Welcome, data enthusiasts! In this month extra articles, we embark on an intriguing journey through a Kaggle dataset sourced about Spotify. Our focus is on analyzing the tracks streamed in 2023 and seeking for interesting pattern before graphing it on an interactive dashboard in Power BI.
Data Exploration of Music Trend
In the realm of data exploration, a recent expedition led me to a Kaggle dataset that promised to unveil the intricate patterns woven into Spotify's musical tapestry. Armed with this treasure trove, my journey began with a meticulous dance of data cleansing and enrichment using the Spotify API.
The first revelation was temporal in nature—the mean release date hovered around 2018, but a closer inspection unveiled a fascinating surge in musical creations between 2020 and 2022. This temporal clustering hints at a dynamic and evolving musical landscape, perhaps reflective of an industry in constant flux.
Diving into the beats and rhythms, the data painted a lively picture in a preliminary observation. With a mean bpm of 122, and dance ability and energy percentages reaching 67% and 64%, respectively, it became clear that Spotify audiences have a preference for high-tempo, dynamic tunes. The beats per minute resonated with a pulsating energy, capturing the very pulse of the listeners. This makes perfect sense since majority of Spotify users are under the age of 35, whom tastes of music are more dynamic than older ones.
A noteworthy trend emerged when examining the average artist count, slightly surpassing 1.5. This hints at a prevailing preference for collaborative efforts or group performances, underscoring the idea that musical synergy often trumps solo acts in the eyes (and ears) of the Spotify audience.
Data Processing
With the raw data in hand, the next act in our data symphony involved processing and refining. Data conversion to suitable types set the stage, followed by a strategic approach to cleansing and filling the gaps.
The challenge at hand included missing values in "in_shazam_charts," "key," and "image_url." While the latter was deemed unreachable from the Spotify API and left untouched, the former two required a delicate touch. Enter K-NN, our trusty ally in the world of imputation.
Considering the 12 available keys, a decision was made to group them into approximately five categories. The 199 unique values for "in_shazam_chart" proved too diverse for a straightforward mapping, leading to the creation of clusters representing ranges such as 0-99, 100-199, 200-299, 300-499, and 500+. The dance of data imputation ensued, harmonizing accuracy and efficiency in equal measure.
Data Analysis on Spotify Dataset
As the layers of data unfolded, intriguing patterns and revelations emerged in the exploration of Spotify's music trend in 2023. As can be seen from the Power BI dashboard above, a spotlight on release patterns uncovered a rhythm aligned with the calendar—Thursday and Friday stood out as the preferred days for musical debuts, strategically timed to capture the attention of audiences gearing up for the weekend.
Delving deeper into song characteristics revealed a fascinating correlation between virality and specific attributes. Viral tracks, it seems, often boast high valence (reflecting mood) or energy. This discovery provides a glimpse into the psyche of the Spotify audience, suggesting that emotionally uplifting or energetically charged songs hold the key to resonating and spreading like wildfire across the digital airwaves.
Conclusion
In the grand symphony of data exploration and analysis, each note plays a crucial role in unraveling the mysteries of the musical universe. As the journey continues, these insights not only become the building blocks for understanding young people choice of music, but also suggest the direction of song writing for undiscovered artists wanting to go viral.
It’s intriguing to see how Spotify's trends are shaping the music landscape. The data-driven approach really highlights the shifts in listener preferences and emerging genres. This kind of insight is invaluable for understanding current trends and predicting future shifts in the music industry. Learn more about Spotify promotion here: https://artistpush.me/collections/spotify-promotion