Creating Local-Level Geographic Datasets

Creating Local-Level Geographic Datasets

A practical, illustrated guide for sub-county policy analysis

Author

Aaron Schroeder

Published

June 4, 2026

Creating Local-Level Geographic Datasets

Creating Local-Level Geographic Datasets
1 The Sub-County Data Gap
2 The Problem of Misaligned Boundaries
3 The Data
4 The Core Method: Areal Interpolation
5 Worked Example: Arlington, Step by Step
6 Results & Interpretation
7 A Second Approach: Parcel-Based Redistribution
8 Limitations & Uncertainty
9 Apply It to Your Own Jurisdiction
10 The Complete Pipeline Code (Python)
11 The Complete Pipeline Code (R)
References

Creating Local-Level Geographic Datasets

Digital equity across Arlington’s 62 civic associations: median household income against broadband download speed.

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1 The Sub-County Data Gap