The other day I needed to show icons on a logistics dashboard based on the status of a shipment and its current location type (warehouse, transit, port, etc.).

The backend would send something like:

{
  "shipment_status": "Delayed",
  "location_type": "Port",
  "success": true
}

But of course, instead of just three or four simple conditions, the logic was handed to me in an Excel file with 20+ combinations like this:

| shipment_status | location_type | icon | | ---------------- | -------------- | --------------- | | In Transit | Warehouse | "truck-loading" | | In Transit | Port | "cargo-ship" | | Delayed | Port | "warning-ship" | | Delivered | Warehouse | "check-circle" | | Delayed | Transit | "warning-truck" |

At first, I thought of hardcoding the logic like a caveman. But my developer instincts said: “Wait, let’s automate this.”

So I converted the Excel file into JSON using a helper:

function convertToJson(rawExcelTabSeparatedData) {
  // parse rows, trim extra whitespace, and convert to JSON
  return cleanedJsonArray;
}

const ICON_RULES = convertToJson(excelData);

⚠️ Heads-up: Always clean your raw data—remove extra tabs, inconsistent quotes, or trailing spaces.

Now all I had to do was this:

function getShipmentIcon(shipmentStatus, locationType) {
  const rule = ICON_RULES.find(item =>
    item.shipment_status === shipmentStatus &&
    item.location_type === locationType
  );
  return rule?.icon || "default-icon";
}

And voilà! The UI shows the right icon depending on live data from the API.

What’s the takeaway? Sometimes the solution is just: 📄 → 🧼 → 🔄 → .find().

No need to overthink it. Use the language features you already know to turn messy Excel logic into clean JSON-driven code.

And yeah—skip ChatGPT once in a while 😉 Let your brain run wild before you ask the bot.

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