# Flatten Scraper Output to Excel

**Use case:** 

Turn messy nested scraper output into a flat, clean table and export it straight to a ready-to-use Excel file.

## Input

```json
{
  "data": [
    {
      "name": "Product A",
      "price": "19.99",
      "shop": {
        "name": "Store One",
        "rating": "4.5"
      },
      "tags": [
        "new",
        "sale"
      ]
    }
  ],
  "flatten": true,
  "flattenSeparator": "_",
  "dedupMode": "none",
  "dedupKeys": [
    "Email"
  ],
  "similarityThreshold": 0.9,
  "keepStrategy": "most_complete",
  "cleanFields": true,
  "stripHtml": false,
  "coerceTypes": true,
  "emptyToNull": true,
  "dropEmptyFields": false,
  "exportFormats": [
    "csv",
    "xlsx"
  ],
  "maxItems": 0
}
```

## Output

```json
{
  "Company Name": {
    "label": "Company Name",
    "format": "text"
  },
  "Email": {
    "label": "Email",
    "format": "text"
  },
  "Phone": {
    "label": "Phone",
    "format": "text"
  },
  "Website": {
    "label": "Website",
    "format": "link"
  },
  "Bio": {
    "label": "Bio",
    "format": "text"
  },
  "Founded": {
    "label": "Founded",
    "format": "number"
  },
  "Active": {
    "label": "Active",
    "format": "boolean"
  },
  "Details_hq_city": {
    "label": "HQ City",
    "format": "text"
  },
  "Details_hq_state": {
    "label": "HQ State",
    "format": "text"
  },
  "Details_tags": {
    "label": "Tags",
    "format": "text"
  },
  "Offers": {
    "label": "Offers",
    "format": "text"
  }
}
```

## About this Actor

This example demonstrates how to use [Dataset Cleaner & Exporter](https://apify.com/nerolabs/dataset-cleaner-exporter) with a specific input configuration. Visit the [Actor detail page](https://apify.com/nerolabs/dataset-cleaner-exporter) to learn more, explore other use cases, and run it yourself.


## How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.
This Task's input is already configured above — use it as-is rather than inventing a new one.

- **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use).
- **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`.
- **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`.
- **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`.
- **Any other language** — the [REST API](https://docs.apify.com/api/v2.md).

For full API examples (JavaScript, Python, CLI, MCP, OpenAPI), see this Task's Actor page: https://apify.com/nerolabs/dataset-cleaner-exporter.md

For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt).
