In this project we will web scrape, clean and analyse data about metal bands from all over the world. The goal is to answer the following questions:
- Which countries are the most metal bands from in total numbers and by population?
- What are the most popular sub-genres and lyrical themes?
- Are there differences in the questions above for bands that are independent or signed to a label?
- Are there differences in the questions above for bands from different world regions?
The data we use is web scraped from Encyclopaedia Metallum: The Metal Archives (https://www.metal-archives.com/) that is an online encyclopedia based upon musical artists who predominantly perform heavy metal music along with its various sub-genres. It attempts to provide comprehensive information on each band, such as a discography, logos, pictures, lyrics, line-ups, biography, trivia and user-submitted reviews. The site also provides a system for submitting bands to the archives. The website is free of advertisements and is run completely independently.
The data about country population is sourced from https://www.cia.gov/the-world-factbook and stored as CSV file worlds_popultion.csv.
To generate a geographic heat map with python library GeoPandas a shapefile was downloaded from https://www.naturalearthdata.com/downloads/10m-cultural-vectors/10m-admin-0-details/.
- To create the SQLite database run create_metal_db.py, a python script using the Sqlite3 library. It will also create the table "band_info" in which later the scraped data is committed. The table contains the following columns:
- band_id: an integer as the auto-incremented primary key
- band_name: the bands name, that do not have to be unique
- url: the unique URL to the band's site on metal_archives.com
- country_of_origin: the country the band was founded
- location: the city or region the band is located
- status: status of activity (activ, on hold, split up, changed name, unknown)
- formed_in: year of founding
- genre: type of played metal style, can be more than one genre
- lyrical_themes: topic of lyrics, can be more than one theme
- current_label: the current music label the band is signed or unsigned/independent
- years_active: time ranges the band was activ, sometimes with additional information
- data_retrieved: the date the data set was retrieved from the given URL
- To scrape the data run web_scraping_metal_archives.py. To get a list of bands and their websites URL it has to use the Selenium library. It allows to open the websites in a browser which is necessary to run JavaScript. Only in this way we get access to some needed data and are able to automate to change sites by click. To use Selenium in this script you need the Chrome browser and the latest version of Chromdriver which controls the browser. To finally collect the data from the individual band websites the script uses the Beautiful Soup library. For further information take a look at the comments in the python scripts. The data in the deposited database was retrieved between 15.12.2022 - 17.12.2022.
Additional to the highlighted libraries you also need: String, Time, Request and Datetime
The process of cleaning and analysing the data is described in Jupiter notebook analyse_metal_archives.ipynb.
