![image](https://private-user-images.githubusercontent.com/88932858/251640127-38f925c9-ea52-4bef-b35b-7b74cef074d9.png?jwt=eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.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.wAVExqXySc53IkbdPsooXT9UcR8TI1PraoSMJmfmN0s)
performed exploratory data analysis(EDA) using pandas, matplotlib and seaborn libraries in Jupitor notebook
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 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