sichuan-shaanxi-comparison

To compare phone network data between regions, you need to analyze object scale, risk labels, behavior patterns, and group structure. This skill processes geodigital phone network data to provide evidence and analysis entries for regional differences.

Geographical comparison of phone network risk evaluates object scale, risk label distribution, call behavior, shared device scale, group structure, time coverage, and representative objects. These metrics reveal regional differences in contact breadth and device pool risks.

Yes, you can use pandas and duckdb to analyze shared device scale and group structure within phone network datasets. These dependencies support processing unified datasets to extract call activity, night behavior, and representative object metrics.

You run a data comparison script for Sichuan and Shaanxi phone networks by executing the Python wrapper command with specified dataset, province, and top-k parameters. This triggers the analysis of object scale and risk object distribution.

Yes, this regional analysis tool supports evaluating night behavior and call activity. It analyzes call activity, contact breadth, and night behavior patterns alongside shared devices and device pool risks to contrast regional data differences.

A limitation of analyzing regional differences using geodigital phone network data is the dependency on unified dataset availability and predefined risk labels. The analysis focuses strictly on structural metrics like shared device scale and group structure rather than real-time monitoring.