My project uses data from the 2019 MLB season to create visualizations. The first visualization allows the user to enter a threshold value for a statistic, and the program prints all players with a statistic value above/below the threshold value. The second statistic uses data from all players to display a possible correlation between two statistics. The final visualization takes two players as input from the user and compares them, creating a graph and printing out which stat each player leads in. - https://drive.google.com/file/d/1fAIQcn-ke7TgxxlHXKhber26SuChc-Wf/preview
A plot of all shots taken by NBA players who have played since the 2000-2001 season. Users can choose individual players and which season that they would like to have plotted. Shots can also be filtered by which quarter they were taken in or by the shot type (2 or 3 pointer) - https://drive.google.com/file/d/12AY45DveDjmUUG7nOvKOFvL3YeQjSmac/preview
My project compares population data and looks for correlations between things like population and birth rates. The final visualization is interactive and allows the user to see for themselves the graphical comparison between different statistics. - https://drive.google.com/file/d/1dbz9UovxO759VbwNyIKSG5C5imq3hLVP/preview
My project compares the winning percentages of teams as the home team and as the away team from 2019. The user can select one of the Power 5 conferences (ACC, BIG 12, BIG 10, PAC-12, and SEC), and the program will display a chart of each team with its corresponding home and away winning percentages. The user can select a form of plotting (Bar graph, histogram, pie chart, and box plot), and the program will display a plot which can be used to show the advantage of having the home field in college football. You can look at various conferences and plots to see which conference it may have the biggest impact on. - https://drive.google.com/file/d/11WfQgs4DIw0ExZoC8i4itCisImkqzGua/preview
I web-scraped data from https://www.worldometers.info/coronavirus/ to analyze the progression of COVID-19. I'll be looking at the total number of cases, total deaths, and total recovered per country that is listed in this table for the top five countries with the most number of cases (USA, Spain, Italy, France, and Germany). The user can then interact with the data by either plotting the total number of cases, deaths, or persons recovered per country against time. The user is also able to decide what kind of visualization they would like to see; this will either be a scatter plot, choropleth map, or a geo-scatter map. - https://drive.google.com/file/d/1_3MWXbh5RcUZTpKX0-C_4JrOF2FW2mU8/preview
My project shows the spread of Coronavirus starting from March 1st up until April 25th. It displays choropleth maps with confirmed cases as raw values and as percentages of each country's population. It also displays death rates by demographics and gives a visualization for the estimated deaths by the user's choice of demographic combination. - https://drive.google.com/file/d/1aCsmV9BIxz-eB9z386n3iKAGd4bI7fut/preview
My project was based on combing NYC MTA traffic data along with NOAA weather data in order to find the best bridge or tunnel to use when travelling in or out of New York City based on the weather conditions for a given day. I had two components a "back-end" and a "front-end." The back-end was used to grab, clean, and parse the data while the front end used the formatted data I had made to visualize it interactively. - https://drive.google.com/file/d/1ShrobAZadJwzc28HR86RUjTx6Kqm3AFH/preview
My project examines the relationships between payroll, attendance, and success for each of the thirty teams in the MLB over the past twenty seasons. This project aims to provide insight into the question: can money buy support and/or success in the MLB? I focused on the MLB instead of other professional sports because there is no salary cap in baseball and thus, there is a broader range of payrolls and more important and interesting conclusions can be drawn from the data. By interacting with my visualizations, users can gain insight into the correlation between payrolls, attendance, and success in general and for specific teams and seasons. - https://drive.google.com/file/d/1-X6T45LS69yeDMsxIdBrbrRiqS5g4EsZ/preview
My project compares overall consumption of alcohol to the success of kickers in the NFL. I first determine whether both figures are correlated, and then I examine whether a specific drink is correlated with kicking success. - https://drive.google.com/file/d/17lmJuSOYF0NQkx2TiTpGGi-PMjlhDW3G/preview
My project allows for different visualizations of data on all 50 US states. The user can see their populations, GDP's, and GDP per capita. In addition to this they can also view this data in multiple ways depending on which one is more suiting to their research and analysis. They can even plot data against each other to see if there are correlations between two different characteristics of different states. - https://drive.google.com/file/d/1YXCWRNDHOCHPFFdlDyGVDieU1ojlvMLn/preview
