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This walkthrough demonstrates how to greatly accelerate data diagnostics, ingestion, and analysis with DAAF (the Data Analyst Augmentation Framework) and Claude Code, for any dataset you can imagine. In this video, we ingest U.S. presidential election data from the MIT Election Data and Science Lab (via Harvard Dataverse) and use DAAF's built-in ingestion and analysis pipelines to recreate the well-known "red shift" visualization from the New York Times -- all in about 10 minutes of analyst effort. Don't know what DAAF is? DAAF (the Data Analyst Augmentation Framework) is an open-source, forever-free, extensible workflow for Claude Code that allows skilled researchers to rapidly scale their expertise and accelerate data analysis by as much as 5-10x -- without sacrificing the transparency, rigor, or reproducibility demanded by our core scientific principles. Not sure what DAAF is? Learn more at our open-source GitHub project here! https://github.com/DAAF-Contribution-... Or take a peek at my 10-minute walkthrough demo of all of the main functions of DAAF here: • DAAF Complete End-to-End AI Data Analysis ... TIMESTAMPS: 0:00 Introduction and video context 0:56 What is DAAF? 1:58 Sourcing the data 2:34 Starting the data ingestion process 3:52 Creating a dataset Skill 5:24 Auditing the data ingestion process 6:04 Testing DAAF with the new data 6:36 Building a dataset Skill ecosystem 7:15 Running a full analysis with the new data 8:42 Finished visualization and comparison 9:06 Self-improving dataset Skills with DAAF 10:04 Wrap-up and what's coming next ADDITIONAL LINKS AND RESOURCES: The DAAF Field Guide (Substack tutorials): https://daafguide.substack.com NYTimes Original Visualization: https://www.nytimes.com/interactive/2... MIT Election Data and Science Lab County Presidential Election Data: https://dataverse.harvard.edu/dataset... Harvard Dataverse: https://dataverse.harvard.edu/ #dataanalytics #DataVisualization #DataScience #DAAF #AI