Anomaly detection is a crucial in any Data Science project. It's an important component during Exploratory Data Analysis and sometimes it's overlooked.
In this project I show the steps (methodology) that I followed for Anomaly Detection in my own personal Spotify data (only song features). I implemented a characterisation of the dataset with K-Means algorithm and parallely used Local Outlier Factor, to find the anomalies/outliers.
Here you can find the notebook where the anomaly detection analysis is performed (here) and how I got the data (here)