My project looks at data from a number of different airlines and visualizes this data. Some of the data are accidents for a given airline from different time spans, amount of kilometres flown, etc. Using these visualizations, one can come to certain conclusions based on the data. - https://drive.google.com/file/d/1LwNrKkEJCtKN_WKaErSRA_ne5j-Yy3TB/preview
I took a csv file I found from online that contained data from each March Madness game from 1985-2015 and created visualizations based on that data depending on user input of round, seed, or team. - https://drive.google.com/file/d/152o5E6y1mXJ_X2BLAYLU_UKrBwi83fee/preview
Being someone who was born and raised in the city of Pittsburgh, I have always loved Allegheny County and all it has to offer. From food to recreation to tourism, Pittsburgh is a small, yet bustling city filled with culture, creativity, and people. For all these reasons, Pittsburgh is a quickly growing city. The goal of my project is to create a program that allows users to examine the aspects of each school district in the county so that they can select the best district for them to live in. The program examines different public amenities offered within the county based on where they are located in respect to school district boundaries. This code will allow users to see which districts have more/less amenities than others. - https://drive.google.com/file/d/1rMSoYokRHEUSGXtp59M7-zcFSX7ee7EP/preview
My project displays certain crime types on an interactive map of the city of Chicago. By selecting a crime type and time range, the user can see where these types of crimes are occurring in Chicago. The user will also have the ability to see the arrest and block data associated with each specific crime. - https://drive.google.com/file/d/1DIq4Xk9FAZV3x-jIXgU87R-EKtcy6ZUW/preview
uses data from a makeup database to help user find best products based on rating - https://drive.google.com/file/d/1itgVfXQ6pvPbWJ4PFrHeWa9qJoptXRRi/preview
Two visualizations showing the wins and competitions of every team in each season they competed in and the average score of every event each season. - https://drive.google.com/file/d/15M4LCjolVnKJa4NQWWtBzmsIlsGxrAr0/preview
While popular machine translation services like Google Translate provide exceptional translation between popular languages, they are often less fantastic at translating particular styles of writing. One example of this is in translating the rules text of Magic: The Gathering cards, where Google Translate frequently substitutes very important keywords with specific meaning within the game for synonyms. This project aims to train a Spanish-to-English machine translation model over the extensive set of professionally-translated Magic cards to yield more accurate automated translation, and compare the developed model to Google Translate. - https://drive.google.com/file/d/1EEqvp3VoF7MLjG7QnoXdr5nEhU4diSYJ/preview
Given an input Pokemon, I determined how many other Pokemon in the Pokedex the input Pokemon is super effective, regularly effective, not very effective, and not at all effective against. The goal of this project was to optimize the user's party of six Pokemon with the Pokemon that will be the most effective in battle, and my project shows many different visualizations that helps the user decide this. - https://drive.google.com/file/d/1AEMaVN27pRrhZSa44Bxzvn_xkrNyfoVn/preview
This project shows multiple graphical representations of the crash of the DOW Jones stock and the quick onset of COVID-19 epidemic in the United States. - https://notredame.zoom.us/rec/play/7sArdLio_G83H92T5ASDUfN8W9S1Kaus1yhK-qFfyR2wAnUKNFCuM-FDZuFbXzqWvZwHehtkVyJyiBlq?continueMode=true/preview
My project compares weather and country information between two countries. The user inputs their home or current city and country, and a second country they want to travel too. They receive information on the temperature, weather conditions, and other travel information both in text and through visuals. Travel information includes information on population, languages spoken, and currencies used. Weather information includes the daily temperature, the weather conditions, the maximum and minimum temperature, and the range. - https://drive.google.com/file/d/1EdLLFcMVNizG6FlfXtAHqoGvVP08CpTl/preview
My project uses data provided by the United Nations and has two main parts: a graphical portion and a user-interactive portion. The graphical portion contains six visualizations modeling the various relationships between different social indicators, with some of the graphs containing additional lines or plots to develop a greater understanding of the data. The second portion is a user-interactive program that recommends countries to live in based on desired social characteristics. It takes in three different social indicators (and their levels) as input, and outputs the countries that meet or closely meet the criteria with descriptions for each country. - https://drive.google.com/file/d/1eo5muT4tb8Rn2qPqCchWBPRseijXb7_n/preview
