
Exploratory Data Analysis of NYC Airbnb listings (2019) — pricing trends, borough analysis, seasonality, and host behaviour using Python, Pandas, Seaborn, and Plotly.
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An Uber Bengaluru Case Study EDA on the reasons and solution for "Rider Cancellation" and "No Cars Available" from the City to the Airport and back through Feature Engineering using Python libraries such as NumPy, Pandas, Matplotlib, Seaborn, etc.
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This repository contains a Tableau Desktop dashboard that provides insights into sales trends, regional performance, product categories, and customer segments across multiple global markets from 2014-2017 for Amazon.
View ProjectMy resume showcases my professional experience, technical skills, and educational background. It includes details about projects I've worked on, technologies I'm proficient in, and my contributions to various organizations.
Feel free to download a copy for your records or to share with your network. I'm always open to discussing new opportunities and collaborating on interesting projects.
Download Resume (PDF)Hi! I'm a data analyst passionate about building actionable data driven insights from raw and messy datasets using analytic tools that users love. I combine technical expertise with a keen eye for design.
Over the past 9 years, I've worked at the intersection technology, writing, policy and design leading projects from ideation to the final product. I'm particularly interested in climate modelling, exploratory data analysis, and feature engineering that solves complex data problems.
When I'm not coding, you can find me contributing to open source, writing technical blogs, or exploring new technologies.

I'm always interested in hearing about interesting projects and opportunities. Feel free to reach out!