Welcome to my project on Exploratory Data Analysis (EDA), a fundamental aspect of data science. EDA is a crucial step, often consuming a significant portion of a data scientist's time, and is essential for uncovering insights. In this project, I have showcased various EDA methods and techniques using Python, applied to the Diwali Sales dataset from Kaggle. Explore the methods and insights, and enjoy your journey into EDA with the Diwali Sales dataset. Good luck!
- Performed Data Cleaning and Data Manipulation.
- Performed Exploratory Data Analysis (EDA) using Pandas, NumPy, Matplotlib, Seaborn Libraries.
- Improved Customer experience by identifying potential customers across different states, occupation, gender and age groups.
- Improved sales by identifying most selling product categories and products, which can help to plan inventory and hence meet the demands.
- Married women age group 26-35 yrs from UP,
- Maharastra and Karnataka working in IT,
- Healthcare and Aviation are more likely to buy products from Food,
- Clothing and Electronics category
LinkedIn : https://www.linkedin.com/in/vaibhav-mahindru-845604175/
Email : vaibhavmahindru04@gmail.com
Thank you!