Transforms prediction market datasets into standardized Nixtla formats for seamless time-series forecasting.
The Nixtla Contract Schema Mapper is designed to bridge the gap between raw prediction market data and advanced forecasting engines like TimeGPT and StatsForecast. It automates the process of mapping arbitrary column names to the required Nixtla schema (unique_id, ds, y), ensuring data integrity through strict date parsing and numeric type validation. This skill is essential for developers and data scientists who need to rapidly prepare datasets for model benchmarking or production-ready forecasting services with built-in visualization and transformation summaries.
主な機能
01Support for both TimeGPT (API-based) and StatsForecast (Open Source) engines
020 GitHub stars
03Automated mapping of custom CSV headers to standard Nixtla columns
04Comprehensive transformation summaries including series count and value ranges
05Built-in time-series visualization for data verification
06Validation of date formats and numeric target values
ユースケース
01Preparing raw financial time-series data for TimeGPT benchmarking
02Standardizing disparate data sources for automated FastAPI forecasting services
03Converting Polymarket or election contract exports for price trend analysis
