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Analyze child welfare policies with Python.
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Module 1
Acquiring and Preparing Child Welfare Data
1
Navigating Child Welfare Data Sources
Identify key U.S. child welfare data sources (e.g., AFCARS, NCANDS) and relevant demographic data (e.g., ACS).
Accessing and Downloading Datasets Programmatically
Programmatically access and download datasets from public sources using APIs or web scraping.
3
Data Cleaning Strategies for Administrative Data
Address common cleaning challenges in administrative data, such as inconsistent coding and data entry errors.
Integrating Child Welfare Data with Demographic Indicators
Merge child welfare data with demographic indicators from different geographic levels (e.g., tract, county).
5
Reshaping Wide to Long Panel Data
Reshape panel data from wide to long format to prepare for longitudinal analysis.
6
Addressing Missing Data in Child Welfare Records
Apply and justify strategies for handling missing data in child welfare records.
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