This is a project based on simulated data of people returning to Nepal from diffirent countries. Based on their data (gender, area of involvement, skills and experience, amount of fund they allocate for entrepreneurship etc) saved in a remote database, we will create a dashboard for the general data view. This dashboard will utilize a data integration through MongoDB database and RESTful API built with Express.js.
RESTful(MVC -model) (Node.js and Express.js) |
Python(Numpy,Pandas, Matplotlib) | MongoDB (NoSQL paradigm) |
|---|---|---|
 |
 |
 |
Express.js build on the top of Node.js is implemented to create a web app. |
Python(pymongo) will be used to study the data and create a database and data management over MongoDB | MongoDB as a noSQL database is used to manage the simulated data |
| Lecture : Server-side Development with NodeJS, Express and MongoDB | Lecture : Python Programming: A Concise Introduction | Lecture : Data Wrangling with MongoDB |
| Implement random data generator in Python | Implement Python API to manage data in MongoDB | Implement Node.js and express.js to create a RESTful web app | Create Data visualization dashboard using d3.js and chart.js] |
|---|---|---|---|
 |
 |
 |
 |
| Random migration data will be generated by data generator class written in python, in real data collection scenario and web app will be used to collect the data from users | Simulated data in the MongoDB database will be used in web app made for visualization, pymongo will be used to play around with data | Chart.js and D3.js are data visualization tools in web apps along with Node.js and Express.js | Once internal working API are created, front line view will be design with HTML,CSS and java script |
| Task | Skills | Detail | Due |
|---|---|---|---|
| 1. Random data generator | Python | Create a random migration data generator(Class) in Python(OOP). | First month |
| 2. Use Scikit learn, Numpy, Pandas and Matplotlib(Seaborn) to create static data visualization (distribution, geogrphical plots, clustering etc.) | Python(basic) and packages | Simulated data has different properties to be explored. Implement exploratory data analysis over the simulated data. | Second month |
| 3. Implement Pymongo to create MongoDB database | Python and MongoDB | Learn to implement database using Pymongo, Python and MongoDB. Simulated data will populate the MongoDB database. | Third month |
4. Use d3.js and chart.js to create interactive data visualization (charts, networks, distribution etc) |
javascript(basic) and packages | Simulated data has different properties to be explored in interactive mode. Data will be imported from MongoDB database. | Fourth month |
5. Wrape up the interactive plots in an Express.js app framework(RESTful) |
Express.js and Node.js |
Interactive data visulation can be made more dynamic. | Fifth month |
6. Create a front line for web app using basic front end(HTML,CSS and javascript) along with Express.js(RESTful) Model-View-Controller (MVC) |
Basic front end (HTML,CSS, javascript) | Fully developed data visualization dashboard will be ready to be deployed in real data. | Sixth month |
