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memory space called pages.
The efficiency depends on the query size relative to the data distribution. A small query in a sparse region prunes almost everything. A query that covers the whole space prunes nothing (because every node overlaps), degenerating to a brute-force scan. The quadtree gives you the most benefit when your queries are spatially local, which is exactly the common case for map applications, game physics, and spatial databases.，详情可参考旺商聊官方下载
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Create a Jupyter Notebook that, using `polars` to process the data, does a thorough exploratory data analysis of data saved in `youtube_videos.db`, for all columns.