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Blake Rayvid

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Tag: Matplotlib

Programmatic data plotting for research projects, including stock performance comparison and tweet sentiment.

Compare Stock Returns

Posted on June 1, 2025May 11, 2026 by Blake

This page lets you enter multiple stock tickers (eg. AAPL, MSFT, GOOGL) and even custom portfolio expressions (eg. 0.5*NVDA, 0.25*AMZN, 0.25*KO) and compare their performance against a benchmark (eg. SPY) over any time period. It’s built with Python and Flask on the backend. Data comes from Yahoo Finance via the yfinance library, pandas crunches the…

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SOAP: A New Polling Platform

Posted on May 4, 2025May 12, 2026 by Blake

Constructive political criticism online is hard to find. Discussions quickly turn mean, and even minor disagreements can escalate into major arguments. Messages often get lost if one’s audience is too small, and misunderstood words can lead to backlash. That’s where Soap comes inβ€”a new kind of social platform designed to change the way we talk…

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Sentiment Classifier

Posted on July 12, 2024May 12, 2026 by Blake

My Flatiron School Data Science Bootcamp Phase 3 Project was to address the business problem of brand reputation management by monitoring and analyzing Twitter sentiment. The goal was to develop a machine learning model that can correctly classify tweets as positive, negative, or neutral, and provide insights to improve brand perception and engagement strategies. πŸ”—…

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Space Debris Exploration

Posted on June 1, 2024May 12, 2026 by Blake

This is an exploratory data analysis (EDA) of a Kaggle dataset I made as part of the Flatiron School Data Science Bootcamp. The slides from an associated presentation are available here. πŸ”— View on GitHub

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Boolean Network Animation

Posted on November 19, 2020May 12, 2026 by Blake

This page animates the dynamics of a random boolean network, a collection of interconnected binary variables with a rule for determining the next state from the current one. πŸ”— network.blakerayvid.com View on GitHub

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Epidemic Simulator

Posted on April 19, 2020May 12, 2026 by Blake

This Jupyter notebook simulates a disease spreading through a community in random motion. Individuals are represented as points undergoing independent random walks in a bounded 2D environment. Parameters include: the population size, the average population density, the number of times to evolve the system, the number of trials to conduct, and the fraction of the…

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Categories

  • Data Science
  • Exploration
  • Finance
  • Health
  • Interactive
  • Optimization
  • Utilities

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D3.js Desmos Docker Express.js FFmpeg Flask Gemini API Google Maps API HTML/CSS/JS MATLAB Matplotlib Netlify NetworkX Next.js NLP Node.js NumPy P5.js Pandas Pillow PostgreSQL Python QuantConnect Railway React.js Scikit-Learn SciPy TensorFlow Tesseract OCR WeasyPrint YFinance API

© 2026 Blake Rayvid. All rights reserved.