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E-Commerce-Data-EDA

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Exploratory Data Analysis (EDA) is performed on the E-Commerce data obtained from a UK-based and registered non-store online retail to discover interesting transactional patterns of different customers and countries.

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# Exploratory Data Analysis (EDA) on E-Commerce data

## Data Source 
https://www.kaggle.com/carrie1/ecommerce-data

## Context of Data 
- Company - UK-based and registered non-store online retail
- Products for selling - Mainly all-occasion gifts
- Customers - Most are wholesalers (local or international)
- Transactions Period - 1st Dec 2010 - 9th Dec 2011 (One year)

## Objectives

Exploratory Data Analysis (EDA) is performed on the E-Commerce data obtained from a UK-based and registered non-store online retail to discover interesting transactional patterns of different customers and countries.

## Results
1. The **customer with the highest number of orders comes from the United Kingdom (UK)** 
2. The **customer with the highest money spent on purchases comes from Netherlands** 
3. The company receives the highest number of orders from customers in the UK (since it is a UK-based company). Therefore, the TOP 5 countries (including UK) that place the highest number of orders are as below: 
    - United Kingdom 
	- Germany 
	- France
	- Ireland (EIRE)
	- Spain
4. As the company receives the highest number of orders from customers in the UK (since it is a UK-based company), customers in the UK spend the most on their purchases. Therefore, the TOP 5 countries (including UK) that spend the most money on purchases are as below: 
    - United Kingdom 
	- Netherlands
	- Ireland (EIRE)
	- Germany
	- France
5. **November 2011 has the highest sales** 
	- The month with the lowest sales is undetermined as the dataset consists of transactions until 9th December 2011 in December 
6. There are **no transactions on Saturday** between 1st Dec 2010 - 9th Dec 2011 
7. The number of orders received by the company tends to increases from Monday to Thursday and decrese afterward
8. The company receives the **highest number of orders at 12:00pm** 
	- Possibly most customers made purchases during **lunch hour between 12:00pm - 2:00pm**
9. The company tends to **give out FREE items for purchases occasionally each month** 
	- However, it is not clear what factors contribute to giving out the FREE items to the particular customers

## NOTES
Kaggle notebook - https://www.kaggle.com/admond1994/e-commerce-data-eda

## Acknowledgements
Per the UCI Machine Learning Repository, this data was made available by Dr Daqing Chen, Director: Public Analytics group. chend '@' lsbu.ac.uk, School of Engineering, London South Bank University, London SE1 0AA, UK.

E-Commerce-Data-EDA

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