🌊🎨 I made a repository showcasing 164 color palettes from Seaborn... so you do not have to!
Conducted in-depth time series analysis on stock market data for major tech companies like Amazon, Google, Apple, and Microsoft. Utilized multivariable analysis to explore the inter-relationship between stock closing prices and daily % return, visualized findings using Seaborn library, and performed value at risk calculations for each company.
Conducted sentiment analysis and data visualization on YouTube comments using the TextBlob library, uncovering insights on audience engagement, emoji usage, and video performance metrics. Implemented linear regression models to explore correlations between views, likes, video titles, and audience engagement.
This repository contains Python notebooks and visualizations for an in-depth data analysis of a dental clinic in Brazil (2020-2025). The project explores analytical techniques like cohort analysis,patient segmentation, engagement, and dropout rates, providing key roecommendations for business growth and operational efficiency
Predicting the best route for the delivery of Starbucks in London.
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