My project has multiple parts. First, it takes user input and calculates the amount of calories they burn in a day, as well as the amount of calories they should eat if they want to lose or gain weight. Next, I have a scatter plot of different foods, which I got from a CSV file. Lastly, I use the Nutritionix API to create a nutritional search engine that returns the nutrition facts of searched foods. - https://drive.google.com/drive/folders/1HmUEOmHvHV2_1_4niZ2jcqU1cINDni-q?usp=sharing
My project uses data from the College Board for the number of students earning each score on each AP exam for the years 2014 through 2019. It creates a data frame from this data with each entry containing the year, exam, and number of students earning each score. It then gets user input for a year, exam, and figure type, and displays a figure from the data for the chosen exam and year. - https://drive.google.com/file/d/1Tpx04j9aXuQxkHgSabA2zSgOOxV3BBm0/preview
I chose this project because my mom's clinic has performed this research in the past, but I wanted to be able to do this research on my own and see the relationships, if any, of these two variables in North Carolina, where I live. My project uses data from multiple sources on food insecurity and demographics in North Carolina to create visualizations representing the relationship between the food insecurity rates in North Carolina and the number of grocery stores per county. From this data, I created three visualizations comparing different aspects of the data, including food insecurity vs. number of grocery stores, food insecurity vs. population, and a map showing the food insecurity rates. From this data, a lot of information can be extracted to see relationships between variables and the factors which affect food insecurity in North Carolina. - https://drive.google.com/file/d/1chtgNRm4r5Uz2nYQD8XFPQWzHemtnGTr/preview
My project involves allowing soccer fans to know about everything that's going on in the pro soccer transfer world through a search button. By searching any player, team, league, or keyword, users can find information coming from a variety of sources that relay up-to-date information through real-time web scraping. - https://drive.google.com/file/d/1bmrRtE1GX2esxNPYKtAZzRDo-8bl03Cs/preview
Life Simulator manipulates mortality rates from the CDC and the SSA to simulate the life of a U.S. citizens based on the state they live in as well as their gender. Life Simulator is an animation which begin at an inputted starting age and ends upon a death. - https://drive.google.com/file/d/1l7y5a8iOBXqOR0jCB-6xmKyv3P9FzhY0/preview
I took the information from the NFL Arrest Database of USA Today and created multiple useful visualizations. I displayed graphs based on the position played, team played on, teams through the years, and the type of arrest. - https://drive.google.com/file/d/1zRfuZ1-T7ZCqa9B6VFrfkth_rrC4fkUZ/preview
For my project, I redesigned the classic video game Space Invaders using the Pygame Python library. - https://drive.google.com/file/d/1ZxRrfWbHb_IwfDxudkT3fyMWUSrjR5MT/preview
This program will compare the followers between two (or three) Twitter accounts and display them in a Venn diagram, allowing users to see the overlap between them - https://drive.google.com/file/d/1V4ueS3yTLMJjmcR3pEIs3ExU9Yi3OVpm/preview
My project allows the user to find a DivvyBike station near them and also check the current weather conditions in Chicago. The user will see the weather conditions and directions to the five nearest DivvyBike stations to their inputted location. - https://drive.google.com/file/d/1YLgweiWr5QwxNaCNHbUjHiL7BoXucPYZ/preview
My project allows for a user to search for a given country by ISO 3 character code. When a country is searched if the given country has corona virus data, the program displays a few key data points alongside that country's population pyramid which is graphed using iplot. - https://drive.google.com/file/d/1D2OoInUP4fMWAHaf-Ugvneoxkj3x44Va/preview
My Project shows the change in the percentage of people getting married over different time periods depending on their country, sex, and age range. - https://drive.google.com/file/d/17dEiOGXIF6sePWX88P_k-v3hqA6ZCZ3F/preview
My project scrapes corona virus data from the web (cases by state) then plots it graphically and colors in a map predicting the spread based on user input. - https://drive.google.com/drive/u/4/folders/1VsXwL0St0d8jtd5WzDB-a2IWvrX7tII2
