This shows examples of CorrPlot and Graph using the same underlying correlation data. CorrPlot displays correlation matrices with hierarchical clustering dendrograms. Graph visualizes correlations as a network with nodes and edges. Both charts demonstrate different ways to explore the same correlation structure.
A Correlation Plot with Dendrogram shows relationships between variables using hierarchical clustering. The dendrogram (top) groups similar variables based on their correlation patterns, with clustering performed dynamically in your browser. Note that it will only appear if i) you select order by dendrogram and ii) you select all of the variables. The correlation matrix (bottom) uses two different correlation measures: Pearson correlations (top-right triangle, marked with 'P:') measure linear relationships, while Spearman correlations (bottom-left triangle, marked with 'S:') measure monotonic relationships and are robust to outliers. You can change the clustering linkage method (Ward, Average, Single, Complete) to see different groupings. Variables are automatically reordered by the clustering to reveal correlation blocks. See here for CorrPlot examples
Data: stock_corr_data.parquet
This Graph allows you to visualise the relationships between variables. The dataformat to make this is a DataFrame with columns: node1, node2, strength, scenario, correlation_method, sector. See here for more Graph examples
Data: stock_corr_data.parquet
This page was created using JSPlots.jl v0.4.1.