This analysis explores a dataset of human motion primitives, focusing on preprocessing, exploratory data analysis (EDA), and clustering. Data is loaded from multiple text files, cleaned, and normalized. EDA includes summary statistics, distributions, boxplots, and scatter plots, as well as a correlation heatmap. Clustering is performed using K-means, with the optimal number of clusters determined via the elbow method, and hierarchical clustering is applied to a sample of the data. The clustering results are evaluated using the Hopkins statistic and Davies-Bouldin Index. This comprehensive analysis provides insights into the dataset's structure and clustering tendencies.

An introduction

Histograms