Spotisis- Analysis of my Spotify Streaming History
You guys might be wondering how Spotify did the 2020 wrapup for its every user. After reading this you will find it easy and anybody can do it with their Spotify account. I’ll be showing you details about my Spotify Streaming history and I’ll be comparing my music with one of my friend Sreelekshmy. Spotify lets you download your data All you have to do is to go to your privacy settings in the dashboard and click request data. It will be available in 3–4 days even though they tell you it might take 30 days. I’ll be using the JSON file “Streaming History0.json” they provided me for this project. You can find the source code at the GitHub link provided at the end of the article. So let’s get started.
These are the things I’m going to analyze
- Timeline of my streaming history
- Day preference
- Favourite artist
- Favourite songs
- Diversity
- Spirit of songs
Part A
The First Song that I heard from Spotify was Old Town Road (Jessie James Decker Version) which was the first object in my JSON. Even though I heard my first song in the last November I didn’t use Spotify frequently. So the first thing I’m gonna share is my minutes streamed per day. You can see a Spike Starting to rise from March 25 2020. You guys know the reason :D. On August 28 2020. The Graph says I have Streamed about 260 minutes.
I use Spotify mostly when I’m working it makes me do my work faster.
you can see that from the pie chart below.
Favourite Artist — everybody who knows me I’m a big fan of A.R. Rahman and One direction. I have played One direction songs 352 times and A.R. Rahman songs 254 times. But when comes to the uniqueness of songs I have played 61 different songs of A.R. Rahman comparing to 41 of One direction. The bigger the circle denotes bigger is the uniqueness of the songs.
Favourite Song-
In the Graph, you can see one song Staying way ahead of the others. “The Nights”. This is my all-time favourite. The First time I heard this song was during my first year at college. May have heard this More than a thousand times in my entire life.
Spotify provides each song with certain attributes if you’re a musician you might be familiar with some of those. The attributes that Spotify proves for a song are as follows:
Danceability — A description of how suitable a track is for dancing based on a combination of musical elements including tempo, rhythm stability, beat strength, and overall regularity. A value of 0.0 is least danceable and 1.0 is most danceable.
Energy — Energy is a measure from 0.0 to 1.0 and represents a perceptual measure of intensity and activity. Typically, energetic tracks feel fast, loud, and noisy.
Instrumentalness — Predicts whether a track contains no vocals. “Ooh” and “aah” sounds are treated as instrumental in this context. The closer the instrumentalness value is to 1.0, the greater likelihood the track contains no vocal content.
Liveness — Detects the presence of an audience in the recording.
Loudness — The overall loudness of a track in decibels (dB). Loudness is the quality of a sound that is the primary psychological correlate of physical strength (amplitude). Values typical range between -60 and 0 dB.
Speechiness — Speechiness detects the presence of spoken words in a track.
Valence — A measure from 0.0 to 1.0 describing the musical positiveness conveyed by a track.
Tempo — The overall estimated tempo of a track in beats per minute (BPM). In musical terminology, the tempo is the speed or pace of a given piece and derives directly from the average beat duration
Mode — Mode indicates the modality (major or minor) of a track, the type of scale from which its melodic content is derived. Major is represented by 1 and minor is 0.
Key — The estimated overall key of the track.
I’ll be comparing five features of my top 5 songs Danceability, Instrumentalness , Speechiness, energy, loudness.
Do I listen to positive songs?
Spotify also provides one attribute called valence. The valence scale is from 0–1, with one being the most positiveness conveyed in the track.
When I plotted the histogram of my top 50 songs it says I listen to less positive songs. When I plotted Venn diagram it says 28 of songs are low spirits(valence<0.5).
Part B
In this Part, I’ll be comparing my top 50 songs with one of my friend Sreelekshmy’s playlist. I hear more energetic songs but she hears songs having a positive mood than me. and danceability of my songs is higher than her. I have also compared tempo and other audio features of our playlist.
This was my first time using Plotly to analyse data I was able to learn a lot from doing this project. Hoping to do more in Future. This is the link to GitHub repo I have shared my notebook and also an interactive form of my graphs that I showed you above.