With this project, I wanted to represent the different factors that led to higher numbers of people in certain groups to be registered to vote and active in local politics. To do this, I created visualizations that analyzed the voter status of different groups, including groupings by gender, income, birth country, and language. - https://drive.google.com/file/d/12D-u2erVpD6l1b0QSR4oFX3dE1ksHxnw/preview
My project collect the exchange rates of currencies within a chosen time frame from 1999-2020. It organizes the data into arrays and then a data frame and allows for users to view visualizations that show the relationship between currencies, as well as specific data for a certain currency and a certain year. - https://www.youtube.com/watch?v=LCZQDaQjZLo&feature=youtu.be&hd=1/preview
This project allows a user to see the overall "structure" of math articles on English Wikipedia, such which articles are more central or peripheral to the subject and how different sub-fields of mathematics are related. Additionally, it allows the user to explore patterns in the viewing history and edit history of these articles, allowing the user to analyze public interest in different areas of mathematics and figure out what steps could be taken to improve an article. - https://drive.google.com/file/d/1Dcmv0q4FRBZ4j7WTH_AF5HI-O6RIxrqD/preview
My project's original scope was to compare fast food restaurant density and poverty rate to see if there is a relationship between the two. Originally, I had only found data for fast food restaurant density by state, however, I eventually found it by county, which allowed me to expand the scope of my project. I also thought of some other interesting factors that may relate to the two original variables, so I included those as well. In the end, my project allows the user to choose between state or county data as well as choose between scatter, choropleth, and 3D scatter plots. Once the user selects these, they can then determine other elements of the graph, such as the x-axis, y-axis, color, etc. - https://drive.google.com/file/d/10aA9q5gU5qnImrk3yDk8HGoMhFxdsu2i/preview
This project allows the user to explore different endangered species populations. The user is able to sort the populations by species, class, continents, and different levels of threats. This allows the user to compare different characteristics of populations and which may be more of a risk factor that conservation efforts need to address. - https://drive.google.com/file/d/13fc9BLJ8--xjFCKO1CmxI6AAt35y0xRC/preview
Using data about temperature, carbon emissions, and sea level worldwide, my project allows users to choose which of those variables they would like to see, and where and when they would like to see them (they can choose to look at one country or multiple, and the data available to visualize spans from 1751 to 2016 depending on which data they choose). This allows the user to visualize our changing climate and compare it to the rise in carbon emissions. - https://drive.google.com/file/d/1hLLRREHUh35nFOWD6ge4x-M2qf9ypmWP/preview
Allows the user to gather live data from twitch livestream chats and display the frequency of messages over time after the data is processed. - https://drive.google.com/file/d/1lAcrN8hATxqFCvFwLbwKIJd_izlTKgS6/preview
The objective of this project was to create my version of the game, Pac-Man. The game runs in real-time, makes use of animation and the visually-appealing “retro-style”, user interaction with the keyboard and mouse moves the Pac-man and controls the menu. There is four direction movement, utilizing the standard “Up, Down, Left, Right” scheme. The game includes multiple “behavior” modes. These include a “frightened” mode, a “random” mode, and a “chase” mode. The “frightened” mode resembles the mode in the standard Pac-man game where the game is flipped and the ghosts can be consumed by the Pac-man. In summary, this project is simply remaking pacman with 3 ghosts instead of 4. - https://drive.google.com/file/d/1Tz9gkHl3tJ0SlORX1EmmAjxhrmDWHHQH/preview
This project manipulates NBA statistics data from a CSV file. The two displays are a scatter plot of simple height vs. weight for all players in the dataframe, and a histogram comparing composite scores of a selected player and the user. The purpose of the histogram is to allow the user to determine if he/she could beat the NBA player in one-on-one, depending on whose bar is higher. - https://drive.google.com/drive/folders/1_nVLASN5cei7Ik_BmzQo74Lo_p5EJ9-x/preview
