Billboard-Wiki

What it does

It scrapes song names and artists from billboard , the creates a valid Wikipedia link from that data for that particular song . Then it extracts song writers ,artists,song producers ,position and genres for all songs , creates a pandas dataframe and stores it as csv file Then using this data , any new song's popularity can be predicted based on the CSV file data .

Getting Started

These instructions will get you a copy of the project up and running on your local machine for development and testing purposes. See deployment for notes on how to deploy the project on a live system.

Prerequisites

Python or PyCharm

Libraries

panas , beautifulsoup4 , requests and html5lib

Installing

There are two ways you can run the program

1. Using PyCharm

1.1 Just clone the project and Under new option in PyCharm , select this folder and you would be good to go .

2. Using Basic Python

2.1 Install Pandas as

pip install pandas

2.2 Install Requests

pip install Requests

2.3 Install BeautifulSoup4

pip install beautifulsoup4

2.4 Install html5lib

pip install html5lib

Running the tests

1. First set Dates in data.py as to from which date to whic date you want the billboard data for .
2. Change the number by which i is divided .From this you can change intervals , as to once per 30 days if the number is 30
3. Run main.py and then it will generate a csv file name example .csv
4. Run the Scikit jupyter notebook file and any new song's popularity can be predicted using trained data.