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 .
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.
Python or PyCharm
panas , beautifulsoup4 , requests and html5lib
There are two ways you can run the program
1.1 Just clone the project and Under new option in PyCharm , select this folder and you would be good to go .
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
- First set Dates in data.py as to from which date to whic date you want the billboard data for .
- 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
- Run main.py and then it will generate a csv file name example .csv
- Run the Scikit jupyter notebook file and any new song's popularity can be predicted using trained data.