This project is an analysis of Olist dataset, aimed to gain insight into the performance of the company in the Brazilian market. Through data analysis, we can identify different trends and patterns in Olist's customers in Sao Paulo, such as the most popular product categories, the highest total price share of product categories, the most used payment type, and the days and times when many customers placed orders. Additionally, we can also look at the time delta between the estimated delivery time and the actual delivery time, as well as the top product categories by purchase day and purchase time. From these analysis, we can develop marketing strategies and product offerings to better reach the Sao Paulo customer base and ensure the best customer experience.

This project combines sqlite3 and pandas for extracting needed data for analysing those values. Matplotlib and Seaborn were used to plot figures accordingly.

Result of analysis can be read here: https://medium.com/@myonisme/olist-68a829619fb7