In this project, we will be analyzing and visualizing sales data to gain insights into customer behavior, product performance, and sales trends. We will be using Python and its data analysis libraries to clean, explore, and visualize the data. The main goal of the project is to provide insights into the following questions:
- Which location has highest and lowest sales? Represent the sales on a barchart, also show the market share for each location using a pie chart.
- Which locations has more female customers and male customers?
- what days of the month make more sales?
- Which branch has more Members vs less Members?
- Which branch has highest and lowest rating?
- which city has more female shopping?
- Who spends more, male or female?
- Which type of customer spends more, member or non-member?
- Which product line sells more?
- Which product line is popular among men and women?
- Which month makes more sales?
The dataset used in this project is a sales dataset that includes information on products, customers and sales. It contains the following columns:
- Invoice ID
- Date
- Time
- Gender
- Location
- City
- Member
- Category
- Price
- Quantity
- Total
- Payment
- Rating