Concerts are a way for the artists to perform their art of music in front of an audience, regardless of the size of that audience and the type of music. Our goal for this project is to predict the prices of the concert tickets of America’s top artists.
We aim to obtain the dataset by web scraping a concert ticket selling website: Razorgator. Since we have yet to begin the data collection process, we assume that the dataset will contain the following features:
- Artist: A band or an individual that will perform live music.
- City: The city that the concert will occur in.
- State: The state that the concert will occur in.
- Venue: The venue that the concert will occur in.
- Date: The date that the concert will occur on.
- Day: The day that the concert will occur on.
- Time: The time that the concert will occur at.
- Level: Front, middle, and last sections/rows.
- Price: The price of the concert ticket.
In addition, we will add a feature that contains the average salary of the state that the concert will occur in.
- Beautiful Soup and Selenium for web scraping.
- Pandas and Numpy for data manipulation.
- Sklearn for linear regression.
- Matplotlib and Seaborn for plotting.
- Tableau for interactive visualizations.
The second project - T5 Data Science Bootcamp
Tuesday, October 5, 2021