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Our project for the "Data and Results Visualization" exam at Politecnico di Milano. The project was about visualizing scraped data from Spotify, searching for an interesting "storytelling".

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Spotify Top30 Visualization

Politecnico di Milano

Open All Collab Spotify

Spotify is a Swedish music streaming and media services provider that was founded in 2006. Since then, its popularity has grown year after year, reaching 299 million active monthly users and being available in 92 countries. These numbers, together with the ability to easily access a large amount of raw data and related services, make Spotify the perfect candidate for an analysis focused on world music preferences and their evolution over time.

Building the dataset

Since no previous source is shaped according to our will, we started scraping from Spotify Charts, a website which collects the daily regional Top200 charts for 65 countries in the world. Then, to enrich the available information for each song, we exploited the Spotify for Developers API, which provided us additional songs' attributes, such as danceability, energy, loudness, instrumentalness and tempo.

Data exploration

In the preliminary phase, the problem was introduced, showing on the map the states under investigation and the number of streams for each of them, considering also the relative population. Annual spotify statistics were also highlighted, delving into the contributions of each continent. Finally, the trend of the number of streams revealed peaks attributable to the release of albums by major international artists, such as Drake, Ariana Grande and Post Malone.

time analysis

Spread analysis

In this section we have selected some interesting case studies to show how national hits can impact on the global audience. We started with Tilidin, a german success, which was not able to cross borders, except for neighboring Austria. Same behaviour also for the italian Soldi which, however, differs for the peak of streams across Europe due to the Eurovision contest. If In My Feelings was an instant hit everywhere, much more interesting is the trend of Dance Monkey (in picture) which has conquered the top of the worldwide charts over the course of months.

spread map

Country study

In this section, we explored national music tastes based on song attributes, seeking to understand if there were any interesting relationships. For example, it turns out that in South America, songs exhibit higher energy and loudness, while acousticness seems accentuated in Eastern countries. Finally, Brazil clearly stands out for songs with high levels of liveness.

country features

Seasonality

In the last section, we looked for possible relationships between song characteristics and the time of the year in which they were released and entered the charts. Considering the songs that had a worldwide success, it is possible to find more energy in spring and summer, while in winter are more frequent more acoustic and sadder songs.

seasonality

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Our project for the "Data and Results Visualization" exam at Politecnico di Milano. The project was about visualizing scraped data from Spotify, searching for an interesting "storytelling".

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