The Recipe Curator program is one that allows a user to be able to interact with a number of sliders that allow him/her to choose the number of nutrients desired in their next meal. For example, the user will be able to decide the minimum and maximum amounts of protein in grams he/she would like to have. Once that information is collected, I will use the Spoonacular API to find data of all available recipes that meet the criteria. With the information, I will be able to display the number of recipes and resultant nutrient clusters in a pie chart. The user will then be able to then either request a random recipe from us or choose the recipe that they would like to have from the data that we collected back from the API. Once that is done, we display the recipe in nicely formatted text for the user to enjoy. - https://notredame.zoom.us/rec/play/u8V8Jumo-j43HdPDuASDBaUrW47uKaqs0igaqPIJz028UnFQM1ryZrQSYuLmbdpu-M9gkkaZ9grnAiep?continueMode=true&_x_zm_rtaid=Rf9gWvqHS-OGDxYnDfS_kg.1588041888874.5176aa307e88428edcb78f71527d2f48&_x_zm_rhtaid=363
I take all the comments posted on reddit.com from the month of December over the course of 5 years and display four comparisons which I describe in detail in my videos. Each comparison reveals a trend in the growth of Reddit as a website. - https://drive.google.com/file/d/1Uqc_lqG9GGuX7RvtHI6W46ncnOm0HzaR/preview
The project has two parts. In Part 1, select the position you would like to investigate. From there, choose a player from the list provided in the interact. Then select the type of graph you would like from a third interact. From here, you will receive the major statistics for that individual players as well as the plot you selected. Part 2 is similar except it is used for comparing multiple players. Again, start by selecting the position you would like to investigate using interact. Then select 2 players from the provided list to compare (interact). From there, you will receive a parallel coordinates plot comparing all of the major statistics between those two players. - https://drive.google.com/file/d/1-ZD3LR9TpEfMPWBehAWO0o_3i4DXQPJ5/view/preview
This program aims to help users compare the total cost of attendance for numerous postsecondary instutitutions by plotting the cost of attendance of a selected college or colleges, given a number of customizeable factors, over a specified time frame. - https://drive.google.com/file/d/1kyTdnmIvn7HpqDmzsKQgpm9a8xIkvdht/preview
I used stock market data along google trends in order to determine what phrases were searched the most when the stock prices peaked. My project takes in a date range and the name of a stock ticker and from there graphs the prices then finds where the prices "peak" which is where relative max. At dates where prices peak I look for the most commonly searched terms related to the stock and print out however many depending on user input. - https://drive.google.com/file/d/15KmGZsue0ArHJoC-ZkL8K4-jeKRKLC_3/preview
Analyze Twitter trends and display relevant Tweets. - https://drive.google.com/file/d/1UotE0IE-xdK4t8ys-8tzv7SHyXMgJ7xB/preview
This tool allows a user to select two NBA players from all eras and compare them on multiple statistics. It uses the python libraries dash and plotly to create a web based dashboard and pulls data from basketball-reference.com to function. - https://drive.google.com/file/d/1RJvB7nPSkKWYpx0a9p9aZSZ41FY3Y5Qy/preview
My project allows users to compare MLB players in different statistics from past years. The user can select what season to analyze, which statistic to sort by, and how many of the top ranked players to include in the analysis. The program then presents the user with a bar graph of the values of their chosen statistic, so they can gain an understanding of how close or far certain players were to each other in performance. The program also presents the user with a box and whisker plot for the selected amount of players as a whole in the chosen year and statistic. This visualization allows the user to look at an entire season as a whole and compare how the top players in that year performed relative to other years. - https://drive.google.com/file/d/19Fx4kzCfwxsTZ4c28wHD-w6SyWI3yWES/preview
This project uses data from 2012-2015 for the amounts of concussions and arrests obtained by different position groups and teams in the NFL. The project uses JSON and HTML requests to gather arrest information and CSV files for concussion information. All of this data is converted into usable DataFrames which then are implemented in a custom GUI in which the user can customize how they see the data available to them (animation, general numbers, by year, multi-year plot). - https://drive.google.com/file/d/1BD3QhA2KnQx5NxyyFzncNflY2Wr35IBi/preview
This program has access to statistics on the top 262 NBA players and provides example visualizations and describes the relationships. It also allows the user to select different areas to compare visually. - https://drive.google.com/file/d/1dQiX1JF-djk_xIbAcrjcnWhkb1UBQ8R2/preview
Users have the ability to choose between comparing the stats of all NFL QBs from the 2019 season or just two QBs head to head. They can then vary which statistics are shown in the x and y axis. - https://drive.google.com/file/d/1VRzhsm1cBZsQPFGRZf7cDz1StRt-9cLA/preview
