Description:
I haven’t seen many examples showcasing how to effectively represent dimensionality reduction analysis, like UMAP, using ECharts. Therefore, this project provides a clear demonstration of how to combine Python with UMAP to generate a dynamic, interactive view. You can configure and select the parameters needed to visualize the graph.
To get started:
Install UMAP in your local Python environment.
In the configuration view:
Configure the columns that will be used for UMAP calculations (these should be numerical columns).
Adjust the parameters via the configuration panel to fine-tune the visualization.
This workflow demonstrates how to blend Python and ECharts to create an explanatory and aesthetically appealing graph for dimensional reduction analysis using UMAP.