EDA of eCommerce multi category store

The main challenge with this notebook was the large dataset I first read only the first 500000 rows just to explore the data

This yielded the above. I see sub Categories are in the category_code column

so I split the parent category

I see Electronics is our best selling item. I want to determine if this is due to more views and if it correlates to conversion. If we see accessories having more views than appliances then that would indicate there might be an issue in the experience offering or price.

Conclusion Summary

Based on the given dataset, the best opportunity to improve would depend on the specific goals and context of the analysis.

However, we can observe that electronics has the highest conversion rate at 3.18%, indicating a higher proportion of users who viewed products in this category ultimately made a purchase. This could be a promising area to focus on for further analysis and potential optimization.

On the other hand, apparel has the lowest conversion rate at 0.48%, indicating that there may be potential to improve the user experience and or marketing efforts in this category to increase the likelihood of users making a purchase