{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "# Roads & Toll Plaza Data Processing\n",
        "\n",
        "**Output:** `toll_plazas_lite.json` -> deployed to `backend/data/roads/`\n",
        "\n",
        "This notebook processes the **NHAI Toll Plaza dataset** to produce a lightweight JSON\n",
        "suitable for the SafeVixAI backend API and offline PWA map layer.\n",
        "\n",
        "---\n",
        "### Dataset\n",
        "- **Source:** NHAI Open Data / custom toll_plazas.csv\n",
        "- **Fields:** Name, NH Number, Latitude, Longitude\n",
        "- **Coverage:** All operational toll plazas on National Highways\n",
        "\n",
        "### Pipeline\n",
        "`toll_plazas.csv -> Select key columns -> Rename headers -> Export toll_plazas_lite.json`"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "## Step 1 - Upload & Process Toll Plaza CSV\n",
        "\n",
        "Upload `toll_plazas.csv` from `backend/data/roads/toll_plazas.csv`\n",
        "\n",
        "The processing pipeline:\n",
        "1. Reads the CSV with `pandas`\n",
        "2. Selects only 4 essential columns: `name, id, lat, lon`\n",
        "3. Drops rows with missing coordinates\n",
        "4. Renames to human-readable headers\n",
        "5. Exports as `toll_plazas_lite.json`\n",
        "\n",
        "The resulting JSON is consumed by the backend `/api/roads/tolls` endpoint\n",
        "and the offline PWA map layer for toll overlay rendering."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 90
        },
        "id": "RjBm7RAZO-O0",
        "outputId": "beacaaad-3b29-4737-8664-ee8c2d92a645"
      },
      "outputs": [],
      "source": [
        "# Cell 1 — Toll Plazas Lite\n",
        "import pandas as pd, json\n",
        "from google.colab import files\n",
        "\n",
        "print(\"▶ UPLOAD your toll_plazas.csv NOW:\")\n",
        "uploaded = files.upload()\n",
        "filename = list(uploaded.keys())[0]\n",
        "\n",
        "toll = pd.read_csv(filename)\n",
        "# The dataset headers are: name, id, lat, lon\n",
        "toll_summary = toll[['name', 'id', 'lat', 'lon']].dropna().rename(columns={\n",
        "    'name': 'Plaza Name',\n",
        "    'id': 'NH Number',\n",
        "    'lat': 'Latitude',\n",
        "    'lon': 'Longitude'\n",
        "}).to_dict(orient='records')\n",
        "\n",
        "with open('toll_plazas_lite.json', 'w') as f:\n",
        "    json.dump(toll_summary, f, indent=2)\n",
        "files.download('toll_plazas_lite.json')\n"
      ]
    }
  ],
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    "kernelspec": {
      "display_name": "Python 3",
      "name": "python3"
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      "name": "python"
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