It is often said that popular music increasingly homogenises. It all ‘sounds the same’
in favour of synthetic dance music. In your project, you will put this hypothesis
to the test by comparing the top hits in of the past 50 years for their audio
features (1970-2019). You need to mould this research problem into a testable
hypothesis. consider the relations between time and aggregated audio features
1. Scrape Billboard hot 100 data in the past 50 years (1970-2019) from
billboard.com. Scrape the artist and track titles. Store this in a csv file with three
variables: year, artist, and track. (for the years 1991-2005 it returns the 2006
data. use the dataset provided: http://www.digitalanalytics.id.au/static/files/chartdata.csv. )
2. Gest track ID, query the combination of artist and track in the Search
Endpoint. Write the results into a new version of csv. (adding a variable trackid).
3. Ues The Spotify API to get audio features. Audio Features Endpoint:
– Read this saved file (enriched with track IDs)
– breaking down the project in multiple steps
– keeping a record of these steps in multiple code and data files. Using the
Audio Features Endpoint, it is up to you to decide what audio features you
consider and to defend the question.
Check that you are getting  response codes, and not  responses.
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