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
- Order ID - Unique order ID reference to each order
- Order Date - Date of Order
- Shipping Date - Delivery date of Order
- Aging - Difference between shipping date and order date
- Ship Mode - Mode of shipping
- Product Category - Category of the product
- Product - Product description
- Sales - Product of Quantity and Unit price (in US dollars - $)
- Quantity - Unit quantity of the order
- Discount - Percentage of discount with respect to unit price
- Profit - Shippping cost percentage is considered as profit
- Shipping Cost - Delivery Charges in US dollar
- Order Priority - Priority of the order
- Customer ID - Unique ID for each order
- Customer Name - Name of the customer
- Segment - Customer professional category
- City - City of the customer located / product delivered
- State - State of the customer located / product delivered
- Country - Country of the customer located / product delivered
- Region - Region of the customer located / product delivered
# Installing opendatasets library
!pip install opendatasets --upgrade --quiet
import opendatasets as od
# Dowloading dataset using opendatasets
od.download('https://www.kaggle.com/datasets/akavinashk07/sales-dataset')
Please provide your Kaggle credentials to download this dataset. Learn more: http://bit.ly/kaggle-creds
Your Kaggle username: trineshnk
Your Kaggle Key: ··········
Downloading sales-dataset.zip to ./sales-dataset
100%|██████████| 6.53M/6.53M [00:00<00:00, 99.9MB/s]