My project is an analysis of Broadway data from shows ranging from 1990-2016. My data is from the Broadway League and was originally contained in a csv file. The dataset included information about Broadway shows by the week and specified information like the date of the end of the week, the show name, the theatre, the attendance for the week, the percent capacity, the gross for the week, and the % gross possible where applicable. I changed the data in the CSV file to a DataFrame, and then manipulated the data that I wanted to use further from there. Through a process that transferred the data into more understandable information, I display three visualizations to help theatre fans and interested users learn more about Broadway through the years. After the user enters the year of their choice, they see a bar graph of weekly attendance for a show, a pie chart of types of shows in the year, and a bar graph of weekly gross for a show. The user can change the show they are looking at with a drop down menu above each bar graph, and the options of shows differ depending on the year they entered at the beginning of the program. - https://drive.google.com/file/d/1w6MdtCEq5qr73joLKUacBOBigYZNjav8/preview
My project simulates air cannon ballistics. Users can use it to learn about projectile motion in a controlled, non-friction environment. It is interactive and updates with user-friendly sliders. From a technical point of view, it uses Euler's Method to assume constant acceleration in small time increments to accurately approximate non constant acceleration situations. In the end, a interactive visualization and a number of interesting launch statistics shed a light on the ballistics process. - https://drive.google.com/file/d/1_zL2pabLpIvoRaUwQC1b7i4PbhLLEbgC/preview
Using data about death rates for selected risk factors (obesity, drug use, alcohol, and smoking), I created several visualizations that a user can specify to learn more about the mortality rates of different risk factors over time and around the world. The user specifies a country, year, and risk factor and then may choose what type of information they wish to see. Depending on the visualization they choose, they may see a choropleth, pie chart, or line graph corresponding to mortality rates for their country or the world. - https://drive.google.com/file/d/1FMcDpnWM-eDHcNrpx9qYkCN-FC1FIf-x/preview
My project "Undergraduate Women in STEM Statistics" examines a few different comparisons between women enrolled in and graduating from undergraduate STEM programs versus men enrolled in and graduating from undergraduate STEM programs over a period of several years. The data visualizations are specifically purposed to make visible and quantifiable any disparate gender distribution in undergraduate STEM programs, a symptom of the disparate gender distribution in the STEM world as a whole. Since the data representing undergraduate enrollment in and graduation from STEM programs span several years, the project also hoped to show an improvement in women's representation in STEM over time. - https://drive.google.com/file/d/1e8jhgiKqKsxxJ90my2DgfUTdT8lQNPDL/preview
“Tweet like President Trump” project processes President Donald Trump’s twitter texts in 2019. It analyzes the tweeting patterns of Trump related to the time of tweeting and hashtags Trump liked to use. It also analyzes how audiences responded to Trump's twitters and usage of hashtags by processing the number of favorite and retweet each original twitter he got and how the responses change throughout the year. - https://drive.google.com/file/d/1J9f7w3FjH2pJpWDdBbPEgKF1vIaPbU7y/preview
My project takes raw data from a selected player's Baseball Reference page and converts it to a data frame. It then allows the user to interact with this data, producing many possible figures that allow the user to see a player's progression over time. - https://drive.google.com/file/d/1fJMvbpbA_Xfak7KIWock6zo-rIgUxObO/preview
It recommends books based on the user inputed book ID. The output is books that have similar ratings. Additionally, I added two visualizations to accompany the book recommender. - https://drive.google.com/file/d/19lyU2pnpLCHKYX1fmFBjgc1HEriUcBsi/preview
My project utilizes statistics from the Motorcycle Legal Foundation, the National Highway Traffic Safety Administration, and United States Census Bureau to create helpful visualizations about motorcycle fatalities and laws per state. - https://drive.google.com/file/d/1ZB6WSQoZcPftnu1q-tcmxI3AXxe1heX3/preview
My project ultimately boils down to 4 sections of visualizations. The first section is a choropleth of the rise in coronavirus cases on a day to day basis of all the states. The second is also a choropleth, but one that does not include the 2 states with the highest coronavirus case count, New York and New Jersey. This choropleth shows some more nuance. The third section is an analysis of a single state's data, the state which the user chooses, and compares it to the US. The fourth section compares two states of the user's choosing. - https://drive.google.com/file/d/1ESkl5lW1vti6j5o6dF5QClEwMVvz5ec8/preview
