Project Overview
This personal project was inspired by my concern about the growing tobacco usage within my generation. Using a dataset from the Indian government's 2023 records, I conducted a comprehensive analysis of youth tobacco consumption patterns. The project involved data preprocessing and visualization techniques to uncover various trends and insights.
My Contributions
In this project, I was responsible for collecting and cleaning the dataset, performing in-depth statistical analysis, and creating visual representations using charts to highlight significant trends. My analysis provided actionable insights, revealing patterns in youth smoking habits, regional differences, and the effectiveness of regulations designed to prevent underage tobacco sales.
I began by collecting and cleaning the dataset, ensuring its readiness for analysis. Using statistical techniques and data visualization, I examined various dimensions of youth tobacco usage, such as the median age at which individuals typically begin smoking and the factors contributing to this behavior. The dataset revealed critical insights into the social and environmental influences that lead to early smoking habits, including peer pressure, socio-economic background, and exposure to tobacco products in certain regions.In addition to demographic analysis, I conducted a state-wise study to evaluate the effectiveness of regulations prohibiting the sale of tobacco to minors. This involved mapping which states were actively enforcing these laws and how they influenced youth tobacco consumption patterns. By using various charts and graphs, I was able to visually represent the correlation between strict enforcement and reduced tobacco usage among underage individuals.

In this project, I took full ownership of the data analysis process. I was responsible for gathering the dataset, performing data cleaning to remove inconsistencies, and conducting detailed exploratory data analysis (EDA). I applied statistical models to extract meaningful insights and leveraged visualization tools to present these findings clearly and effectively
.Some of the key insights I uncovered include:
The median age for starting tobacco use and the various factors that increase the likelihood of youth smoking at an early age.
State-wise differences in tobacco consumption, with a focus on regions where the enforcement of tobacco sales restrictions to minors was either lax or stringent.
Insights into socio-economic factors and peer influence that contribute to the early adoption of smoking habits among youth.

My work culminated in a set of actionable insights that could be used to inform policies or awareness campaigns aimed at reducing tobacco usage among underage individuals. This project not only honed my data analysis and visualization skills but also deepened my understanding of public health issues related to tobacco consumption.
Big Data Analysis
Autogenic
Mar 2024 — Jun 2024