Exploratory Data Analysis on Sales Dataset

###Project Statement
Exploratory data analysis, or EDA, is an important aspect of data science. It allows us to analyse data sets and summarise them with visuals and findings.

In this project, I’ll be analysing a Sales data set available on Kaggle. The sales dataset contain information abour products, categories, dates, and basic information of customer with location. I’m hoping that by the end of this project, I will better understand the relationships that sales, most sold products, and other demographics have on workplace-related things.

The purpose behind choosing this data set to study is to understand sales in current market, product demands, trend in sales, delivery details based on location etc.. This dataset is good example dataset not a realtime data however it'll be very good dataset for a beginner to understand structure of current sales data in real world

Sales dataset is a publically available dataset from Kaggle, This is the link to the dataset https://www.kaggle.com/datasets/akavinashk07/sales-dataset

Introduction about dataset

This is Sample data set which have information about sales of products across different countries of world. It contains 51290 rows and 20 columns of data. This is a practice dataset for begineers to understand data analysis. It has data only for the yeat 2015. Below are the the column description, we will understand more on datatypes and size as we proceed through project

About Dataset

1. Order ID - Unique order ID reference to each order
2. Order Date - Date of Order
3. Shipping Date - Delivery date of Order
4. Aging - Difference between shipping date and order date
5. Ship Mode - Mode of shipping
6. Product Category - Category of the product
7. Product - Product description
8. Sales - Product of Quantity and Unit price (in US dollars - $)
9. Quantity - Unit quantity of the order
10. Discount - Percentage of discount with respect to unit price
11. Profit - Shippping cost percentage is considered as profit
12. Shipping Cost - Delivery Charges in US dollar
13. Order Priority - Priority of the order
14. Customer ID - Unique ID for each order
15. Customer Name - Name of the customer
16. Segment - Customer professional category
17. City - City of the customer located / product delivered
18. State - State of the customer located / product delivered
19. Country - Country of the customer located / product delivered
20. Region - Region of the customer located / product delivered