National Premier League -- Indian State Rankings

A dashboard for ranking and comparing Indian states across measurable dimensions of governance and human development. Built on official data from MoSPI, RBI, NFHS, Census, NCRB, UDISE+, and other government sources, it computes normalized scores across 27 categories and 126 metrics for all 36 states and union territories.

Features

• Overall league table with tier-based classification (Champion, Contender, Rising, Developing)
• Category rankings across economy, employment, education, health, and 23 other domains
• State profiles with per-category score breakdowns, population, and regional metadata
• Head-to-head comparison between any two states across all categories
• Interactive choropleth map of India using react-simple-maps and D3 color scales
• Metric-level drill-down pages with bar charts and score distributions
• Static export -- all pages are pre-rendered from generated JSON bundles

Tech Stack

• Framework: Next.js 15 (App Router, Turbopack)
• Language: TypeScript
• UI: React 19, Tailwind CSS 4, Radix UI primitives, Lucide icons
• Charts: Recharts, D3 scale-chromatic
• Maps: react-simple-maps with GeoJSON topology
• Database: SQLite via better-sqlite3
• Data tables: TanStack Table
• Data parsing: PapaParse (CSV), xlsx (Excel)

Data Pipeline

The project includes a multi-step pipeline that ingests, scores, and exports data:

npm run pipeline

This runs the following steps in order:

1. Seed reference data -- loads states, categories, and metric definitions into SQLite
2. Ingest MoSPI data -- connects to the MoSPI MCP server (mcp.mospi.gov.in) and fetches indicator data via a 4-step API workflow
3. Fetch DFI charts -- discovers and downloads chart data from Data For India's public API
4. Transform DFI data -- converts DFI chart JSON into standardized CSV format
5. Ingest CSV data -- loads all curated CSV files (government publications + DFI-derived) into the database
6. Compute scores -- normalizes metrics (min-max with outlier capping at p2/p98), computes weighted category averages, and aggregates into overall rankings with tier assignment
7. Validate data -- checks data integrity
8. Generate JSON -- exports static JSON bundles to public/data/ for the Next.js frontend

Individual steps can also be run separately:

npm run db:seed           # Seed reference data
npm run db:ingest-mospi   # Ingest from MoSPI
npm run db:score          # Compute scores
npm run db:export         # Generate JSON bundles

Getting Started

Prerequisites

• Node.js 18+
• npm

Installation

npm install

Seed and build data

Run the full pipeline to populate the database and generate JSON:

npm run pipeline

Or seed reference data and compute scores from existing data:

npm run db:seed
npm run db:score
npm run db:export

Development

npm run dev

The app starts at http://localhost:3000 with Turbopack for fast refresh.

Production build

npm run build
npm run start

Project Structure

app/
  page.tsx              # Homepage with overall league table
  rankings/             # Full rankings and per-category rankings
  states/               # State listing and individual state profiles
  compare/              # Side-by-side state comparison
  metrics/              # Metric-level detail pages
  about/                # About page
components/
  charts/               # Recharts bar charts and score distributions
  map/                  # India choropleth map (react-simple-maps)
  league-table/         # League table, tier badges, score bars
  layout/               # Header and footer
  ui/                   # Shared UI primitives (Radix-based)
scripts/
  pipeline.ts           # Orchestrator for the full data pipeline
  seed-reference.ts     # Loads reference data into SQLite
  ingest-mospi.ts       # Fetches data from MoSPI MCP server
  scrape-dfi.ts         # Fetches chart data from Data For India
  transform-dfi.ts      # Converts DFI chart JSON to CSV
  dfi-inspect.ts        # Utility to inspect DFI chart structure
  ingest-csv.ts         # Config-driven CSV ingestion (40+ files)
  compute-scores.ts     # Scoring engine (normalize, weight, aggregate)
  generate-json.ts      # Exports JSON bundles for static rendering
  validate-data.ts      # Data integrity checks
lib/
  db.ts                 # SQLite connection helper
  queries.ts            # Database query functions
  scoring.ts            # Normalization, outlier capping, weighted averages
  types.ts              # Shared TypeScript types
  constants.ts          # Tier thresholds and category definitions
data/
  reference/            # Static reference JSON (states, categories, metrics)
  npl.db                # SQLite database (gitignored)

Data Sources

Data is sourced from multiple official government databases:

• MoSPI — National Accounts, PLFS (employment), CPI (prices), ASI (industry) via MCP server
• RBI — State finances, banking statistics
• NFHS-5 — Health, nutrition, women and children indicators
• Census / SRS — Demographics, literacy, mortality, life tables
• NCRB — Crime statistics, police strength
• UDISE+ / AISHE — School and higher education enrollment
• NITI Aayog — Multidimensional Poverty Index
• Data For India — Curated government datasets (CC-BY 4.0)
• Other — DPIIT, GST Council, CEA, FSI, MoRTH, JJM, ECI, MoT