# Data Cleaner — messy CSV/Excel/JSON to clean typed data (`amanatools/data-cleaner`) Actor

Clean, deduplicate, and type-infer CSV, Excel, and JSON files from URLs. Returns a quality report, preview rows, and a download link to the cleaned CSV. Built for AI agents and data pipelines.

- **URL**: https://apify.com/amanatools/data-cleaner.md
- **Developed by:** [Dos](https://apify.com/amanatools) (community)
- **Categories:** Developer tools, AI
- **Stats:** 1 total users, 0 monthly users, 0.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

Pay per event

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.

Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event

## What's an Apify Actor?

Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.
Actors are written with capital "A".

## 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.
The best way to integrate Actors is as follows.

- **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 usage examples, see the [API](#api) section below.

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).

# README

## Data Cleaner — messy CSV/Excel/JSON to clean, typed data

Point it at data files; get back **deduplicated, whitespace-trimmed, type-inferred data** plus an honest quality report — and a direct download link to the cleaned CSV. The un-glamorous work every data pipeline and AI agent needs done before anything else works.

### What it does per file

- Reads CSV (separator auto-detected), Excel (.xlsx, any sheet), JSON (records or JSON-lines)
- Normalizes headers; trims whitespace; blanks become nulls
- Drops empty rows/columns; removes duplicate rows
- Infers column types (numbers, dates) when >=90% of values parse
- Outputs: `quality_report`, `preview_rows` (first 20), `cleaned_csv_url` (full file)

### Pricing

Pay-per-event: a small fee per file plus a micro-fee per 1,000 cleaned rows. No subscription.

### Limits

Up to 50 files/run, 100 MB and 250,000 rows per file. Failures return `status: "error"` so pipelines can branch.

### Other actors by amanatools

- [PDF Text Extractor](https://apify.com/amanatools/pdf-table-extractor) — tables and text from PDF files into clean JSON rows
- [PDF OCR Extractor](https://apify.com/amanatools/pdf-ocr-extractor) — scanned and image-only PDFs into searchable text
- [ATS Job Scraper](https://apify.com/amanatools/ats-jobs-extractor) — open jobs straight from Greenhouse, Lever, Workday and more
- [Doc to Markdown](https://apify.com/amanatools/doc-to-markdown) — DOCX, PDF and web pages into clean markdown

# Actor input Schema

## `file_urls` (type: `array`):

Direct links to data files (up to 50 per run, 100 MB / 250k rows each).

## `deduplicate` (type: `boolean`):

Drop rows that are exact duplicates of an earlier row, keeping the first.

## `infer_types` (type: `boolean`):

Cast text columns to numbers or dates when at least 90% of values parse.

## `drop_empty_columns` (type: `boolean`):

Remove columns where every value is empty or null.

## `excel_sheet` (type: `string`):

Which sheet to read from Excel files. Default: first sheet.

## Actor input object example

```json
{
  "deduplicate": true,
  "infer_types": true,
  "drop_empty_columns": true,
  "excel_sheet": "0"
}
```

# API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

## JavaScript example

```javascript
import { ApifyClient } from 'apify-client';

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {};

// Run the Actor and wait for it to finish
const run = await client.actor("amanatools/data-cleaner").call(input);

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

```

## Python example

```python
from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = {}

# Run the Actor and wait for it to finish
run = client.actor("amanatools/data-cleaner").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"])
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{}' |
apify call amanatools/data-cleaner --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "command": "npx",
            "args": [
                "mcp-remote",
                "https://mcp.apify.com/?tools=amanatools/data-cleaner",
                "--header",
                "Authorization: Bearer <YOUR_API_TOKEN>"
            ]
        }
    }
}

```

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/acts/Lm9UwfgDqPY8BVskA/builds/0YAWXle5bgd8gGQJD/openapi.json