Includes GitHub repo links to standalone projects I've created in descending order of completion.
Analyzing the most recent 2021 freeCodeCamp survey data instead of the 2017 one provided by the course, I independently sought to achieve the same project objective as Dataquest's guided project: identifying the two best markets for an e-learning company to advertise its product in.
Apart from using only the project objective as my guiding light, this project demonstrates construction of a large set of complex and informative visuals.
The original project 'Investigating Fandango Movie Ratings' uses data from 2015 and is very outdated as Fandango no longer uses the rating system the project is based on. This project diverges from the original by exploring ratings for current movie releases in theaters only.
Statistical elements, namely sampling, descriptive statistics (mean), and frequency distributions were incorporated to demonstrate lessons learned in Dataquest: Data Scientist's Part 6: Probability and Statistics leading up to the project. Much of the project also demonstrates web scraping to form our own dataset.
This is my adaptation and extended version of one of Dataquest's guided projects in which I've analyzed the 1,186 survey responses collected by FiveThirtyEight for their own original analysis.
The Day 52 project of /100-days-of-code was to create an Instagram bot to automate following any Instagram page's list of followers.
I followed the advised project structure of using a class function with three methods but had to write the solution code independently as the course solution code is very outdated.
The Day 50 project of /100-days-of-code was to create a Tinder bot to automatically match with profiles by liking or disliking.
I adapted this project by creating a Giphy bot instead to automatically match hashtags of GIFs with the user's search phrase. If they match, the GIF is saved to Favorites; otherwise, the GIF is skipped.
giphy.com was chosen to develop a family-friendly alternative while somewhat preserving the "swipe left or right" functionality of Tinder.
This is my adaptation and extended version of one of Dataquest's guided projects in which I've explored the relationships between demographics of New York high school students and its impact on their SAT scores.
This is my final project submission to conclude the CS50's Introduction to Programming with Python course at HarvardX. The project is a basic calorie tracker specifically for the menu items at In-N-Out Burger.