Learn how to create an economic distress index layer using Census data with Python. This blog post guides you through developing an index to identify areas with high economic distress. By condensing multiple economic factors into a single indicator, policymakers can better target interventions. The process involves retrieving Census data, calculating composite index components, computing the economic distress index, adding geographic information, and sharing the feature layer on ArcGIS Online. Automating these tasks with Python streamlines the workflow and enhances efficiency, enabling more effective policy formulation and decision-making.
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