Engineer features from survey data
skillx_class_aware_c2__feature_engineering__SKILLskillsetup L2★0
jackal092927/skillX ↗What it does
Convert survey data to DID-ready numeric features
Best for
Preparing respondent-keyed data for difference-in-differences causal analysis.
Inputs
- · cleaned survey CSV
- · respondent demographics
Outputs
- · feature-engineered CSV
- · encoding mappings
Requires
- · pandas
Preconditions
- · Survey ResponseID consistency
- · clean input data
Failure modes
- · Object columns in output
- · identifier leakage
- · row misalignment
Trust signals
- · Explicit binary/categorical mappings
- · pre-handoff validation checklist