Data Sources

There is enormous interest in building a better understanding of how evidence and data can inform policy. New possibilities have opened up to enable data to be shared and used across states and agencies. One is a technical approach – the Administrative Data Research Facility – which provides a secure environment within which education, training, and workforce data can be shared across agencies and states. The other is human – the Applied Data Analytics training program – which trains government agency staff how to combine and use the data to serve their agency missions. Over 650 participants from over 150 agencies have participated and produced new products and new networks in the process. This presentation discusses the approach sponsored by the California Department of Social Services, joint with the Department of Education and the Economic Development Department. The D-Lab worked with the Coleridge Initiative to successfully combine the two approaches. The presentation will also address the broader vision of how approaches like this can serve to democratize data for the United States.

Pandas is a Python package that provides fast, flexible, and expressive data structures designed to make working with 'relational' or 'labeled' data both easy and intuitive. It enables doing practical, real world data analysis in Python. In this workshop, we'll work with example data and go through the various steps you might need to prepare data for analysis.

Participants in this workshop will learn about some of the issues surrounding the collection of health statistics, and will also learn about authoritative sources of health statistics and data. We will look at tools that let you create custom tables of vital statistics (birth, death, etc.), disease statistics, health behavior statistics, and more.