Clustering Analysis in Python demonstration notebooks¶
My collection demonstrating useful clustering analysis algorithms and associated visualizations implemented in Python.
The four primary classes of clustering algorithms are hierarchical, centroid, density, and statistical. Presently, the first three of the four are demonstrated here.
Select a notebook from the list below:
Available Demonstration Notebooks¶
Coming soon / available at another link¶
- Here shows a heatmap visualization of public data from CITI Bike from July 2019 of over 2.18 million rides, displaying the connections between stations using Clustergrammer2. Go to there and press the 'launch binder' button to see the Voila form of the notebook. Clustergrammer2 is an interactive heatmap Jupyter widget to help researchers interactively explore single cell data (e.g. scRNA-seq). The notebook/Voila page also uses UMAP which is popular for analysis of single cell RNA-seq data (scRNA-seq).