Dataquest Projects

This will be a collection of all the projects I have completed from the Data Scientist Path at Dataquest. These will act more of a “proof of concept” for my skills as it continues to grow with each completed mission. My goal is to apply all that I have learned into a personal project that I find interesting once I completed the Data Scientist Path. Those will be in a seperate repository, so please keep a look out for them as I continue my journey down the Data Scientist Path.

  • Profitable App Profiles for the App Store and Google Play Markets

    Applying the python fundamentals to analyze the profitable apps within the Google Play market and Apple App Store.

  • Exploring Hacker News Post

    A continuation of applying the python fundamentals with the addition of some data cleaning and working with dates/times.

  • Exploring Ebay Car Sales Data

    Applying the fundamentals of the Pandas and NumPy libaries with some basic data cleaning the analyze the Ebay Car sales Data.

  • Visualizing Earnings Based on College Majors

    Exploring the matplotlib library to help visualize the Earnings on College Majors. Used a variety of charts and plots.

  • Visualizing The Gender Gap In College Degrees

    A continuation of exploring the matplotlib library. Applied more fine tunings to improve plot aesthetics. Also explored conditional plots and visualizing geographic data.

  • Clean and Analyze Employee Exit Surveys

    Applying more data cleaning and analysis tools with pandas library (data aggregation, transforming, and dealing with missing/duplcate data) to gain some insight on employees satisfaction.

  • Analyzing and Visualizing the Data

    Going through a more in-depth process to clean, combining multiple data sets, and analyzing the NYC High School Data. Explored various correlations student race, gender, AP exams and their SAT scores.

  • Star Wars Survey

    Cleaning and Analyzing Star Wars Survey data collected by FiveThirtyEight. Quick analysis to see which Star Wars movie was more popular and how each gender rated it differently.

  • Analyzing CIA Factbook Data Using SQLite and Python

    Applying the fundamentals of SQL and Python to analyze the CIA Factbook Data

  • Answering Business Questions using SQL

    A continuation of applying SQL fundamentals and Python to answer some business questions.

  • Designing and Creating a Database

    Learning to design and create a database.

  • Investigating Fandango Movie Ratings

    In October 2015, a data journalist named Walk Hickey analyzed movie ratings data and found strong evidence to suggest that Fandango’s rating system was biased and dishonest. Fandango later responded saying that the rounding was a bug in their system.

    With this project, we want to investigate whether Fandango is still rounding up their reviews or if they did in fact fix the bug.

  • Finding the Best Markets to Advertise In

    In this project, we are assuming that we are working for an e-learning company that offers courses on programming. Most of our courses are on web and mobile development, but we also cover many other domains, like data science, game development, etc. We want to promote our product and we’d like to invest some money in advertisement. The goal of this project is to find out two best markets to advertise our product in.

  • Winning Jeopardy In this project, we are work with a dataset of Jeopardy questions to figure out some patterns in the questions that could help us win Jeopardy

  • Mobile app for Lottery Addiction

    For this guided project, we will be playing with the idea of making an app that aims to prevent and treat gambling addictions. This app will help lottery addicts better estimate their chances of winning.