My project seeks to answer (or at least shed light on) the question, "what effect do popular online U.S. news sites have on the election?" - https://drive.google.com/file/d/1A3CilhY7RcalauAFTGsKiQViDtpwoOW-/preview
My project manipulates NCAA Men's Basketball team data to do a variety of different tasks. It uses the data to create a multiple linear regression model that can be used to predict the win percentage of a team given a few data points. The linear regression model also shows how different statistics relate to a team's success. The data was used to find the best and worst teams for various statistics for the 2019-2020 season. The data was also used to create various visualizations that can be used to compared how various team statistics are related to each other. - https://drive.google.com/file/d/1Zm9bKKdZQyDnJvWM9aG9xSXKphHmGczQ/preview
visualize data from past and present baseball franchises - https://drive.google.com/file/d/1TXKBafGG9tJGErDGZbpP5H8dKXEqYBNr/preview
My project is a game that allows users to learn Chinese characters. The game randomly selects characters from a Chinese-English dictionary and displays these characters to the user. The user must select the correct translation of the character from a list of five choices. The game shows the user their score and the questions that they missed. - https://drive.google.com/drive/u/1/folders/1FDlLpqU_8fzXurPg9nn4hKxQG-TNosf_
This project obtains and cleans data on performance for different rocket fuels and oxidizers. It then uses the data to create several interactive visualizations in order to help the user understand the characteristics of different fuels and some of the tradeoffs that rocket designers are forced to make in selecting fuel/oxidizer combinations. - https://drive.google.com/file/d/17pe2eaRM0CXcapBgqirkhi2pdPNFy0Aa/preview
For my final project in Intro to Engineering II, I created a program which simulates the process of natural selection. The code analyzes traits that are most crucial in survival against competitors. Initial creatures compete against each other for resources. Each creature has traits that hold the potential to mutate including size, speed, vision, passiveness, aggressiveness, and attack ratio. In addition, different traits equate to varying levels of energy consumption. For example, the larger the size of the creature, the more energy required for movement. As the program runs, successful creatures reproduce, and unsuccessful creatures die off. The program demonstrates which traits are most important in the environment of the simulation and related survival. - https://drive.google.com/file/d/1SctYMCjh5XxWgfprbMcljBjeFR4EIcZf/preview
My project is a nutritional information display to help the user not only see the necessary nutritional information of common fruits and vegetables easily but to see the relationship between the different aspects of nutrition to make decisions about their diet. - https://drive.google.com/file/d/1oyzEi6IIrEFY1WTYXn8O_UznDAPmi-oR/preview
Visualizing the correlation between different data points by state. - https://drive.google.com/file/d/1-4SdE-qfcefe4lw7sgG876NBlMn4Pw5Y/preview
My project involves getting data from an XML file (that my dad sends to me from his private login with the Patent Office) and then creating an Excel file that displays all the data for my dad to use. - https://drive.google.com/drive/folders/1Zr3OjuXN0I0PMLQ60S_i8OY8dVf3FvEy
I took nfl fantasy football data from the years 2018 and 2019 for four fantasy/offensive positions. After putting the data into a dataframe (and also creating multiple new columns for additional player-selection criteria), I prompted the user via interact to select which criteria they prefer for selecting fantasy football players for their roster. They then are able to adjust the weights for each criterion, or how much emphasis they place on each one. Online fantasy sites have an option called "auto draft", where the computer uses a proven method to automatically select quality players. My goal was to give the user the power to compete with the computer and try to maximize their own team's total scoring and wins on their own. In short, I am manipulating and using the 2018 data to draw conclusions and best select player for the 2019 season. I then use data from 2019 to simulate a new season to test these criteria set for each player. At the end, the program shows us with visuals who wins in both raw scoring and total wins, an aspect most fantasy players (including the auto draft system) neglect when drafting. - https://drive.google.com/drive/folders/1L_DPmW5eVmRc0BfoSV4spAw1Hz34Hq1J?usp=sharing