This is the course project of Data Warehousing and Data Mining Technology at Peking University.

This project consists of client, server and database, aiming to visualize the distribution of the Bank Marketing Data Set.

The client is implemented by HTML/CSS and JavaScript. I used Bootstrap and jQuery to simplify the process. What's more, the visualization work is under the help of the powerful interactive data visualization tool ------D3.js.

The documents for client are contained in the folder static.

The server is coded with Python, under the framework of Flask.

The document for server is the file app.py.

The database I use is MySQL. It's easy and free to establish your own databases through MySQL.

The file to establish the database is setup_database.sql.

##About the Data The data used in this project is the Bank Marketing Data Set. It contains 45211 records. Each record consists of 17 attributes. I only select 9 of them to visualize their distribution.

The data is in the folder data.

1. Download the project and put the project folder on the Desktop.
2. Open MySQL on your terminal. Run the setup_database.sql file to establish the database.

$ source ~/Desktop/BankMarketingDataSet-master/setup_database.sql

3. Run the server on your terminal.

$ python app.py

4. Open your browser (better using Chrome in full-screen mode) and visit localhost:5000. Then enjoy playing with it!

Note: In Basic mode, users can add only one constraint on each of 9 attributes. While in Advance mode, users can freely add several constraints on each attribute at the same time.

[1] Documentation of Flask: http://docs.jinkan.org/docs/flask/

[2] Official website of D3.js: https://d3js.org/

[3] Some tutorials about HTML/CSS/JavaScript/Python: http://www.runoob.com/