Exploratory Data Analysis on a dataset containing Black Friday sales information of an E-Commerce.
This EDA is restricted to visual analysis tools only. The challenge was to produce insights only by visualization.
Questions to be answered by the EDA:
- Does the marital status influences in the Average Purchase Value?
- Does the marital status influences in the Purchase Category?
- If one wants to sell more products of category 14, should one invest more in publicity for marital status 0 or 1?
- Which variables are correlated to the value of the purchase?
Dataset:
| Column | Description |
|---|---|
| User_ID | User ID (key) |
| Product_ID | Product ID (key) |
| Gender | User gender |
| Age | Interval range of user age |
| Occupation | Occupation (masked) |
| City_Category | City Size Category (A, B, C) |
| StayInCurrentCityYears | Number of Years the user is living in the current city |
| Marital_Status | Marital status (Single or Married) |
| Product_Category_1 | Product category (Masked) |
| Product_Category_2 | A 2nd possible product category (Masked) |
| Product_Category_3 | A 3rd possible product category (Masked) |
| Purchase | Purchase value |