{"version":"1.0","type":"rich","title":"Gist 4063106","description":"This example visualizes the density distribution of bicycle data from the `table_2007_2009_bicy` dataset, dividing points into five quantile-based buckets. It shows how the maximum point count and density vary across these buckets, revealing spatial clustering patterns. The SQL code uses CartoDB functions such as `st_snaptogrid` and `CDB_XYZ_Resolution` to aggregate points into grid cells at a given zoom level, then calculates density per cell and assigns quartiles via `ntile(5)`. The final output summarizes each bucket’s maximum values, providing a statistical overview of the underlying geographic data.","provider_name":"VizHub AI Studio","provider_url":"https://next.vizhub.com","html":"<iframe src=\"https://next.vizhub.com/viz/gist-4063106?mode=embed\" width=\"960\" height=\"500\" scrolling=\"no\" frameborder=\"1\"></iframe>","width":960,"height":500,"cache_age":3600}