Accelerator, I was prompted to analyze the State of Massachusetts education data. The main focuses were:
What schools are struggling the most?
How does class size affect college admission?
What are the top math schools in the state?
In this case study from Data Analytics Accelerator, I was prompted to analyze DoorDash sales over a 24 month period. The main focuses were:
How many people made purchases after campaign 6?
How much was spent in total during the 24 month period?
Who was the oldest user to make a purchase?
In this case study from Data Analytics Accelerator, I was promoted to analyst World Bank data for the IDA which provides loans to developing country’s. The main focus was understading how to use SQL to parse out the data needed to gain insights into which countries; receive the most loans, which countries repay loans fastes and more.
This project we focus our efforts in SQL using two data bases to pull in Patient health information and Patient demographic information. We used fuctions such as INNERJOIN, GROUP BY, ORDER BY, UNION, SUBQUERY and CONCAT to disect insights from the data. Had a great time trying my hand at SQL and look forward to using SQL on a more regular basis.
In this project I pulled all player stats from the 2022-2023 NBA season. I wanted to understand which teams and positions had the best 3 point percentages so that opposing teams could plan on defending the high efficent 3 point teams. I also wanted to see which players were best in points, assists and total rebounds by position. I also provide insights into which players scored the most and by which team. This was a really fun project as I love sports and always want to find interesting insights from the data.
This project was focused on using Python to provide our analysis. Being fairly new to using Python it gave me a great sense on how powerful Python is and hwo you can find your answers fairly quickly if you have the right line of code.