Professional Projects
Below are projects that demonstrate my abilities with VBA, Python, SQL, and Tableau. I categorize these as professional projects since they utilize commonly used technical skills in analytics. In addition, I believe that they also teach universal and transferrable skills, such as the ability to learn in an unguided and independent setting and the ability to leverage available resources to complete a task.
View my certifications at https://www.credly.com/users/binaryxxsune
TIP: Fullscreen/download files for easier readability if necessary. Usually found at the bottom of the media
VBA
To use and inspect the macros, please download the worksheet.
Question Auto Fill Macro
- Designed a user form to populate and format a sheet with a character’s info and stats, based on the inputted parameters.
Character Creation User Form
- Create a macro to automatically answer common questions, such as name and current date, regardless of its location in the selection.
Python
Street Fighter 6 Rank Distribution Explorer
- Visualized the distribution of 750k players’ ranks based on web-scraped data to provide an accurate benchmark
- Leveraged multiprocessing for an 80% runtime reduction to allow for the implementation of a player inactivity check
Valorant Meta Analysis Series
- Built an interactive dashboard to reveal the most popular and successful characters based on the map and skill level
- Evaluated whether performance statistics from past matches, such as accuracy, can be used to predict a player’s rank
- Gathered, stored, and wrangled data requested from a REST API to overcome the limited match data provided
IBM Data Science Professional Capstone Project: Winning the Space Race through Data Science
- Employed classification algorithms, such as KNN and SVM, to predict if rocket engines will be successfully retrieved and reused after their launch, determining the company’s ability to offer competitive contracts through cost savings
- Performed all the tasks found in a data science project’s life cycle, from data collection to communication of findings
SQL
HackerRank: The Report
Completed the following HackerRank challenge: “The Report - write a query to generate a report containing three columns: Name, Grade and Mark.”
https://www.hackerrank.com/challenges/the-report/problem
SELECT
CASE
WHEN g.grade > 7 THEN s.name
ELSE NULL
END AS student_identifier,
CASE
WHEN s.marks BETWEEN g.min_mark and g.max_mark THEN g.grade
END AS student_grade,
s.marks
FROM students AS s
INNER JOIN grades AS g
ON s.marks BETWEEN g.min_mark AND g.max_mark
ORDER BY student_grade DESC,
CASE
WHEN student_identifier IS NULL THEN s.marks
ELSE s.name
END
;
HackerRank: Top Competitors
Completed the following HackerRank challenge: “Top Competitors - query a list of top-scoring hackers.”
https://www.hackerrank.com/challenges/full-score/problem
SELECT Hackers.hacker_id, Hackers.name
FROM (
SELECT Submissions.hacker_id as hacker_id, COUNT(Submissions.submission_id) as challenge_count
FROM Submissions
INNER JOIN Challenges ON Challenges.challenge_id = Submissions.challenge_id
INNER JOIN Difficulty ON Difficulty.difficulty_level = Challenges.difficulty_level
WHERE Difficulty.score = Submissions.score
GROUP BY Submissions.hacker_id
) AS Perfect
INNER JOIN Hackers ON Hackers.hacker_id = Perfect.hacker_id
WHERE challenge_count > 1
ORDER BY challenge_count DESC, Hackers.hacker_id ASC
;
Tableau
Iris Data Set EDA
- Established a matrix scatterplot to provide an overall overview of the iris data set and any relationship between its features and the species it belongs to.
- Made separate dashboards for each feature to provide a more detailed summary of the distribution of species per feature.
- The original scatterplots, which compared 2 different features and the resulting species, are also included for a detailed view of the data.
TIP: View on Tableau Public or Fullscreen at the bottom of the visualization for a complete view since the dimensions for the embedded links are set for browsing purposes.
Multivariate Analysis of the Iris Data Set
Distribution of Iris Species Based on Petal Length
Distribution of Iris Species Based on Sepal Length
Distribution of Iris Species Based on Sepal Width
Distribution of Iris Species Based on Petal Width
Distribution of Iris Species Based on Different Features
NOTE: Please ensure that the “Show Sheets” option is selected in the Settings to be able to access the different sheets.