Computer Science Projects

For this project, I scraped data from a website containing information about countries, their capitals, populations, coordinates of their capitals, and other stats in order to answer questions about countries. After retrieving and organizing the data into readable files, I used SQL queries to ask questions about the data set. Most of the project involved mapping data from one file to the other, and organizing the data. I also wrote a program to find the distance between any two capitals in the world using their coordinate points and the formula for arc length. 

This project worked with data about the vaccination trends and records of every country in the world paired with data about their population, GDP per capita, and population density in order to describe correlations between factors. The code used dictionaries to answer and store questions about data, and included programs to read and describe data in CSV files. 

This project analyzed website data containing different stats of every country in the world. I first had to retrieve data from an html file, and read from that data to analyze correlations between the different statistics. Most of the correlations I was looking for were between literacy and GDP per capita, or GDP per capita and telephone usage. For this project I had to map data from different datasets to others, create and analyze data frames, and use linters to analyze and correct my own code. 

In this project I used data from multiple JSON and CSV files containing data on tweets of millions of users on Twitter. Most of the project concerned organizing the data from the different files into data structures that would be suitable for answering questions about trends in the data. I utilized tuples and handling errors in real-world datasets. I also programmed scatter plots and charts to describe trends in the data. 

In this project I used data from a CSV file concerning the cost, ownership, quality,  locations etc. of Airbnb homes in the United States. It was necessary for the code to be able to deal with more real-world, messy data sets with errors and missing values. It also utilized using string functions and sorting to order data. 

This project used a CSV file of the stats  of different Pokémon characters in order to program a simulation for a fight between any two Pokémon and predict the outcome. The code needed to read and retrieve data from a CSV file and use the different stats and probabilities to predict the outcome of a battle. 

In this project I examined and described the data from five different agencies in Madison: governments, gyms, restaurants, schools, and stores. All of the data to be analyzed was in a CSV file that I had to read and call in a Python notebook. My code found trends in the spending data of these agencies such as minimums and maximums and also projected spending for future years. 

This project used a CSV file of data on past hurricanes to analyze the speeds, duration, damage, economic effects, and patterns of hurricanes in the United States. The code utilized fundamental loop structures and basic string manipulations. 

This project dealt with multiple CSV files containing data about the year, actors, directors, duration, profit, and other data about thousands of movies. In this project I had to  integrate relevant information from various sources, and apply proper data structures to data in order to answer questions about the data. I also practiced binning data and using the Matplotlib module to plot trends and graphs to describe the data.