I have submitted a single jupyter notebook containing all the tasks. Following is an outline of the file describing the steps for the tasks.
pandas NumPy scikit-learn seaborn scipy plotly networkx
Task 1: Exploratory Data Analysis - Imports - Read data - EDA on raw data - DataFrame Statistcs - Univariate Analysis - Bivariate Analysis - Duration vs Bike Type - Duration vs Passholder Type - Duration vs Trip Route Category - Passholder Type vs Bike Type - Passholder Type vs Trip Route Category - Bike Type vs Trip Route Category - Adding Attributes - EDA on processed data - Univariate Analysis - Bivariate Analysis - Day vs Duration - Part of Day vs Duration - Day vs Bike Type - Part of Day vs Bike Type - Day vs Passholder Type - Part of Day vs Passholder Type - Day vs Trip Category Type - Part of Day vs Trip Category Type - Sunburst Charts - PCA and Clustering Analysis - PCA Analysis - Clustering Analysis - Statistical Tests
Task 2: Clustering Analysis - Imports - Visualisation - Full Data Visualisation - PCA reduced Data analysis - KMeans - Workflow - Fit models - Visualise Clusters - Sihouette Analysis - Inital Model Selection - Inertia Analysis - Model Selection - Conclusion - Gaussian Mixture Models - Workflow - Fit models - Visualising clusters - Model Selection - Conclusion - Results
Task 3: Network Analysis - Statistics - Degree - Connected Components - Diameter - Clustering Coefficient - Betweenness Centrality - Assortavity - Visualisation - Conclusions and Learnings